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CLAUDE CODE FULL COURSE 4 HOURS: Build & Sell (2026)

CLAUDE CODE FULL COURSE 4 HOURS: Build & Sell (2026)

Nick Saraev

8060 segments EN

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[00:00]

Hey, this is the definitive course on

[00:01]

Cloud Code for beginners. I use Cloud

[00:03]

Code every day to manage a business that

[00:05]

does over $4 million a year in profit. I

[00:07]

also teach over 2,000 people how to use

[00:09]

Cloud Code both for personal and then

[00:11]

corporate or professional tasks. So,

[00:13]

this is more or less what I do all day.

[00:15]

Once you understand what I'm about to

[00:17]

show you in this course, it's no small

[00:18]

stretch to say that Cloud Code will

[00:20]

augment your productivity. You'll gain

[00:22]

leverage in areas that you probably

[00:23]

didn't even realize that you had. And

[00:25]

that's both for software engineering and

[00:27]

also other parts of your life. The focus

[00:29]

here is not software per se, so you

[00:31]

don't need to have a technical

[00:32]

background to understand what I'm going

[00:33]

to tell you. I'll make sure to start

[00:34]

slow and build concepts on each other

[00:36]

naturally and gradually so that

[00:38]

everybody here is on the same page. So,

[00:39]

no fluff. Here's what you guys are going

[00:41]

to learn in this course. We're going to

[00:42]

start with the basics by downloading and

[00:44]

then setting up cloud code ourselves.

[00:46]

I'll then teach you all about integrated

[00:48]

development environments or idees.

[00:50]

There's several on the market and I'm

[00:52]

going to walk you guys through the three

[00:53]

most commonly used ones so that we're

[00:55]

all on the same page. Afterwards, I'll

[00:57]

show you how to set up your project

[00:58]

brain, which is also known as the

[01:00]

claw.md file. Once we're done with that,

[01:02]

we'll use Claude Code to actually build

[01:04]

something because the focus of this

[01:06]

whole course is on practical building.

[01:08]

We'll build a simple web app hosted live

[01:10]

on the internet, which I'll help you

[01:11]

guys learn by doing, not just sitting

[01:13]

around and listening to me. After that,

[01:14]

we'll cover the Claude directory, the

[01:16]

sub aents folder, and a bunch of

[01:18]

functionality that not a lot of people

[01:19]

know about. We'll then cover Claude

[01:21]

Code's various modes, including their

[01:23]

plan mode, which you guys might have

[01:24]

heard about. Dangerously skip

[01:26]

permissions mode, which gained a fair

[01:27]

amount of uh notoriety recently, and how

[01:29]

to use them, as well as use them safely.

[01:32]

We'll then cover complex project builds

[01:34]

using plan mode and what I just showed

[01:35]

you guys. After that, we'll cover

[01:37]

context management, which is quite the

[01:39]

term right now. I'll teach you guys all

[01:40]

about how to manage your context

[01:42]

efficiently, avoid context rot, and

[01:44]

ensure that your prompts are built and

[01:45]

structured in a high ROI way. I'll run

[01:47]

you through every slash command in Cloud

[01:49]

Code and how to use all of them. We'll

[01:50]

then cover hooks, which are custom

[01:52]

scripts that you guys can fire

[01:53]

automatically before or after every

[01:54]

Cloud Code tool call. Very useful to

[01:56]

know. I'll then talk about Claude Code

[01:58]

skills, which is basically how to create

[01:59]

these skill files that turn Claude code

[02:01]

into a bunch of different specialized

[02:03]

agents. We'll then cover model context

[02:05]

protocol and how to set it up

[02:06]

effectively. I'll talk about a handful

[02:08]

of automated systems that you guys can

[02:09]

quickly build with model context

[02:11]

protocol, including email managers. You

[02:13]

can build your own bookkeeper and more.

[02:15]

I'll cover cloud code plugins and

[02:16]

marketplaces. The Chrome DevTools

[02:19]

integration, which is a very slept on uh

[02:21]

connection between Cloud Code and Chrome

[02:23]

that enables you to collect data from

[02:25]

sources that don't have APIs. It's very,

[02:27]

very valuable to learn. We'll then cover

[02:29]

Cloud Code sub agents with scoped tool

[02:31]

access. I'll talk about their new agent

[02:33]

team feature and how to use them

[02:34]

productively. and then get work trees

[02:36]

and session mobility which essentially

[02:37]

will allow you to spin up parallel cloud

[02:39]

sessions without a lot of the downsides

[02:41]

and issues that things like claudebot or

[02:43]

or open claude have unfortunately

[02:45]

resulted in. Finally, we'll cover

[02:47]

scaling and deployment. Basically, how

[02:49]

to take your automations and run them in

[02:50]

production using modal web hooks, GitHub

[02:52]

actions, and cloud code on the web. So,

[02:54]

we've got quite a lot to cover. Let's

[02:56]

just dive right into it with the first,

[02:58]

which is how to set up cloud code as a

[03:00]

total beginner. So, the first thing we

[03:01]

have to do is we actually have to

[03:02]

purchase cloud code. And the reason why

[03:04]

is because they don't offer it for their

[03:06]

free plan at $0. In order to have access

[03:08]

to Cloud Code, you need at least their

[03:10]

pro plan for everyday productivity. I'd

[03:13]

recommend this if you guys are starting

[03:14]

out. The money that you spend on a

[03:16]

subscription like this is

[03:19]

so small compared to the massive

[03:21]

productivity benefits that despite the

[03:23]

fact that it's $17, I personally would

[03:25]

not even raise an eyebrow. It's no small

[03:27]

stretch to say that Cloud Code probably

[03:29]

delivers me productivity benefits on the

[03:31]

order of $10 to $15,000 a month because

[03:34]

it's not only just skilled as a

[03:36]

developer might be, which allows me to

[03:38]

build systems that alleviate stresses

[03:39]

and strain in my life, but it's much

[03:41]

more than a developer as well. It's

[03:43]

basically my second brain at this point.

[03:44]

After you click try Claude, it'll take

[03:46]

you to a page where you have to log in.

[03:48]

And once you're done, you can then

[03:49]

create your account for the very first

[03:51]

time. So, I'd select both of these. I'm

[03:53]

not going to subscribe to occasional

[03:54]

product updates because my email inbox

[03:56]

is busy enough. And then you have an

[03:58]

onboarding screen with some personal

[03:59]

information. So, I'm just going to fill

[04:01]

that out and then once I'm done, circle

[04:02]

back. Okay. So, I'm Canadian and

[04:04]

unfortunately our dollars convert quite

[04:06]

poorly to freedom dollars. So, the $17

[04:09]

that we saw earlier is $28 in my own

[04:11]

currency. I'm going to click get pro

[04:13]

plan and then walk through the payment

[04:15]

details below. Cool. And now I have a

[04:17]

Cloud subscription. This is all that you

[04:19]

need in order to get set up. Everything

[04:20]

else is totally free from here on out.

[04:22]

The simplest way to get up and running

[04:23]

with Cloud Code is just opening up a

[04:25]

terminal instance. That'll seem pretty

[04:27]

intimidating to a lot of you. So, I'm

[04:28]

not just going to show you how to do it

[04:29]

in the terminal. I'm also going to show

[04:31]

you how to do it using what's called

[04:32]

their graphical user interface, which

[04:34]

they put together four or five months

[04:35]

ago. Any resource that I show you

[04:37]

throughout this course is probably going

[04:39]

to look a little different by the time

[04:40]

that you look at it versus when I'm

[04:42]

looking at it. And that's because cloud

[04:44]

code, anthropic, and just AI tools in

[04:46]

general change really quickly,

[04:47]

especially since most of the developers

[04:49]

are also using cloud code. So it kind of

[04:51]

multiplies the productivity here. What's

[04:53]

important is not the specific layout,

[04:55]

the colors, the the the words on the

[04:57]

screen. What's more important is that

[04:58]

you just know how to find it. And so the

[05:00]

number one resource that I personally

[05:02]

use to look up advanced cla features is

[05:05]

in the cloud code documentation. It's at

[05:07]

code.cloud.com/doccks.

[05:10]

Whatever language you speak, just pump

[05:11]

in there and then it'll automatically

[05:13]

translate that over to. So the cloud

[05:15]

code docs specify that in order to

[05:17]

install cloud code in your system for

[05:18]

the first time, you can run what's

[05:20]

called a curl command here. If you're

[05:22]

running Windows PowerShell, you know,

[05:24]

you can run this Windows cmd, you can

[05:26]

run that. Just so we're all on the same

[05:28]

page here, when you have little snippets

[05:29]

of text like this, what they're telling

[05:31]

you to do is basically to open up a

[05:33]

terminal or a command prompt. So on Mac

[05:36]

OS, Linux, or WSL, which are all

[05:38]

different operating systems, in order to

[05:40]

open up a terminal, you just type

[05:41]

terminal. When you do so, you then get a

[05:44]

terminal. Now, this terminal might look

[05:46]

a little intimidating to you if it's

[05:47]

your first time ever using something

[05:48]

like that. But don't worry about it too

[05:50]

much. I just wanted to show you guys how

[05:51]

easy it is to get set up with cloud code

[05:53]

in this. And then afterwards, as

[05:54]

mentioned, we'll we'll do the graphical

[05:55]

user interface stuff. Okay. So, this is

[05:57]

what it looks like on Mac. If you guys

[05:58]

are on a Windows, then um you'll have to

[06:00]

use the Windows key search bar. Then

[06:02]

it'll look up something like cmd or

[06:04]

command prompt. At the end of it, you'll

[06:06]

get something that looks pretty similar

[06:07]

to this. From here on out, all we have

[06:08]

to do is we have to copy over the

[06:10]

command that it gives us. So, because we

[06:12]

want a native install and I'm in Mac OS,

[06:14]

I'm just going to copy over this

[06:15]

command. You can also click this little

[06:17]

button over here and then alt tab back.

[06:19]

I'm then going to paste it in and press

[06:20]

enter. From here on out, a bunch of

[06:21]

complicated things are going to occur.

[06:23]

If you don't already have it installed,

[06:25]

may take you a little bit longer, but

[06:27]

now we're good to go. Claude Code is

[06:29]

installed on our computer. Once you're

[06:30]

done with all that, all you have to do

[06:31]

in order to use Claude is just type the

[06:33]

word Claude directly into your terminal.

[06:35]

It's really that easy. Now, if it's the

[06:37]

very first time that you're logging in,

[06:39]

you'll also have to authenticate, and

[06:40]

it'll ask you to do so automatically

[06:42]

when you open this stuff up. If not, you

[06:44]

can also type back slashl

[06:47]

i n. Once you've clicked this, it'll

[06:49]

tell you cloud code can be used with

[06:51]

your cloud subscription or build based

[06:53]

on API usage through your console

[06:55]

account. How would you like to set up?

[06:57]

Now, in our case, we're using the

[06:59]

cheapest, most effective method, which

[07:00]

is the Pro, Max, Teamer, or Enterprise

[07:02]

subscription. It's also the most

[07:04]

straightforward, which is why it's the

[07:05]

one that I used in this course. I'm just

[07:07]

going to click enter, and then it'll

[07:09]

then log you into your Claude account,

[07:12]

the one that you just set up a moment

[07:13]

ago. Once we're done, you're all set up

[07:15]

for Claude Code, you can close this

[07:16]

window, then alt tab back, and you'll

[07:18]

see that it's going to say just press

[07:20]

enter to continue. Now, just so we're

[07:22]

all on the same page here, all we've

[07:23]

really done so far is we've just opened

[07:25]

up a chat interface with an AI model.

[07:27]

It's just instead of it being in like a

[07:29]

nice desktop application or on the web,

[07:31]

it's in our terminal. And the value here

[07:33]

is instead of running an AI model on the

[07:35]

web or in some distant cloud server,

[07:37]

what we're doing now is we're running it

[07:38]

locally on our computer. So we actually

[07:40]

have the ability to take this model and

[07:43]

then locally modify files on our

[07:46]

computer, write scripts, write stories,

[07:48]

write poems, restructure our file

[07:51]

organizer, clean up our our PC or our

[07:54]

Mac. Like this thing is currently

[07:55]

connected to my computer. And I'll run

[07:57]

you guys through how permissions and all

[07:58]

that stuff work later on in the course

[08:00]

as I talked about in the outline. But

[08:02]

even this alone makes it extraordinarily

[08:05]

powerful. So this screen can look pretty

[08:07]

intimidating for beginners. Most people

[08:09]

end up using the terminal um flow, not

[08:11]

the GUI flow, but I'm going to explain

[08:12]

to you what you guys see here just for

[08:14]

simplicity. In the top lefthand corner,

[08:16]

you have that cute little claude code

[08:18]

widget. I think it's I don't know if it

[08:19]

was supposed to be a crab or like a

[08:20]

jellyfish, but it's adorable. Then you

[08:22]

have claude code and the actual version

[08:23]

up above. Underneath you have the model

[08:26]

that you're currently using. In my case,

[08:27]

I'm using Opus 4.6. Then you have the

[08:29]

plan that you're on. In my case, Claude

[08:30]

Mac. So this is a couple levels up from

[08:32]

the pro plan. And then perhaps most

[08:34]

importantly, you have the current

[08:35]

working directory. As I mentioned to you

[08:37]

a moment ago, this is working inside of

[08:39]

your computer in a specific folder. And

[08:41]

so Cloud Code currently lives inside /

[08:44]

users/nixar,

[08:46]

which is basically like the the home

[08:47]

folder, at least on my Mac OS. Here is

[08:50]

your previous command. And so I just

[08:52]

wrote clear because I wanted to clear it

[08:54]

all the way up and give you guys a fresh

[08:56]

canvas. Here is where you actually

[08:58]

insert the text. So when you type stuff,

[09:01]

it pops up. Underneath here, it tells

[09:03]

you the model again. Then it gives you

[09:05]

various modes. So in my mode right now,

[09:07]

I'm in bypass permissions. This is sort

[09:09]

of like a dangerous mode. It's a mode

[09:10]

that not a lot of people feel super

[09:11]

comfortable with, but it's the mode that

[09:13]

I prefer for uh knowledge work and

[09:14]

intellectually valuable tasks. And I'll

[09:16]

run you guys uh through more of that

[09:18]

later on. But you can cycle through

[09:20]

modes simply by clicking shift and tab,

[09:22]

which I'll show you guys how to do. And

[09:24]

then there's some additional information

[09:25]

here. There's a version, the latest, and

[09:27]

then over here is at least in my case,

[09:28]

the the token readout. And you know

[09:30]

what's really cool? You can actually

[09:32]

adjust this. This sort of thing is your

[09:33]

your claude code status line, which I'm

[09:35]

also going to run you through it. You

[09:36]

can make it all colorful and all wonky

[09:38]

and really fun. You can have it display

[09:40]

whatever the heck you want. So the very

[09:41]

first thing I'm going to do is I'm just

[09:42]

going to say, "Hey, how's it going?" And

[09:45]

immediately after, I'm going to take a

[09:46]

screenshot so I could show you guys some

[09:48]

more information. So, opening this up in

[09:49]

my drawing tool. What ended up happening

[09:52]

is immediately after we said, "Hey,

[09:53]

how's it going?" You see that another

[09:55]

prompt showed up called finagling. This

[09:57]

is one of like a thousand different

[09:59]

words that Claude Code uses. Basically,

[10:01]

anytime it's thinking, it's going to use

[10:02]

some funny term like finagling or

[10:05]

processing or uh I don't know, rumpeting

[10:08]

or considering or what whatever the

[10:10]

heck. They're pretty funny. And the cool

[10:12]

thing is you can customize that. Next,

[10:13]

you have the number of seconds that your

[10:15]

your query has lasted. So, I just said,

[10:17]

"Hey, how's it going?" And then 2

[10:18]

seconds in, it's now produced five

[10:20]

tokens for me. And then finally, you

[10:22]

also have the the token count. So, just

[10:24]

so we're all on the same page, a token

[10:25]

is not the same as a word, but at least

[10:27]

for the purposes of most of what you do,

[10:29]

you can consider a token to be similar

[10:30]

to a word. For instance, I said, "Hey,

[10:32]

how's it going?" Um, this is not 1 2 3

[10:35]

four. This isn't four tokens. It might

[10:37]

be four words. It's probably closer to

[10:39]

six or seven tokens, but just think

[10:40]

about tokens as being analogous towards

[10:42]

just a few more if that makes sense.

[10:44]

You'll also see that an additional piece

[10:45]

of information popped up down here

[10:47]

called context. And this is really

[10:48]

important. Um context goes from 0 to

[10:51]

100% and that's how much basically um

[10:53]

conversation history you have in the

[10:55]

current chat window with your current

[10:57]

instance of cloud code. This becomes

[10:59]

really important later when you're

[11:00]

designing uh better context management

[11:02]

techniques which is a big portion of

[11:04]

what this course is going to be all

[11:05]

about because at least as of the time of

[11:07]

this recording context management is

[11:09]

sort of like the the big bottleneck in

[11:10]

getting these systems to do more and

[11:12]

better for you. You'll also notice that

[11:14]

on the right hand side my token counter

[11:16]

uh my status line here it it went up

[11:18]

significantly. And so basically what

[11:20]

this means is at about 20,000 tokens or

[11:22]

so, we're about 10% of the way through

[11:25]

um our entire conversation thread that's

[11:28]

allotted to us. What's really cool is

[11:29]

Claude Code will take all of that

[11:31]

history and at regular intervals, it'll

[11:33]

actually compress that for you by

[11:35]

increasing the information density,

[11:36]

taking a string of text and then making

[11:38]

it higher information density and higher

[11:40]

information density and higher

[11:41]

information density successively. So

[11:43]

that even if you wrote something in kind

[11:44]

of like a you know a bloated way, a way

[11:46]

that you know you could have used fewer

[11:48]

words to say um as your context goes up

[11:51]

and longer um cloud will automatically

[11:53]

manage that for you to ensure that

[11:54]

you're within the window. So that's how

[11:55]

to set up cloud code in the terminal.

[11:57]

Hopefully we're all on the same page.

[11:58]

Terminals are really similar to

[12:00]

graphical user interfaces which I'm

[12:01]

about to show you in a moment. I do

[12:03]

recommend that you guys get used to

[12:04]

using it in terminal because when you

[12:05]

use it in terminal you basically unlock

[12:07]

even more functionality. You can run a

[12:09]

bunch of these side by side. You could

[12:11]

run different terminal tools and whatnot

[12:13]

that give you guys faster refresh times

[12:14]

and we'll cover that sort of stuff

[12:16]

later. Um, but what I want to do now is

[12:17]

I want to show you guys how to run it in

[12:18]

a graphical user interface. And these

[12:20]

graphical user interfaces are typically

[12:22]

managed by what's called an integrated

[12:23]

development environment. Well, that

[12:24]

takes us to the next logical question

[12:26]

which is Nick, what is an integrated

[12:29]

development environment? An integrated

[12:31]

development environment also termed

[12:35]

is basically three things put together.

[12:37]

Okay, it's a file folder organizer plus

[12:42]

a

[12:44]

text editor

[12:47]

plus an AI chat widget similar to what

[12:53]

you get if you go on chatgpd.com or

[12:55]

cloud.ai. So, you know how on my Mac if

[12:58]

I go Finder um I open up a basically

[13:01]

series of folders where I can select

[13:03]

different files and open them up and so

[13:04]

on and so forth. You can do the same

[13:06]

thing on Windows if you just type in

[13:08]

folder or I don't know the C drive or

[13:10]

whatnot. Well, an ID is basically that

[13:12]

plus something like notepad or notes

[13:15]

plus something like chat GBT allin one.

[13:18]

[snorts] And right now we have two major

[13:21]

idees that the market is tending

[13:23]

towards. The first is called Visual

[13:25]

Studio Code and the second is called

[13:26]

anti-gravity. Visual Studio Code is sort

[13:30]

of like the OG one because anti-gravity

[13:32]

is actually built on it. Um, it was

[13:33]

developed a lot longer by Microsoft.

[13:35]

It's really, really extensible. It has

[13:37]

great support and it's very

[13:39]

straightforward. So, I'm going to show

[13:40]

you guys how to set things up on it, but

[13:42]

anti-gravity I would consider to

[13:44]

basically be Visual Studio 2.0. So, not

[13:47]

only does it have most of the same

[13:48]

features now, although it is uh some of

[13:50]

them are still kind of a little

[13:51]

beta-ish. Um, it's also a lot more

[13:53]

modern, and then there's a much bigger

[13:56]

focus on AI, which is obviously kind of

[13:58]

the whole point of this course. So, uh,

[14:00]

I'm going to be showing you guys

[14:01]

initially how to set things up in Visual

[14:02]

Studio Code. Then I'm going to do

[14:03]

anti-gravity, and then for the rest of

[14:05]

the course, we're just going to be doing

[14:06]

all of our work inside of anti-gravity.

[14:07]

And anti-gravity is really cool. There's

[14:09]

some additional functionality within

[14:10]

anti-gravity, not even tied to cloud

[14:11]

code. So, the first thing we need to do

[14:13]

is obviously we need to set up Visual

[14:14]

Studio Code. Um, in order to do that,

[14:16]

just head over to Visual Studio Code on

[14:18]

Google over here and then download for

[14:20]

whatever your specific application is.

[14:22]

In my case, I'm downloading the Mac OS.

[14:25]

I'm then going to have the download

[14:27]

appear in the top right hand corner. I'm

[14:29]

then going to give that a click and then

[14:31]

go download unverified file. And then

[14:33]

over here on a Mac, you again have to

[14:35]

drag the little window over. So, I'm

[14:37]

just going to do that. And once you're

[14:38]

done, you're going to have a page that

[14:39]

looks something like this. So, remember

[14:40]

earlier how I said it was like a file

[14:42]

editor? Well, that's what this little

[14:44]

lefth hand side is about. If I click

[14:45]

open a folder, I can actually go through

[14:47]

and I can open a folder on my computer.

[14:48]

So, why don't I just go and open uh I

[14:50]

don't know, leftclick contact. Okay.

[14:53]

Okay, so now I'm inside of the leftclick

[14:54]

contact folder and you can see we have

[14:56]

some files here, a git ignore, claw.nd,

[14:59]

contact, index, and a neti tl. We're

[15:02]

going to go through all that sort of

[15:03]

stuff in a moment. It's not super

[15:05]

important for now, but this is sort of

[15:06]

like where the um file explorer

[15:09]

functionality comes in. If I were to

[15:10]

click on one of these, as you can see,

[15:12]

we've now opened up a big text editor

[15:14]

right in the middle of the screen. And

[15:15]

so this is a bunch of CSS. It's a

[15:17]

programming language. What's really cool

[15:19]

is with cloud code, you don't actually

[15:20]

have to know how to read any of this

[15:21]

stuff. It'll just tell you everything.

[15:22]

And so that is the text editor

[15:24]

functionality. I can make changes. Hey,

[15:27]

what's up? You know, I could um create a

[15:29]

new file here if I wanted to called

[15:31]

message.md.

[15:33]

And I could say, hey, how's it going

[15:36]

YouTube? So just like in that way, we

[15:39]

basically have file editing

[15:40]

functionality and then we can also

[15:42]

select files to work on and stuff like

[15:43]

that. And then on the right hand side,

[15:45]

you have an agent tab, which is where

[15:47]

you have your chat interface with AI.

[15:49]

Now, right out of the gate, the VS Code

[15:51]

chat interface isn't actually Claude

[15:53]

Code. In order to access Cloud Code, you

[15:55]

have to download it as an extension. So,

[15:56]

I'm going to run you guys through that

[15:57]

right now. On the left hand side here,

[15:59]

click on these little blocks. Then, just

[16:01]

type Claude Code. You'll see a variety

[16:04]

of these. The one that you're looking

[16:05]

for is the one that's developed by

[16:06]

Anthropic, the one with that little

[16:08]

check mark in it. be very wary of

[16:10]

downloading extensions that are not from

[16:12]

official developers and vendors like

[16:14]

Anthropic simply because uh people have

[16:16]

been known to insert malware and and

[16:18]

different things like that in these.

[16:19]

It's very important that you're that you

[16:20]

preferentially use verified sources. In

[16:22]

my case, I've already installed this,

[16:24]

but all you have to do is go through

[16:25]

that little installation wizard here.

[16:26]

Then once you're done, you will have

[16:28]

access to cloud code. The question is,

[16:30]

okay, I have access to cloud code. How

[16:32]

do I actually use it? Well, it's really

[16:33]

easy. If you just go to the top right

[16:34]

hand corner of this little agent window,

[16:36]

you now can just click on cloud code.

[16:38]

But you'll also see that there's a

[16:40]

clawed logo up here as well. But what

[16:42]

the hell does this mean? If you click on

[16:43]

this, you'll open up just like another

[16:45]

window. And in my case, I open it up

[16:47]

with a terminal default. Uh, so it's

[16:49]

going to open up this in the terminal.

[16:50]

This can be pretty intimidating and kind

[16:52]

of annoying to be honest, juggling all

[16:53]

these things. Just going to zoom in so

[16:55]

it's easier for us to see. So my

[16:57]

recommendation is at least for

[16:58]

beginners, just stick to the one on the

[17:00]

right. That one's simpler. And as you

[17:01]

can see, it's a different user interface

[17:02]

than the terminal. Okay. So how exactly

[17:04]

do you use this? and what are all of the

[17:06]

different features and buttons and stuff

[17:08]

like that. Covering the interface,

[17:10]

obviously up top you have the past

[17:12]

conversations tab. And so as you build

[17:14]

up more conversation history, you'll

[17:16]

actually be able to jump back to any

[17:18]

prior conversation you've had with

[17:19]

Claude Code over here. You can do that

[17:21]

both locally and then on the web. Um I

[17:23]

don't have access to either of these yet

[17:24]

because I just set this up fresh for you

[17:26]

guys. Underneath that you have the

[17:28]

Claude Code logo. Underneath that you

[17:30]

have that cute little jellyfish or

[17:32]

lobster, whatever the heck it is.

[17:34]

Underneath you have your little chat

[17:36]

window. So here is where I can actually

[17:37]

talk to Claude. Hey Claude, what's up?

[17:42]

Once we open this, you'll see that

[17:44]

similarly to how we had before, we have

[17:46]

that little accomplishing fidgeting

[17:48]

whatever we have that little like

[17:49]

process uh text come up. After that, you

[17:52]

then have the response. The response

[17:54]

comes in in this little window. Although

[17:55]

you'll see it's different when it

[17:56]

accesses files and stuff like that.

[17:58]

Underneath at the very bottom lefthand

[18:00]

corner, you have the various permission

[18:02]

modes. Remember how earlier mine said uh

[18:04]

dangerously skip permissions? Well, you

[18:05]

can do the same thing here. If you just

[18:07]

click on this, you can cycle through all

[18:08]

of the different possible modes. And

[18:10]

you'll see that little window around the

[18:11]

chatbot also changes. So, uh in my case,

[18:14]

I'm asking before edits, which means

[18:16]

because this is running locally on my

[18:17]

computer before it makes any changes to

[18:19]

any local files. I'm going to say, hey,

[18:21]

just ask me to make sure. Now, this is

[18:24]

pretty safe and a lot of people,

[18:25]

especially coders and and you know,

[18:27]

developers that are a little more old

[18:28]

school, will usually work like this. But

[18:30]

personally, given that when Claude's

[18:31]

really in the thick of things, it's

[18:33]

asking me for edits every five freaking

[18:34]

seconds. If you really want to unlock

[18:36]

that productivity, as I talked about

[18:37]

before, you either use edit

[18:39]

automatically or use bypass permissions.

[18:41]

And I'll cover plan mode and whatnot

[18:42]

later as well. To the right of that is,

[18:45]

and this is kind of intimidating for

[18:46]

some people to understand, but this is

[18:48]

the file that is currently being fed in

[18:51]

as context. So, for instance, do you see

[18:53]

how here it says index.html? And if I

[18:56]

click this, I get this little eye icon.

[18:58]

Well, if I leave this open, basically

[19:00]

Claude is currently looking at this

[19:02]

file. So, what file are you looking at

[19:05]

right now?

[19:07]

It'll now tell me that it's looking

[19:09]

through the index.html that's open in my

[19:11]

editor. It hasn't read through the

[19:13]

contents yet because reading through the

[19:14]

contents of this massive file would feed

[19:16]

a fair amount of uh tokens into context,

[19:18]

which would charge me a fair amount of

[19:19]

money. So, right now, it's not doing any

[19:21]

of that, but suffice to say, I can

[19:22]

actually edit this in real time. Yes.

[19:24]

Change the title to Nick's YouTube

[19:28]

example. And what it's going to do is

[19:30]

it's going to go through my file. It's

[19:32]

going to find the title, which is listed

[19:34]

right over here. Then it's going to

[19:36]

change that for me. This is an example

[19:38]

of a really simple, easy, and

[19:40]

straightforward change. But I could do

[19:41]

way more. I could refactor this whole

[19:43]

thing from light uh dark mode to light

[19:45]

mode. So, I'm actually going to ask it

[19:47]

to do so. Refactor this index html from

[19:50]

dark mode to light mode. And if you

[19:52]

don't know what this means, it's okay.

[19:54]

Bear with me. We're actually going to

[19:55]

rebuild a whole app using cloud code and

[19:57]

various design uh patterns in a moment.

[19:59]

The first thing it'll do is it'll try

[20:01]

planning out the changes that it's going

[20:03]

to make. And so it's doing a bunch of

[20:05]

programmatic adjacent things right now.

[20:07]

Like it's filtering out a bunch of um

[20:10]

you know different CSS snippets. It's

[20:12]

doing a fair amount of work here. And

[20:13]

you don't need to be a programmer to

[20:14]

understand what's going on. We basically

[20:16]

now given this a task. It's

[20:17]

deconstructing the task into a list of

[20:19]

highle steps. Then it's going to go

[20:20]

through and it's actually going to

[20:21]

present this plan to me uh for me to say

[20:24]

yes or no to. Now you'll notice that

[20:25]

when I did this in addition to the

[20:27]

interface changing and now the colors

[20:28]

being blue in the bottom right hand

[20:30]

corner we now have sort of a little

[20:32]

pause button. This pause button is

[20:34]

pretty important because it allows us to

[20:35]

actually stop a claud code execution in

[20:37]

process. So like while it's working. So

[20:39]

I could theoretically change this at any

[20:41]

point in time. Okay. And I could

[20:43]

actually pause it and then maybe I could

[20:44]

give it some more instructions or uh I

[20:46]

don't know tell it to do something

[20:48]

differently. So, I'm actually going to

[20:49]

click this little button. Then, I'm

[20:50]

going to go to bypass permissions. I'll

[20:52]

say no plan, just do it. And what I've

[20:55]

done is I've I've interrupted the

[20:56]

process in the tool call. And now it's

[20:58]

going to go through and instead of

[20:59]

having to do this big fat plan, I'm just

[21:01]

going to say it's the wild wild west,

[21:03]

buddy. Just get in there and start

[21:04]

making some changes. When I did this,

[21:05]

you'll notice that there's now a

[21:07]

thinking tab that's open. If you click

[21:08]

on this, you can actually peer into the

[21:10]

internal thoughts of Claude as it goes

[21:13]

through and accomplishes your request.

[21:16]

So in this case I said the user wants me

[21:18]

to just refactor the dark mode to light

[21:19]

mode without planning. Let me read the

[21:21]

whole file understand all the colors and

[21:23]

then make the changes. And as you see we

[21:25]

just had some changes made which is what

[21:26]

this little blue uh thing is here

[21:29]

showing that we've made you know the

[21:30]

changes. So immediately after thinking

[21:32]

it then did some more thinking. Then

[21:35]

down at the very bottom it's now updated

[21:36]

a bunch of the sections of my code and

[21:38]

it's continuing down some little to-do

[21:40]

list. So this is how you interact with

[21:42]

cloud code through the graphical user

[21:44]

interface. And there are a couple of

[21:45]

additional things like you can click on

[21:47]

this button to attach files and folders

[21:48]

and use the browser. You can also check

[21:50]

all of the commands here which are

[21:52]

pretty powerful stuff and I'll cover

[21:54]

them all in due time. So that's claude

[21:55]

code in Visual Studio Code VS Code.

[21:58]

Let's now cover how it looks in

[21:59]

anti-gravity. How to set that up and

[22:01]

then immediately after we're going to

[22:02]

build an actual real web app using

[22:04]

Claude Code. As expected, anti-gravity

[22:06]

is pretty similar. They have a website

[22:07]

here called anti-gravity.google. It's

[22:09]

very sexy and clean. Wouldn't be

[22:11]

surprised they built this with agents.

[22:13]

You just click download for whatever

[22:14]

your specific um you know operating

[22:16]

system is. In my case, Mac OS with Apple

[22:18]

silicon. Going to give that a click.

[22:19]

Then it'll go through that same process

[22:20]

that we just did for VS Code. Once you

[22:22]

open up anti-gravity, it looks very

[22:25]

similar to what we just saw a moment ago

[22:26]

with VS Code. And that's because the two

[22:28]

were sort of built on each other. So,

[22:30]

just like VS Code was both a file

[22:32]

explorer, a file editor, a notepad, and

[22:35]

an agent manager, you can see here we

[22:37]

have those three same ideas. On the left

[22:39]

hand side, we're going to have the

[22:40]

folders. On the middle, we're going to

[22:41]

be able to edit the uh text of the files

[22:43]

that we uh uh work with. And then on the

[22:45]

right hand side, we can actually talk to

[22:46]

agents. First thing I'm going to do is

[22:47]

I'll click open folder and we'll go back

[22:49]

to I don't know, leftclick contact just

[22:51]

so you guys could see what we're dealing

[22:52]

with. And you'll you'll understand here

[22:54]

that the UX is just slightly different

[22:56]

than what we had earlier. Um you know,

[22:57]

some things are indented. We have like

[22:59]

some little cool symbols in the lefth

[23:00]

hand sides of the file. This isn't super

[23:02]

important, but I just think anti-gravity

[23:04]

looks cleaner, which is why I like using

[23:05]

it. In the middle here, if I click this

[23:07]

index.html, HTML. You'll see that we

[23:09]

also have the text pop up just like we

[23:10]

did earlier. And the only real

[23:12]

difference between um anti-gravity and

[23:14]

VS Code. It's just what we have in this

[23:15]

right hand side. Earlier we we could

[23:17]

have used Claude Code really easily

[23:18]

because there was an actual dedicated

[23:20]

Cloud Code button. Right now there

[23:21]

isn't. In order to access Cloud Code,

[23:23]

assuming that you've installed it, so

[23:25]

head over here, Claude Code for VS Code.

[23:27]

Give that installation button a click.

[23:29]

Assuming that we've installed it, what

[23:30]

we have to do instead is we have to

[23:31]

double click somewhere here and then

[23:33]

click on this little claude icon. Okay?

[23:35]

and then just delete the agent icon. And

[23:37]

now you have the same layout that we had

[23:39]

earlier in VS Code. Just now you have it

[23:40]

with uh with cloud code. The reason why

[23:42]

is just because anti-gravity is a Google

[23:44]

product. So they try and push uh the

[23:46]

Google Gemini series of models. That's

[23:47]

what we had on the right hand side

[23:48]

earlier. And to be clear, this is a

[23:50]

cloud code specific course. Um but you

[23:52]

can also use whatever model you want to

[23:53]

do whatever purpose. Like the model type

[23:55]

is less important than just the fact

[23:56]

that you're really good at using it and

[23:58]

the fact that it's smart. So exact same

[24:00]

layout here. Not going to cover it

[24:01]

anymore. Let's get into actually

[24:02]

building some stuff. So, let's now build

[24:04]

our very first app/web page with claude

[24:09]

code. For simplicity sake, I'm starting

[24:12]

with probably the most straightforward

[24:14]

build, which is just going to be a web

[24:16]

page. And we're not just going to do the

[24:18]

hero header, which is the top or above

[24:20]

the fold section. We're going to do the

[24:21]

the whole website. And the reason why

[24:23]

I'm starting with this is because I just

[24:25]

want everybody to understand how good

[24:27]

Claude Code and similar tools have

[24:29]

gotten at being able to design

[24:30]

highquality websites. This is a site up

[24:33]

here called godly.ebsite. And what it

[24:35]

does is it basically just showcases

[24:37]

really highquality design. And every

[24:40]

single one of these, with maybe just a

[24:42]

couple of exceptions, is now doable in

[24:45]

probably I want to say less than 10

[24:48]

minutes or so front to back using cloud

[24:51]

code. This isn't me just, you know,

[24:53]

pretending. This is something that I

[24:55]

have done myself dozens of times. I've

[24:57]

built really high quality websites. The

[24:58]

other day I built like 15 or so for a

[25:00]

project. um they all look just like

[25:02]

this. So, award-winning design,

[25:04]

award-winning app functionality and

[25:06]

stuff like that. These are just a few of

[25:08]

the things that you guys are going to

[25:09]

learn today. In addition, you're also

[25:11]

going to learn how claude.md, which is

[25:14]

the system brain file, affects your

[25:17]

prompts. I'm going to run you guys

[25:19]

through the three major ways that people

[25:20]

currently design sites and the various

[25:22]

ways that you guys could use um these

[25:24]

approaches to both design websites,

[25:26]

apps, and more or less anything else you

[25:27]

want. Then, I'm also going to talk a

[25:29]

little bit about deploying

[25:31]

So let's start with cloud.md.

[25:34]

I have open in anti-gravity here. Um the

[25:37]

same workspace that we were looking at

[25:38]

before with just a couple of changes.

[25:40]

Namely, there's this node modules folder

[25:43]

here, which you guys don't have to pay

[25:44]

attention to. Um this is automatically

[25:46]

generated by cloud code every time we

[25:48]

use a library or use some sort of um npm

[25:50]

package. And then underneath we have

[25:53]

claw.md. Now claw.md as mentioned is the

[25:56]

brain of your workspace.

[26:00]

To make it really really simple and

[26:02]

straightforward for you because I think

[26:03]

a lot of people misunderstand how cloud

[26:04]

identities work. Let's just look at a

[26:06]

hypothetical conversation

[26:08]

over here. Let's say you are on the

[26:12]

right hand side. And so what you do,

[26:14]

okay,

[26:16]

is you say, "Hey, research X for me.

[26:20]

Research, I don't know, the best

[26:22]

trending posts on Twitter in my niche,

[26:24]

whatever the heck, right?" And then what

[26:26]

ends up happening is the model

[26:28]

afterwards claude whatever you're using

[26:30]

whether it's opus 4.6 six or 4.5 or

[26:33]

sonnet or haiku, it'll respond to you in

[26:35]

purple saying sure at one moment after

[26:37]

it returns whatever you want then you

[26:40]

know you continue in this vein and so

[26:42]

what I'm trying to get at is there's a

[26:44]

pattern here right there's user and then

[26:46]

there's model and then there's user and

[26:48]

then there's model

[26:51]

the way that the claw.md prompt works is

[26:54]

basically at the very first message

[26:57]

before you even get to that point what's

[26:59]

hidden from you is the fact that there's

[27:01]

actually another prompt. Okay, this

[27:04]

prompt is injected at the very top of

[27:07]

your conversation string before you even

[27:09]

send the first message. And so this

[27:12]

cloudmd being sort of the very first

[27:14]

thing that the model reads and sort of

[27:16]

internalizes is really really important

[27:19]

to help steer the output of the ship.

[27:22]

Now what is steering the output of the

[27:23]

ship? Well, I often use an analogy here.

[27:26]

Let's say you're somewhere on the east

[27:28]

coast of uh you know, North America and

[27:31]

you're trying to go to I don't know,

[27:33]

let's say the westmost coast of Africa

[27:35]

or something like that. As you guys

[27:37]

know, these intervening distances are

[27:38]

are really huge. These are I don't

[27:40]

actually know how long it is, but

[27:42]

probably at least 10,000 km or so. Now,

[27:45]

if you're a ship positioned right over

[27:47]

here, okay, and this is your port and

[27:49]

your goal port is over here.

[27:53]

Let's hypothetically say you have

[27:54]

limited ability to steer the ship. For

[27:56]

whatever reason, the steering wheel or

[27:58]

whatever the ship equivalent is, it just

[27:59]

doesn't really turn that much. What that

[28:01]

means is if you wanted to make it as

[28:03]

close as humanly possible to that X,

[28:05]

what you would have to do logically is

[28:07]

you'd have to make sure you're very very

[28:11]

accurate at least when you leave the the

[28:13]

port. And the reason why is because if

[28:15]

you're not, okay, if you give even a

[28:17]

very slight range of possible, I want to

[28:21]

say angles that you could go, okay, it

[28:24]

may not seem like that big of a

[28:25]

difference if you go, you know, from

[28:27]

this line um to this line, at least

[28:29]

initially, right? But over an

[28:31]

intervening distance of tens of

[28:32]

thousands of kilometers, obviously this

[28:34]

goes, you know, a very very long way

[28:35]

away from what your what your goal is.

[28:37]

And so steerability in AI is basically

[28:41]

when you try and minimize

[28:45]

the number of potential or the width of

[28:47]

all of the potential options. And so

[28:50]

what clawmd does is it allows you to

[28:52]

take this space of like, you know, a

[28:54]

really wide angle of ways that the AI

[28:56]

could go. Okay? And it's like I don't

[28:58]

even know where the hell we're going to

[28:59]

go if we take that topmost path and then

[29:01]

compress it down into a much more likely

[29:05]

subset of possible options that the AI

[29:08]

could go such that you know if you were

[29:11]

to be even slightly off here the impact

[29:13]

on your final destination while you know

[29:15]

you wouldn't make it to your goal you

[29:17]

still make it pretty close. So I want

[29:19]

you to treat your cloud.MD MD is

[29:20]

basically that initial trajectory that

[29:23]

you launch um all of your cloud sessions

[29:27]

um whether in terminal or whether in the

[29:28]

GUI tool like I'm showing up here. So

[29:31]

with that understood now that we're on

[29:33]

the same page about how cloudmd is

[29:35]

injected at the very front of any

[29:36]

conversation you start to realize that

[29:39]

there's a tremendous amount of value in

[29:41]

making that cloudmd as high quality as

[29:43]

possible. Okay. So including a file

[29:46]

capital C cl a Ude.m MD in any workspace

[29:50]

project directory means that this is now

[29:52]

injected at the front of our

[29:54]

conversation. And so you don't talk to

[29:57]

this any differently than you would

[29:58]

claude itself. This is just a file that

[30:00]

standardizes it and makes it really easy

[30:02]

to build in like conventions for

[30:04]

different workspaces. In such a file,

[30:07]

you're going to want to be very concise

[30:09]

and you're also going to want to give it

[30:10]

sort of the bounds of what this

[30:12]

workspace is for. I could just as well

[30:14]

actually copy this whole thing over,

[30:16]

okay, and then paste this directly into

[30:18]

my cloud code and then just get rid of

[30:20]

my cloud MD entirely. But the value in

[30:22]

having a cloud MD is I just don't have

[30:24]

to do that every time. It's initialized

[30:26]

very top of that conversation history

[30:28]

like we just saw. And so what's in here

[30:31]

to be honest is not super important. I

[30:33]

actually had another version of Claude

[30:35]

just develop this based off some um

[30:37]

Twitter posts that I saw that talked all

[30:39]

about how to build websites with best

[30:40]

practices. And you guys have access to

[30:42]

all this stuff down below. I obviously

[30:44]

have that template folder um that you

[30:45]

guys could use to to get this and

[30:47]

anything else. But suffice to say um

[30:50]

this is how or one of the ways rather

[30:52]

that you can currently design websites

[30:53]

using claude code. So the three major

[30:57]

ways that people are currently using

[30:58]

claude code and other agents to do

[31:00]

designs are as follows. The first is

[31:03]

that you give it a pre-existing design

[31:05]

and then you give it the ability to

[31:06]

screenshot itself over and over and over

[31:08]

and over again. And basically what

[31:10]

happens is the first variant that they

[31:13]

create that cloud code creates will be

[31:15]

like an 80% match. Then it'll screenshot

[31:17]

that compare it directly to the source

[31:20]

image and then um list all the

[31:22]

differences and then get 90% of the way

[31:24]

there. And then it'll get 95% of the way

[31:26]

there. And it usually can't get 100% of

[31:28]

the way there, but it can get like 99%

[31:30]

of the way. The value in this sort of

[31:32]

approach is what we're doing is we're

[31:33]

basically taking an inspiration website.

[31:36]

And so in our case, we're going to be

[31:37]

using it on this site here. Um, and then

[31:39]

we're using that to template out a bunch

[31:41]

of like design fundamentals. So like the

[31:43]

size of the text, the colors, the the

[31:44]

way the buttons look and stuff. And then

[31:46]

what you do is you just change the

[31:48]

content of the site with cloud so that

[31:50]

it's like whatever site you want it to

[31:51]

make. So in my case, you know, I run

[31:52]

this business called Leftclick. This is

[31:54]

my a automation agency. Um, you know, we

[31:56]

help people install growth systems into

[31:59]

their businesses, typically B2B

[32:00]

agencies. So what I would do is I would

[32:02]

basically try and rebuild this site

[32:03]

using this design. And you know, I can

[32:06]

make some minor changes afterwards, but

[32:07]

so long as I start with this nugget,

[32:09]

Claude tends to do a really good job

[32:10]

afterwards. The second way to build is

[32:13]

you basically just give it a massive

[32:14]

voice transcript dump. For those of you

[32:16]

that didn't know, there are now ways for

[32:18]

us to uh basically dump like a large

[32:21]

amount of text using a voice transcript

[32:22]

tool. I'll show you guys what that looks

[32:23]

like now, but if I just hold this Fn

[32:25]

key, this little widget appears at the

[32:27]

bottom of my screen. Now, this is

[32:28]

listening to everything that I say. And

[32:29]

because I can speak a lot faster than I

[32:31]

can type, I can actually say a fair

[32:33]

amount in a pretty short period of time.

[32:34]

Most people type it between 50 to maybe

[32:36]

70 words a minute, but we talk closer to

[32:38]

200 words a minute. That's a two and a

[32:40]

half to maybe 3x improvement. And

[32:42]

because these models are so intelligent

[32:43]

and smart and capable of extracting the

[32:45]

meaning from the text, you know, text is

[32:47]

all they look at all day long. Um, what

[32:49]

you could do is you could just use a

[32:51]

massive voice transcript dump to

[32:53]

basically spell out everything that you

[32:54]

want on the website. Um, this isn't

[32:56]

going to oneshot your website because we

[32:58]

don't have a pre-existing design, but

[32:59]

then you can just go back and forth with

[33:01]

it. And then in a fraction of the time

[33:02]

of developing a real website using a

[33:03]

voice transcript tool, you can get

[33:04]

pretty close. The third major way people

[33:07]

are currently designing is they use

[33:09]

components. Now for anyone here um

[33:11]

unsure of what components are, basically

[33:15]

there are now services and tools out

[33:17]

there like 21st.dev where designers have

[33:20]

created specific components on websites

[33:23]

and there are features on these where

[33:25]

you can actually click on it and then

[33:26]

click on this button up here, copy

[33:28]

prompt. Okay. And then it will take this

[33:31]

entire web page, entire design, you

[33:33]

know, this little animation flickering

[33:36]

thing, this jump on a call button, this

[33:37]

sign up here button, whatever. And then

[33:39]

it'll copy all the text needed to have

[33:41]

Claude code reproduce that for you. And

[33:44]

so it's really straightforward and

[33:45]

simple. You just make an account on one

[33:46]

of these services. And then let's say

[33:47]

you're building a website. You scroll

[33:49]

through and you're like, "Wow, I really

[33:50]

like this background paths component,

[33:52]

right? With these cool sweeping things.

[33:54]

I want that on my website." You would

[33:56]

just copy the prompt, paste it into

[33:57]

cloud code and say, "Hey, install this

[33:59]

thing somewhere up at the top because AI

[34:01]

is great at language. Uh, you know, you

[34:03]

can get pretty close." So, you can do

[34:04]

all sorts of things with this. You could

[34:06]

do like cool button borders as we see

[34:08]

here. You could have like a sign-in

[34:09]

component over here. You could have

[34:11]

multiple cards. You know, this stuff is

[34:13]

okay. To be honest, I find it much

[34:15]

easier just to go straight to u number

[34:17]

one, which is just giving it a design in

[34:19]

a screenshot loop and just having it

[34:20]

work off of something pre-existing. I

[34:22]

don't want you guys to think of this as

[34:23]

like you copying a design as you'll see

[34:25]

the end result will be quite different

[34:27]

from this but it's just a good way for

[34:28]

you to like get a rough idea of the end

[34:32]

design um and also not have to worry

[34:33]

about things like the sizes of fonts you

[34:35]

know the the colors and so on and so

[34:37]

forth. Okay, so we're basically going to

[34:39]

use this as like our inspiration and

[34:41]

then once we have our inspiration in

[34:42]

place um Claude's going to be able to

[34:43]

design whatever we want whether it's an

[34:45]

app or a dashboard or whatnot uh very

[34:47]

very quickly. The final thing that I

[34:48]

have to talk about before we actually do

[34:50]

the designing is the difference between

[34:51]

building something and then deploying.

[34:53]

So when you build something, you're

[34:55]

typically building it locally. When you

[34:57]

do a tool, an automation like we're

[34:59]

going to do later on in the course or an

[35:01]

app or a website, you know, we're we're

[35:03]

running this thing on our local

[35:04]

computer. But if we want other people to

[35:06]

be able to access it, then obviously we

[35:08]

need to deploy it. We need to push it

[35:09]

onto the internet and there variety of

[35:11]

different tools that allow you to do so.

[35:12]

So today I'm just going to show you how

[35:14]

to build the stuff and then over the

[35:16]

course the next few modules as we get

[35:17]

deeper and deeper into the course I'll

[35:19]

also talk a little bit about tools like

[35:20]

Netlefi Versel modal and whatnot that

[35:23]

allow you to pull to push both your

[35:25]

software uh the tools that you make and

[35:27]

then even things like websites and and

[35:29]

full-fledged apps to the cloud so that

[35:31]

other people can access it on a domain

[35:33]

like you know nicksaw awesometool.com.

[35:35]

Okay, so without further ado, how would

[35:36]

I actually go about this design process?

[35:38]

Well, as mentioned, I had this

[35:39]

claude.mmd file set up here. And this is

[35:41]

just something that I had Claude uh

[35:43]

basically scrape through Twitter to find

[35:45]

me the best practices of all of the

[35:47]

different types of website designs out

[35:48]

there that people are currently using

[35:49]

Claude and other tools to create. Uh,

[35:51]

and then I just had it like write me a

[35:52]

little a little script, basically a

[35:54]

little summary. And this is very

[35:56]

squarely this give it a design

[35:58]

screenshot loop. It's just written in

[35:59]

like a very particular way. You do not

[36:01]

need to know how the tools work. You

[36:02]

don't need to know how anything works.

[36:03]

You basically just need to know how to

[36:04]

like find a resource out there or use AI

[36:06]

to find a resource and then use it to

[36:07]

make your own claw.d D. With that in

[36:09]

mind, what I'm going to do now is I'm

[36:10]

actually just going to go on the website

[36:12]

that I want, I'm going to screenshot it.

[36:13]

However, if you guys aren't familiar,

[36:15]

um, you know, if I just screenshot like

[36:17]

one section of the site, like this for

[36:18]

instance, on Mac, then I feed it in, you

[36:21]

know, I don't actually have most of the

[36:22]

site, right? I only have that hero

[36:23]

header. Okay. In terms of how to

[36:25]

actually build this puppy, um, use

[36:27]

command shift I or right click on the

[36:30]

page and then type inspect. This will

[36:32]

open up a window that looks something

[36:34]

like this. Once you're done, change the

[36:36]

dimensions to full page width. On

[36:39]

desktop, that's usually 1920x 1080. This

[36:42]

is termed the widescreen aspect ratio.

[36:44]

Then just hold commandshiftp. I think

[36:47]

it's control shiftp on Windows. You'll

[36:49]

open up this little command bar. With

[36:50]

this command bar in place, you can then

[36:52]

just type in screenshot and then go

[36:53]

capture full size screenshot. It'll

[36:55]

actually scroll through the whole site

[36:57]

and take an entire screenshot for you.

[36:59]

If I click on this button now, as you

[37:00]

guys could see, we now have a screenshot

[37:02]

of the entire website top to bottom.

[37:04]

It's kind of a hack. Not a lot of people

[37:06]

realize that you can do this, but you

[37:07]

can. It's pretty neat. And once we have

[37:09]

this, we just have to do one more thing.

[37:10]

It's pretty big right now. If you were

[37:12]

to send cloud code, you know, like 20

[37:14]

megabytes or something like that of

[37:15]

file, um, number one, it would like

[37:17]

really massively eat up your token

[37:18]

limits. And then two, uh, I think the

[37:20]

API might have like a limit on this. So,

[37:22]

we just have to make this file

[37:23]

significantly smaller. So, I'm just

[37:24]

going to open up this resize PNG file

[37:27]

here. um page called resize PNG from i

[37:30]

loveimage.com. You can use whatever the

[37:31]

heck you want. Then I'm just going to

[37:33]

drag and drop this in. I don't know, 50%

[37:35]

smaller, even like 75% smaller. And then

[37:38]

click resize images. This is now going

[37:40]

to basically remap this for us. We can

[37:42]

click download. What we're looking for

[37:44]

is we're looking to get a file that's

[37:45]

less than about I want to say um I think

[37:49]

like four or five megabytes or so. So

[37:51]

it's not perfect. Okay, it's a little

[37:52]

bit blurry, but it's all right. Maybe

[37:54]

I'm just going to go back and resize

[37:56]

this one more time so that it's um I

[37:58]

don't know, maybe a little bit bigger.

[37:59]

Let's do 50% smaller instead of 75%.

[38:01]

Okay, once we're done, we can click

[38:02]

download resized images. This one is

[38:05]

about 4 megabytes or so. If we open it

[38:07]

up, you can see that it's still high

[38:09]

quality, but it's much much smaller than

[38:10]

the other file, which is like three or

[38:12]

four times. And now that we're done, we

[38:13]

just add this into cloud code. So, back

[38:15]

to our cloud code instance. I'm going to

[38:17]

go down here to bypass permissions.

[38:19]

Then, I just need to go find the file.

[38:20]

So, I'm going to click this top right

[38:22]

hand corner and I'm just going to see if

[38:23]

I can drag this in directly.

[38:26]

Okay, so it's going to open this up.

[38:27]

That's okay. Just zoom in, copy, and

[38:30]

then you can actually paste this in um

[38:32]

directly.

[38:34]

Okay, so just click that copy button,

[38:35]

paste it, and you actually have the

[38:36]

whole file as context. Okay, and then we

[38:38]

just have to do one more thing. We're

[38:40]

just going to head back to the website.

[38:41]

I'm going to find actual, and then

[38:44]

scroll down to this little body tag, and

[38:45]

then rightclick and press copy styles.

[38:48]

This is going to copy the styles of the

[38:50]

site, including the button colors and

[38:52]

sort of like the little gradients in the

[38:53]

background and and so on and so forth.

[38:55]

And paste that in. Okay. And then I'm

[38:58]

just going to press enter. Now that

[39:00]

we've uploaded these, keep in mind that

[39:02]

despite the fact that this might mean

[39:04]

nothing to you or I, um, keep in mind

[39:06]

that there's that extra prompt that's

[39:08]

been injected up at the top that

[39:10]

literally says when the user provides a

[39:11]

reference image, screenshot, and

[39:12]

optionally some CSS classes or style

[39:14]

notes, you should generate a website. So

[39:17]

that's what it's doing immediately. It's

[39:18]

analyzing the reference image and

[39:20]

building this website recreation. Let me

[39:22]

start by creating the actual HTML file.

[39:24]

So this will now walk through its own

[39:26]

little to-do list. Take screenshots of

[39:28]

its created website, compare it with

[39:30]

round one, basically do the same thing

[39:32]

over and over and over and over again

[39:33]

until it gets to where we want it to go.

[39:35]

And this is really what I'd consider to

[39:37]

be the core building philosophy

[39:40]

um for cloud code. What you do is you

[39:42]

basically give it a highle task which in

[39:44]

our case we did with the claw.mmd. Okay.

[39:47]

Then we allow it to do the task

[39:50]

and then we allow it to verify or

[39:53]

basically judge its results.

[39:57]

I think the reason why a lot of people

[39:58]

end up sucking at cloud code or maybe

[40:00]

they end up giving it instructions and

[40:02]

then not being satisfied with its

[40:03]

results is they'll just give it the task

[40:05]

and then it'll do the task and then

[40:08]

their loop is kind of like this, right?

[40:09]

task, do the task, give it another task,

[40:11]

do the task, so on and so on and so

[40:12]

forth. If you don't give cloud code the

[40:14]

ability to verify its own results either

[40:16]

visually through a screenshot tool or if

[40:18]

you're building some sort of software

[40:19]

through like um automated testing

[40:21]

mechanisms and and so on and so forth,

[40:22]

test driven development, then uh you

[40:25]

lose like the vast majority of the value

[40:26]

of AI. The reality is AI is not going to

[40:29]

be perfect the very first time, but the

[40:31]

value of AI is not in its ability to

[40:33]

oneshot everything 100%. the value of AI

[40:35]

is its speed because you can have it get

[40:38]

to 80%. Let's say this is like a I don't

[40:41]

know a little quality bar or something.

[40:45]

You know what you can do is you can

[40:46]

immediately, you know, it's not just

[40:48]

going to be like if this is time step 1

[40:50]

2 3. It's not just immediately going to

[40:51]

be at 100%, right? That's just that's

[40:53]

not what it does. It's not going to go

[40:55]

from here to here in like 2 seconds and

[40:57]

be done. What it is going to do though

[41:00]

is it's very quickly going to start

[41:03]

here. Then it'll go here. Then it'll go

[41:06]

here. It'll go here. And then eventually

[41:09]

after two or three or four time steps,

[41:11]

it'll it'll hit that 100%. And you know,

[41:13]

we think that this is a really long

[41:15]

period of time. Okay?

[41:17]

But in reality, this is like 5 minutes.

[41:19]

And if you contrast this with how long

[41:21]

it would take a human to do that same,

[41:23]

you know, approach, you know, humans

[41:24]

will probably get closer to 100% quality

[41:27]

on their very first go, but it's not

[41:28]

going to be like a minute or two. What

[41:30]

this is going to be is it's going to be

[41:31]

like, um, I don't know, 5 hours. You

[41:34]

know, we actually, believe it or not,

[41:35]

tend to be a lot more precise in these

[41:36]

machines that we've built. Um, we can

[41:38]

oneshot things to a much greater degree

[41:39]

than they can, but their ability to test

[41:42]

and then retest and work really, really

[41:43]

quickly, orders of magnitude times

[41:44]

faster than we do, is the real value.

[41:46]

And that's something that I don't think

[41:47]

enough people talk about. So, just make

[41:49]

sure there's always a task, do the task,

[41:50]

and then verify the results loop

[41:52]

somewhere in here, and you'll be fine.

[41:53]

Now, heading back to our um cloud code

[41:55]

instance, you can see it's now actually

[41:58]

completed the first round of its HTML.

[42:00]

Now, it's um screenshotted it as well.

[42:02]

And then it's basically comparing the

[42:04]

screenshot to the work that it's

[42:06]

generated. And with this, it's going to

[42:09]

make minor changes. So, as you see, the

[42:10]

very first thing it's done is it's

[42:12]

replicated the get paid the same day by

[42:14]

setting a payment link or the most

[42:15]

flexible invoice on the planet with the

[42:16]

buttons and so on and so forth. Okay?

[42:18]

It's also replicated that top section.

[42:20]

And it's used little placeholders here

[42:23]

with these 160* 100 little buttons even

[42:26]

with like the right tilts and whatnot

[42:27]

because it doesn't have access to the

[42:29]

images. It then is uh you know entering

[42:32]

these little divs, right? It's even got

[42:34]

this cool little post-it note which is

[42:35]

really cool. And then it even has the

[42:36]

reviews. And so as sort of like

[42:38]

rebuilding the design of this website,

[42:40]

it's doing a really good job and we're

[42:41]

only a couple minutes in. What's cool

[42:42]

too is if you check out the thinking

[42:43]

tab, you can see that it's gone through

[42:46]

iteratively every section of the site.

[42:48]

Okay. And it's um you know listing what

[42:50]

it needs to do next. So better

[42:51]

decorative elements in hero, better

[42:53]

floating band, fixing the blue dot

[42:55]

positioning, improving the invoice cards

[42:56]

with map thumbnails. I don't know what

[42:58]

half of the stuff means, but to be

[42:59]

honest, for me, it's not super

[43:00]

important. Now, just because I want it

[43:01]

to be a little bit special and then show

[43:03]

you the parallel capacity of Cloud Code,

[43:05]

what I've done here is I've actually

[43:06]

opened up another anti-gravity instance.

[43:09]

And what I'm going to show you guys how

[43:10]

to do is actually design multiple of

[43:12]

these simultaneously. Once we've built

[43:14]

this test uh this do test and then

[43:16]

verify loop over and over and over

[43:18]

again, which we already have in our

[43:19]

cloudmd, it's actually really easy to

[43:21]

spin up multiple prompts and just have

[43:22]

like 10 versions of cloud working on

[43:24]

things simultaneously. So, just for

[43:27]

shits and giggles, why don't we head

[43:28]

back over to our little website

[43:30]

designer. It's then giving me a file

[43:31]

here called Twgate. Okay. And then I'm

[43:33]

pasting it all in. And now my computer's

[43:35]

really humming. Like, uh, you guys

[43:37]

probably can't hear this cuz I like to

[43:38]

noise cancel most things, but it's

[43:40]

making some noise. And the reason why is

[43:42]

because I now have two of these

[43:43]

instances running simultaneously, both

[43:45]

developing me a website. On the left

[43:47]

hand side of things, just expand this.

[43:49]

Um, we see that it's taken multiple

[43:51]

screenshots. There's screenshot one,

[43:53]

screenshot two, screenshot three. You

[43:55]

guys see how it's getting closer and

[43:56]

closer and closer to the end result?

[43:58]

Well, now it's doing some final editing.

[44:00]

It's making some feature thumbnails

[44:02]

better. On the right hand side, it's now

[44:03]

going through the initial development of

[44:05]

that new index.html. And so, because you

[44:07]

can run as many cloud instances as you

[44:09]

have tokens, basically, um, I can run as

[44:11]

many of these website designers

[44:13]

simultaneously in however many tabs I

[44:15]

want. And this isn't even the most

[44:16]

efficient way to do this. I'm going to

[44:17]

show you guys a much more effective

[44:19]

terminal management structure that'll

[44:21]

allow you to do like five or 10 or 20 of

[44:23]

these simultaneously. Okay. Okay, on the

[44:24]

left hand side, it's now saying it's

[44:25]

done. So, I'm going to say open

[44:26]

index.html. That's always just going to

[44:28]

be the actual website file. And if you

[44:30]

just tell it to open, it's going to go

[44:31]

through and do so in a tab for you.

[44:33]

Okay. And here is the demo of the

[44:35]

website that we put together. So, I

[44:37]

mean, it's not perfect. It's not

[44:38]

everything that I want, but it's good

[44:39]

enough for us to start. So, what I'll do

[44:40]

now is I'll go back and I'll have it

[44:42]

recreate. Leftclick.

[44:44]

Hey, this is looking pretty solid so

[44:45]

far. I'd like you to um check out

[44:48]

leftclick.ai.

[44:49]

That's my personal website. And what I

[44:51]

want you to do is to design uh or take

[44:55]

the information from leftclick.ai and

[44:56]

then insert it into this website. I

[44:58]

don't want this to be a clone of

[44:59]

leftclick.ai, but I want it to be pretty

[45:01]

close. Use the formatting and everything

[45:03]

that you've developed so far to help

[45:05]

place elements and stuff like that as

[45:06]

necessary. Um insert images as well and

[45:09]

make sure that any elements that um are

[45:11]

there look good. Continue doing a

[45:13]

screenshot loop if necessary until you

[45:15]

have something that looks very high-end,

[45:16]

very professional and and minimalistic

[45:18]

just like you've already developed.

[45:19]

Okay, so I just fed in a bunch of

[45:21]

information. Now it's going to go

[45:22]

through fetch the content from leftclick

[45:24]

and then help me design the site. On the

[45:26]

right hand side, we're creating that

[45:27]

initial index.html. Now in this case, I

[45:30]

obviously did the two website design

[45:32]

simultaneously manually. Uh but what you

[45:34]

can do is you could actually work this

[45:35]

into your website or app design process.

[45:38]

You could actually have it take in,

[45:40]

let's say, three different examples of

[45:43]

uh templates or of design inspirations,

[45:45]

whether from godly.e website or from I

[45:48]

don't know dribble or one of these big

[45:50]

design aggregators and then in the

[45:52]

cloud.mmd you could say hey I actually

[45:53]

want you to develop three versions of

[45:54]

this then you could give it some source

[45:56]

and then you could actually just like

[45:57]

let it do its little test verification

[45:59]

retry loop before giving it you know a

[46:01]

source website like in my case

[46:02]

leftclquick.aii I to have it like do

[46:04]

some modifications or maybe just doing a

[46:06]

big voice dump of what your website is,

[46:08]

what it's for, the various audiences you

[46:10]

serve and stuff. And then at the end,

[46:11]

you could actually have three websites

[46:13]

simultaneously that Claude presents to

[46:14]

you after 5 or 10 minutes and says,

[46:16]

"Which one do you like the best?" The

[46:18]

options here are virtually unlimited.

[46:19]

The other uh website developer so far

[46:22]

has made this, which actually looks

[46:23]

pretty reasonable. You can see that

[46:25]

there's still some things that it needs

[46:26]

to change. Uh some of the text looks

[46:28]

like it's placed weirdly, some of the

[46:29]

blog posts and stuff like that.

[46:30]

Obviously, the development is mostly

[46:32]

hands-off at this point. I'm just

[46:34]

monitoring it. And on the left hand

[46:35]

side, we've now taken four screenshots

[46:37]

of this and gotten really, really close

[46:38]

to that end result. Um, it's now

[46:40]

building like the leftclick site itself.

[46:42]

Most of the time, I don't actually care

[46:44]

too much about what's in the file

[46:45]

explorer. Um, so that is the third panel

[46:48]

on the left hand side of both of these

[46:49]

windows. So, for simplicity, what I do

[46:51]

is I actually just close it out. And

[46:53]

then I usually have on the right hand

[46:54]

side some sort of output that AI has

[46:56]

generated me. And then on the lefth hand

[46:58]

side, I just have my my actual little

[47:00]

chat window. I'm just going to zoom out

[47:01]

just a tiny bit here. So we're still all

[47:03]

on the same page. We could see

[47:04]

everything. Uh and then that way I can

[47:06]

now just orchestrate and kind of take a

[47:08]

step back and see how things go. The

[47:10]

leftclick design is also starting to

[47:11]

come together. As you can see, we've

[47:13]

taken that initial website from actual

[47:15]

as inspiration. So we have like the same

[47:17]

sort of buttons and the nice rounding,

[47:19]

nice hover effects on things and then

[47:21]

obviously we have the font. Uh but then

[47:22]

now we've actually replaced it with

[47:24]

leftclick content. So, the definitive AI

[47:26]

growth partner for fastmoving B2B

[47:27]

companies. Tens of millions of dollars

[47:28]

generated and more saved criteria

[47:30]

systems, real revenue, no fluff. As we

[47:32]

scroll through here, you can see it's

[47:33]

even inserted like a little

[47:34]

button-and-click video element. We all

[47:36]

have our case studies down below. We

[47:38]

have some pictures of me and my business

[47:40]

partner, although we're kind of cut off

[47:41]

at the middle of the head, so we could

[47:42]

probably fix that. And uh yeah, we've

[47:44]

even got some testimonials, which is

[47:45]

really, really clean. Let's see what

[47:47]

happens if I click this button. Oh,

[47:48]

nice. It's even gone to our discovery

[47:50]

page. So, we we we're actually like

[47:51]

having buttonclick functionality and

[47:53]

stuff like that in here as well. kind of

[47:54]

curious what happens if I click on this.

[47:56]

Okay, nothing so far, but maybe I can

[47:57]

tell it to do stuff. We also have an

[47:59]

about and then we have a case studies.

[48:00]

That's really nice. So, yeah, I mean

[48:02]

things are progressing more or less

[48:03]

exactly like we wanted them to. We even

[48:05]

have our little logo. Um, from here on

[48:06]

out, I'm just making minor changes and

[48:08]

um, you know, going to go back and forth

[48:10]

with it until I get what I want. So, on

[48:11]

the left hand side, I'm just going to

[48:12]

voice dump in my voice transcription

[48:14]

tool. I can do this like this.

[48:17]

I really like the output. I think the

[48:20]

logo in the top lefthand corner is a

[48:22]

little too big. Make that smaller. The

[48:24]

bolding of the hero header font is also

[48:26]

quite strong. See if we could try a

[48:28]

Sarah font instead of a sans sarif font.

[48:31]

Underneath the introducing leftclick

[48:33]

section, we have a button player um over

[48:37]

the picture of myself and Alex Ramosi

[48:40]

and Sam Evans. But when I click on this,

[48:42]

nothing happens. Either turn this into a

[48:44]

light box or eliminate that little

[48:47]

button in the middle. The rest of these

[48:49]

look great. My and Noah's profile

[48:52]

pictures are currently cut off at around

[48:54]

the middle of our foreheads. So, move us

[48:57]

down and zoom out of the photo slightly

[48:59]

so that we're perfectly centered in

[49:01]

frame. And everything else here looks

[49:03]

great. Meanwhile, on the right hand

[49:06]

side, we see this index.html is now

[49:08]

done. So, we can open this up. I'll say

[49:10]

open in Chrome. That's now going to open

[49:14]

up the other version of that website for

[49:15]

me. And it's looking like it's pretty

[49:17]

clean. It's pretty matched with what we

[49:19]

have. So, because I want to do the same

[49:21]

thing that I did with the other source,

[49:22]

I'm just going to scroll back up to

[49:24]

where I gave it the instructions to

[49:25]

basically copy over left click. And then

[49:28]

I'm just going to paste this in. And now

[49:30]

I have this also customizing the site to

[49:32]

my specs. You don't have to develop in

[49:34]

multiple tabs. Um, this is something

[49:36]

that I think you learn how to do the

[49:38]

more of these cloud code agents,

[49:41]

frankly, that you're orchestrating. The

[49:43]

benefit to this is obviously you can

[49:44]

develop basically however many times

[49:46]

faster as tabs that you have open. But

[49:48]

the downside is you also tend to context

[49:50]

switch a fair bit. The number one thing

[49:51]

that you don't want clog code to do is

[49:53]

basically just sit around waiting for

[49:55]

your instructions. So if you are going

[49:57]

to do it this way, just be honest with

[49:59]

yourself and ask yourself whether or not

[50:00]

there's always like cloud code operating

[50:02]

in the background. I find if it's not

[50:04]

running because it's waiting for you for

[50:06]

more than maybe 10 or 20% of the time,

[50:08]

you probably have too many tabs open.

[50:09]

Personally, I cap out at about three or

[50:12]

four. Depends on how intellectually

[50:13]

heavy the things that I'm building are.

[50:15]

Um, and you know, it's a learned skill.

[50:16]

It's not something that you're going to

[50:17]

figure out right away. There's a fair

[50:19]

amount of like remembering that you have

[50:20]

to do as well. Um, I've built a couple

[50:22]

of things to help me build things

[50:24]

faster. One of them is a little hook.

[50:26]

That's a chime that keeps on going off

[50:27]

that you've probably been like, "Hey,

[50:28]

what the heck is that thing?" Um, that's

[50:30]

something that you can do, and I'll show

[50:31]

you guys how to do a little bit later on

[50:33]

in the course. With that knowledge, you

[50:35]

can basically set different chimes for

[50:37]

different windows. And when chime one

[50:39]

plays, for instance, you know that your

[50:40]

top left window is done. So, you can go

[50:42]

give it some more instructions, look at

[50:43]

the results. when chime 2 plays, you

[50:45]

know, you can go to the top right window

[50:46]

and and do some work there as well. All

[50:48]

this stuff in due time. Okay, now we've

[50:51]

implemented all of the changes that I

[50:52]

want, including some changes that I

[50:54]

didn't even mention. As you see here in

[50:55]

the background, there's this very slight

[50:57]

little vertical line design um that it

[50:59]

pulled from my main website, which is

[51:01]

really clean. I like that. Makes it

[51:02]

makes it quite different. We also have a

[51:04]

serif font instead of a sand serif. I

[51:06]

like that. Makes me stand out a bit. As

[51:08]

we scroll down, you can see that we've

[51:09]

since removed that little play button,

[51:10]

which didn't really make any sense, and

[51:12]

it's looking clean. We have all of our

[51:14]

profile photos. I like how it kind of

[51:15]

inset us a bit. Looks like my buddy Noah

[51:17]

is still quite cut off, which is

[51:18]

unfortunate. So, I'm going to have to

[51:20]

fix that up. But the rest of this looks

[51:21]

really good, which uh you know, I'm a

[51:23]

fan of. Let me just make sure all these

[51:24]

buttons work. Again, cool. That goes

[51:26]

directly to our thing. With some minor

[51:28]

changes, I think this website's

[51:29]

basically ready to go. And looking at

[51:30]

the other option here, we've um more or

[51:33]

less taken the same hero header. We have

[51:36]

the calendar button working. We have

[51:38]

this nice noise background, which I

[51:39]

like. We still have some issues with the

[51:41]

photos and them being cut off. You're

[51:42]

gonna get stuff like this uh pretty

[51:44]

pretty often to be honest with AI, but

[51:46]

that's okay. You can also manually

[51:47]

readjust them if necessary. I don't

[51:49]

really like how there are two logos, so

[51:50]

I'm just going to do the same thing.

[51:53]

Hey, this looks great. I don't like that

[51:55]

there is both an image logo and then a

[51:57]

text logo. Just have the text logo. We

[51:59]

want a textgram just called leftclick in

[52:01]

the top lefthand corner.

[52:03]

The noise background gradient looks a

[52:07]

little bit blurry, so remove that. Only

[52:11]

keep it on the social proof section.

[52:15]

Myself and Noah's faces look fine. Just

[52:19]

move Nick Sarah's head down about 15% as

[52:23]

it's getting cut off a bit right now.

[52:25]

Center of the testimonials and client

[52:27]

review section. Right now it's a little

[52:29]

bit weirdly set off to the left. And

[52:32]

then change the 2025 copyright to 2026.

[52:36]

That's all. And that looks a lot cleaner

[52:38]

to me. We have our case studies nice and

[52:40]

centered. Both of our heads are visible,

[52:42]

which is really clean. We have our

[52:43]

various services. And then down here,

[52:45]

let me just click this button. Make sure

[52:46]

it opens that tab. Nice. So, I mean, you

[52:48]

know, I wasn't juggling this and trying

[52:50]

to show you guys how to do it

[52:51]

realistically. Hopefully, you guys could

[52:52]

see. You could build your own super

[52:54]

clean, high-end, sexy website in

[52:56]

probably less than 5 minutes now. Um, at

[52:58]

least locally. Uh, later on in the the

[53:00]

course, I'm going to show you guys how

[53:01]

to take this local website and then

[53:02]

deploy it. That will similarly just take

[53:04]

a few minutes once you know what you're

[53:05]

doing and the various platforms to use.

[53:07]

So you could take the same approach. You

[53:09]

could use it to build an app. You could

[53:10]

use it to build a dashboard. You could

[53:11]

use it to build more or less whatever

[53:13]

you want. Whether uh you are sourcing

[53:15]

websites from a repository like godly uh

[53:18]

website ordesign or whatever. Or you're

[53:20]

doing this maybe a little more manually.

[53:22]

Maybe you're actually going into apps

[53:23]

that you really like and then you're

[53:24]

using them as design inspo. Um either

[53:26]

way is perfectly fine so long as you

[53:28]

start with that little nugget.

[53:29]

Everything else as you guys see here

[53:30]

gets a lot easier. And worth noting, um,

[53:32]

I just designed for desktop today, but,

[53:34]

uh, if you wanted to design for mobile

[53:35]

or whatever, you do the exact same

[53:37]

process. You would just do it with a

[53:38]

mobile screenshot. Uh, if you are just

[53:40]

designing for a website, make sure that

[53:41]

your websites are, you know, mobile and

[53:43]

responsive and stuff like that, lest

[53:44]

somebody open it up on their phone and

[53:46]

get treated with, I don't know, my giant

[53:48]

ass forehead. Uh, you can also do that

[53:50]

in the agent. Really easy. Just say,

[53:51]

"Hey, make sure this is nice and mobile

[53:52]

optimized. I'm noticing XYZ image is in

[53:54]

a weird place." Okay, so hopefully you

[53:57]

guys have now learned at least a little

[53:58]

bit about the way to do a practical

[54:00]

build and practical design with cloud

[54:01]

code. As you see, a lot of it's quite

[54:03]

hands-off. It's not like extraordinarily

[54:05]

involved. What you do is you basically

[54:07]

steer it like I I I talked about before.

[54:09]

You carve out the the river and then you

[54:11]

just give it a boat and then it just

[54:13]

goes along its way. So long as there's

[54:15]

some sort of test-driven development

[54:16]

loop, some sort of screenshot or

[54:17]

verification loop, uh the quality that

[54:19]

you can end up with is orders of

[54:20]

magnitude better than not. And if you

[54:22]

guys are ever wondering why you're not

[54:23]

getting the results that you want, just

[54:24]

make sure you have some sort of

[54:25]

verification loop built in. Next up,

[54:27]

we're going to learn how to build

[54:28]

significantly more complex tools, not

[54:30]

just websites and visually designed

[54:32]

things, but also whole backends, whole

[54:34]

architectures, and things that you could

[54:35]

use either to, I don't know, like launch

[54:37]

your own SAS product, or build really

[54:39]

cool internal tooling for yourself, your

[54:41]

own personal life, or for your team. All

[54:43]

right, now that we've done a little bit

[54:44]

of building with Cloud Code, we put

[54:45]

together what I would consider to be

[54:47]

pretty solid websites with just a few

[54:48]

moments of work. Let's dive a little bit

[54:50]

more into Cloud Code's advanced

[54:52]

functionality. And I want to let you

[54:54]

guys know that what I'm about to talk

[54:55]

about here, probably less than 10% of

[54:58]

everybody that currently uses Cloud Code

[55:00]

understands. So, when you unlock what

[55:02]

I'm going to be teaching you in this

[55:03]

module, uh you'll know significantly

[55:05]

more about Cloud Code for one, and then

[55:06]

you'll also be able to combine each of

[55:08]

these cool different features in in

[55:10]

fantastic ways that uh I think you'll

[55:12]

quickly see the value of. So, what is

[55:15]

the claude directory? Just to be clear

[55:18]

here for anybody that doesn't know in

[55:20]

programming convention, first of all,

[55:22]

this is a folder. And in programming

[55:24]

convention, if you put a period in front

[55:25]

of the folder, this basically hides the

[55:28]

folder from view. And so if you just

[55:30]

open it up in a file explorer, you

[55:31]

wouldn't actually see. For instance, you

[55:33]

know how like um I don't know, in my

[55:34]

case, my computer is called Nick. And

[55:36]

then underneath that, I might have some

[55:37]

some other folders. Maybe I'll have like

[55:39]

a documents or something. Let's turn

[55:40]

this off before that frustrates me. I

[55:43]

might have a documents. Well, if under

[55:45]

Nick I stored another folder called

[55:47]

hidden, if I were to open up my file

[55:50]

explorer because it has a period in

[55:51]

front of it and because that just

[55:52]

happens to be the convention, the file

[55:53]

explorer wouldn't show it to me. So this

[55:55]

is sort of like the developer way of,

[55:57]

you know, building folders that don't

[55:59]

really muck around and ruin your nice

[56:01]

organization. So in Claude Codes's case,

[56:03]

they have a lowercase C cla directory.

[56:07]

And inside of this cloud directory,

[56:09]

there's basically support for like 10 or

[56:12]

15 cool advanced features um that once

[56:15]

you know you can augment cloud code

[56:16]

significantly more than sort of vanilla

[56:17]

out of the box. So let's run through all

[56:19]

of them together. This is what like a

[56:21]

fully loaded cloud folder would look

[56:24]

like. Okay. And there's actually two

[56:25]

levels to this and I'll cover both of

[56:26]

them in a moment. But the one that I

[56:28]

want to talk about first is right over

[56:30]

here. So inside of thecloud folder, you

[56:33]

can add a settings.json JSON, which is

[56:36]

team permissions and hooks. I'll talk

[56:38]

about hooks a little bit later on, but

[56:39]

that's how I get my cool little chime

[56:40]

noise at the end of everyone. Uh, you

[56:43]

have settings.local.json.

[56:45]

Anytime you have a local inside of a

[56:47]

file, um, this basically keeps it local

[56:49]

on your computer as opposed to push it

[56:51]

pushes it to a uh, online repository.

[56:53]

For those of you that are unaware, a lot

[56:55]

of programmers and people that use cloud

[56:57]

code use um, GitHub to basically store

[57:00]

all of their active projects. Now,

[57:02]

because GitHub is a cloud service, there

[57:04]

are some instances where you don't

[57:05]

actually want the cloud service to have

[57:08]

access to the data inside of your repo,

[57:10]

particularly if it's quite sensitive

[57:11]

stuff like, you know, tokens and and

[57:13]

authentication keys and whatnot. So,

[57:15]

they developed this convention where you

[57:16]

could just go local whatever um in order

[57:20]

to kind of override that and then not

[57:21]

push it to GitHub. You have the same

[57:24]

pattern here with claude where your

[57:25]

claude.md lives and then

[57:27]

claude.local.md. This is again ignored.

[57:30]

That just means it's not going to go

[57:31]

over to GitHub. Then, interestingly, you

[57:34]

have an agents subfolder, you have a

[57:36]

skills subfolder, and you have a rules

[57:38]

subfolder. Then, finally, you have a

[57:40]

hidden mcp.json as well. You know, I

[57:43]

think if you're somebody coming into

[57:45]

this without a technical background,

[57:46]

you'd look at this and you'd like be

[57:47]

like, "Oh my god, this looks insane."

[57:48]

Like, what the hell's going on?

[57:49]

Settings.js, settings.local.jso,

[57:52]

why is claude capitalized? What does MD

[57:54]

mean? And I'm going to explain all that

[57:56]

stuff to you in due time. But for now,

[57:58]

just know that these are basically the

[58:00]

various buttons that Anthropic, the

[58:02]

developers of Cloud Code, have given you

[58:04]

that you could press to sort of

[58:05]

customize your own instance. And each of

[58:07]

these files you can customize to

[58:09]

whatever degree. You can add whatever

[58:10]

the heck you want in there. Some of

[58:11]

these files reference other files. Um,

[58:14]

you know, it's really up to you and

[58:15]

Claude because most people don't

[58:16]

actually develop this stuff on their

[58:17]

own. They actually like kind of co-work

[58:19]

with Claude to put together their own

[58:20]

settings. Um, but it's up to you how

[58:22]

intense you want to go into. Personally,

[58:24]

I just have a claude.mmd. Sometimes I'll

[58:27]

have skills and agents. I'll run you

[58:29]

through sort of like my own 8020 setup

[58:31]

um later on in the course. Okay. So

[58:34]

anyway, this claude folder actually

[58:36]

lives inside of your claude code folder

[58:40]

workspace wherever you're working. So I

[58:42]

mean I don't actually have a folder set

[58:43]

up yet, but let me do it right now. And

[58:45]

if you use this cloud folder, you're

[58:46]

basically like uh unlocking uh advanced

[58:50]

functionality uh more so than just

[58:52]

having a cloudmd in the root of the

[58:53]

folder. So, that's what I'm going to do.

[58:54]

I'm just going to move over my docloud

[58:56]

to sorry, I'm going to move over my

[58:57]

cloud.nd tocloud.

[59:00]

And then, as you see, there are some

[59:01]

additional folders here that I'm going

[59:02]

to put together as well. Inside of this,

[59:04]

I'm going to go agents.

[59:07]

Also going to go skills.

[59:09]

And over here, I'm going to go rules.

[59:11]

And let's explain what all of these

[59:12]

three mean. The first idea is this idea

[59:14]

of breaking up your big claw.md into

[59:16]

different rules. And so basically what

[59:19]

this slash rules folder allows you to do

[59:21]

is allows you to take everything that

[59:22]

we've written here and then instead of

[59:25]

just sticking it all into one file, you

[59:26]

can define highlevel rules that um

[59:29]

correspond to different parts of let's

[59:31]

say a build. So for instance in this

[59:33]

example there's a rule for code style,

[59:36]

there's a rule for testing, there's a

[59:38]

rule for security, there's a rule for

[59:39]

front end, there's a rule for, you know,

[59:41]

within front end react and then styles

[59:43]

as well. And so, you know, code style

[59:46]

might be a very simple kind of two

[59:48]

paragraph thing that just explains how

[59:50]

to organize your code. Security might be

[59:53]

a pretty simple few paragraph thing that

[59:55]

explains how to, you know, secure your

[59:56]

code bases and whatnot. Styles could be

[59:59]

a list of Tailwind CSS styles or I don't

[60:01]

know, whatever, just like some some sort

[60:03]

of formatting instructions to make

[60:04]

websites look a certain way. And so, for

[60:06]

instance, if you look at our claw.md

[60:08]

over here on the right hand side, you

[60:09]

can see that we've split it into a

[60:10]

variety of sections already. There's

[60:11]

like a workflow section. There's like a

[60:13]

technical default section. There's like

[60:14]

a rule section. We can actually split

[60:16]

these into their own uh rules files. And

[60:19]

that's what I'm going to have Claude do

[60:20]

in a second. Split claude.md into its

[60:24]

component rules. Use the Claude code

[60:27]

rule spec specification if you don't

[60:29]

know what that means.

[60:31]

And so what I'm doing is I'm empowering

[60:33]

claude code to basically go through our

[60:35]

current folder for one. Then if it

[60:38]

doesn't already know what you know rule

[60:40]

specs are, it's going to go read up on

[60:41]

rule specs. And then it's basically just

[60:43]

going to take this file and then split

[60:45]

it into what looks like three file rules

[60:47]

inside of um the rules folder. [gasps]

[60:50]

So now we have rules split into

[60:52]

workflow, technical defaults, and then

[60:54]

design rules. Okay. And as you can see,

[60:56]

this is a little bit more compressed

[60:57]

than we had earlier. Basically, the

[60:58]

title of the file is sort of like that

[61:00]

little heading.

[61:02]

Okay, great. anything else we'd need for

[61:05]

efficient coding

[61:09]

and you know it can go through and it

[61:10]

can create some additional rules for

[61:12]

you. So now if you think about it, okay,

[61:14]

and by the way, I don't actually

[61:15]

recommend just asking claude, hey, build

[61:17]

me rules for efficient coding. It's not

[61:19]

going to do a very good job. Usually the

[61:20]

best place to find like highle

[61:22]

instructions and stuff like that. Um,

[61:23]

that's sort of on the cutting edge. I

[61:24]

would recommend uh like scrolling

[61:26]

through Twitter and then finding cloud

[61:27]

code power users. It's like a real gold

[61:29]

mine. The reality is cloud uh code will

[61:32]

actually like incorporate the most

[61:33]

commonly used cloudmd configurations and

[61:36]

stuff like that into every successive

[61:37]

generation. So a lot of the time, you

[61:39]

know, you don't have to include the

[61:40]

stuff you had in your cloud node from

[61:42]

like Opus 4 or whatever because nowadays

[61:44]

it just sort of understands that

[61:46]

natively. And so if I, you know, talk

[61:48]

about this example in the context of

[61:50]

what we've already done, you know, over

[61:51]

here we had one monolithic claw. MD

[61:54]

file, right? But imagine that we instead

[61:56]

split this into I don't know, let's just

[61:58]

say three rules. You know, we have the

[62:02]

workflows, then over here were the

[62:06]

design rules,

[62:10]

and then the tech defaults. Okay, now

[62:12]

instead of dumping it in as one big claw

[62:14]

in default, we actually have a lot more

[62:15]

granular control over little things. Um,

[62:18]

and so we can organize this to, let's

[62:20]

say, evolve the workflow without

[62:22]

touching the design rules and so on and

[62:23]

so forth. And in general, this form of

[62:25]

segmentation can be useful, especially

[62:26]

when you're working with other people.

[62:28]

you can give people access to let's say

[62:29]

like the styles but then maybe you

[62:31]

actually have full control over like the

[62:33]

top down workflow or as I'm sure you can

[62:36]

imagine you could have a really really

[62:37]

long claude.mmd right a lot of people

[62:39]

have cloudMDs that are I don't know like

[62:41]

many many many thousands of words

[62:43]

sometimes tens of thousands of words so

[62:45]

splitting it up in this way just helps

[62:47]

keep you organized it also helps uh

[62:48]

allow you to see areas that like you

[62:50]

don't really need anymore. It's one

[62:51]

thing if it's a giant file that's 10,000

[62:53]

freaking words long. It's another thing

[62:55]

if it's like pretty simple and pretty

[62:56]

straightforward. So, we can similarly

[62:58]

create skills and agents and they're

[63:00]

organized in very um um you know similar

[63:02]

ways. I'm going to talk through some

[63:04]

specific agents that I'd recommend

[63:05]

having and then ways to use the skills

[63:07]

folder to basically automate large

[63:09]

portions of most knowledge work later.

[63:11]

For now, I want to talk a little bit

[63:12]

about the top half of this image. So,

[63:14]

the bottom half, okay, this is stuff

[63:16]

that we've already kind of discussed.

[63:18]

This is the cloud/folder. But it turns

[63:20]

out there was one folder that exists at

[63:23]

an even higher level than the cloud in

[63:25]

your workspace. Okay? And this is like

[63:28]

the global folder.

[63:31]

Now, anytime you see this little

[63:32]

squiggle, okay, in computer programming

[63:35]

or networking or in file in your file

[63:37]

explorer, this basically refers to like

[63:40]

your home folder, okay? And this isn't

[63:42]

the home folder of your workspace, not

[63:44]

the specific one that we're working in.

[63:45]

This isn't, you know, if I go back to

[63:46]

anti-gravity, my website design example

[63:49]

copy folder. What this is referring to

[63:50]

is this is referring to like the home on

[63:52]

your computer. And so this might be like

[63:53]

the Nicholas folder or something like

[63:55]

that on my computer. And basically Cloud

[63:58]

Code allows you to define settings that

[64:00]

are both local, which corresponds

[64:03]

specifically to the workspace that

[64:04]

you're in, and also global, which are

[64:07]

are basically settings that are shared

[64:08]

between all of your workspaces. And

[64:10]

that's where the second U

[64:12]

[clears throat] sort of category bins

[64:14]

into. And so what we do is in addition

[64:17]

to being able to set a cloud MD on the

[64:20]

local level for instance aka have one

[64:22]

that applies to all workspaces if we

[64:24]

were to expand this just a little bit.

[64:26]

The way that this thing actually works

[64:28]

if you think about it is we have the

[64:32]

claude.md that's over here

[64:35]

and this is your local

[64:39]

claude. Okay. But then we also have

[64:43]

highlevel other clamd files and rules

[64:47]

and stuff like that. Maybe this is

[64:49]

called tech rules. Maybe this is called

[64:52]

permissions, you know. Maybe this one's

[64:54]

called um I don't know style guide. And

[64:58]

these come from your global

[65:03]

little squiggly line slash.cloud.

[65:06]

And the way that this is organized is

[65:07]

very similar to the way that the

[65:09]

local.cloud is organized. it just exists

[65:11]

in a different folder and it basically

[65:12]

supersedes any local cloud

[65:15]

functionality. So this is another

[65:17]

example of like splitting permissions.

[65:19]

For instance, if you're working on a big

[65:20]

team, um you know, maybe you as the

[65:22]

director of the team have access to like

[65:24]

the global.claude

[65:26]

uh uh tilda it's called /.cloud folder

[65:29]

and in there you put your like global

[65:31]

settings. So these are highle rules that

[65:33]

the AI agent in all workspaces reads and

[65:36]

and understands. Maybe things like, hey,

[65:39]

you know, don't allow people to delete

[65:40]

these files or folders. When speaking

[65:43]

with uh, you know, staff members, refer

[65:45]

to them as X, Y, and Z, whatever. And

[65:47]

then every individual engineer on the

[65:49]

team or every individual team member,

[65:50]

they empower themselves with a local

[65:52]

dotcloud folder. And this is ways that a

[65:54]

bunch of companies are currently

[65:55]

starting to organize both their highle,

[65:57]

you know, home clouds or their global

[65:59]

clouds and then um, you know, the ones

[66:01]

that exist uh, per workspace. So to make

[66:03]

a long story short, there's actually

[66:05]

three layers of claw.md that merge

[66:07]

together. We've talked about two of them

[66:08]

so far and there's like one more that's

[66:10]

even higher level, but basically the

[66:12]

first is your personal global and that

[66:15]

is at the very top level here. That's in

[66:17]

your home folder/cloud/cloud.mmd.

[66:21]

Then you have the per project or per

[66:23]

workspace folder which iscloud inside of

[66:26]

your current workspace/cloud.mmd.

[66:28]

And there's also a third option

[66:30]

specifically for enterprise. This is

[66:31]

like your manage system level cloudmd

[66:34]

for enterprise licenses and stuff like

[66:36]

that. 99.9% of you will not have

[66:38]

enterprise licenses. So I'm not going to

[66:39]

talk about this at all, but rest assured

[66:41]

it's a very similar concept. You just

[66:42]

define another markdown file that uh you

[66:44]

know sort of exists in that ranking or

[66:46]

precedence level. Now if I open up a

[66:47]

repo that we haven't looked at before,

[66:49]

this is my own leftclick site where I'm

[66:52]

working using a strategy called git work

[66:54]

trees. Again we'll chat about that

[66:55]

later. But let's say, you know, I open

[66:57]

up a new file folder and I want to run

[66:59]

cloud code in it and I don't actually

[67:00]

have a pre-existing cloud code and you

[67:02]

know I want the model to help me with

[67:03]

this. All I need to do is just open up

[67:05]

that file folder. Okay, open up cloud

[67:07]

code and then type slashinit. We'll get

[67:10]

into more slash commands in a moment.

[67:12]

What this does is this basically allows

[67:14]

us to analyze the current codebase and

[67:17]

then write a cla.md that summarizes what

[67:20]

the current codebase does and then gives

[67:21]

some instructions to uh you know a

[67:23]

future version of claude which is really

[67:25]

cool. So what this is doing right now is

[67:27]

it's reading through all of the files.

[67:29]

It's summarizing them. It's sort of

[67:31]

looking through and you know seeing uh

[67:33]

what what stands out in the codebase

[67:35]

trying to look for commonalities and

[67:37]

patterns between them. And then finally

[67:38]

it ends up creating a a capital

[67:40]

cloud.mmd and it does this directly in

[67:42]

like the workspace route. So it doesn't

[67:43]

do this inside of a cloud folder. You

[67:45]

have to you know do this sort of

[67:46]

organization yourself if you want to go

[67:48]

any higher level. But as you can see

[67:49]

here it just put that together and I can

[67:50]

open it up and I can actually see sort

[67:52]

of like the way that it wrote its own

[67:54]

cloud. MD. So this file provides

[67:56]

guidance to claude code when working

[67:57]

with code in this repository. This is a

[67:59]

premium marketing website for leftclick.

[68:01]

It's an a automation agency targeting to

[68:02]

B2B companies. Here's how to deploy it

[68:04]

to Netlfi. Here's the architecture.

[68:07]

Here's the design system. Here's the

[68:08]

Netlefi config, etc. Why is this

[68:11]

valuable? I mean like it technically has

[68:12]

access to all this information anyway,

[68:14]

right? So like why are we getting it to

[68:15]

summarize it all? Well, we're getting it

[68:16]

to summarize it all because one thing

[68:18]

we're going to talk a lot about in this

[68:19]

course is context management. And that

[68:21]

basically just means um all of the uh

[68:23]

tokens currently in a prompt. As you've

[68:25]

seen, there are multiple levels to this,

[68:27]

right? There's like the global cloudMD

[68:28]

that's injected. Then there's the local

[68:30]

cloudMD that's injected. There's the

[68:32]

enterprise level cloudmd that's

[68:34]

injected. We're then going to talk a lot

[68:36]

more about the tool calls and various

[68:38]

tool definitions. Those are all

[68:39]

injected. And then finally, at the very

[68:40]

end of it, you actually have your own

[68:42]

prompt that you're sending, which is

[68:43]

also part of the context.

[68:45]

>> [snorts]

[68:45]

>> Well, if in addition to that, you force

[68:47]

Claude to read through every single file

[68:48]

every time that you initialize to know

[68:50]

what the hell you're talking about,

[68:51]

obviously you have to add significantly

[68:53]

more tokens to any prompt, right? And by

[68:55]

doing so, a couple things happen. One,

[68:57]

the quality of Claude on average will go

[68:59]

down because there's a negative

[69:01]

relationship between the length of the

[69:03]

prompt and then the quality of Claude's

[69:05]

outputs. That's just sort of the way

[69:07]

that it works statistically with these

[69:08]

models. But two, um, you're also paying

[69:11]

way more because now instead of

[69:12]

consuming, you know, let's say 10,000

[69:14]

tokens at a time, you're consuming a

[69:15]

100,000 because this thing had to read

[69:16]

through your contact. HTML, it had to

[69:18]

read your index.html, it had to read

[69:20]

your message. It had to read everything.

[69:22]

And so, cloud.MD, MD if you think about

[69:24]

it in addition to providing high level

[69:26]

instructions and you know uh uh some

[69:28]

guidance and and steering of the ship

[69:31]

also is a mechanism by which you can

[69:33]

significantly reduce your token usage

[69:35]

and then increase the average quality of

[69:37]

cloud because it'll just know everything

[69:39]

especially when you use uh back/init

[69:42]

like I just showed you a moment ago

[69:43]

before actually having to read through

[69:45]

the files. You know it'll know that

[69:46]

index.html uses an inverted light color

[69:49]

scheme. Okay. It'll know that you know

[69:51]

there's a contact.html html which is a

[69:52]

contact page. It'll know how it's

[69:54]

hosted. It's not going to have to like

[69:55]

do a bunch of API calls to various

[69:56]

services to figure this out. It it just

[69:58]

already knows all this stuff because

[69:59]

that's what the slashet just did. So, if

[70:01]

you don't already have a claw.mmd, I'd

[70:03]

highly recommend go into your folder,

[70:05]

generate one. Um, once you have it

[70:06]

generated, then you can continue making

[70:08]

additions and changes as necessary. But

[70:10]

literally just having a description of

[70:12]

the way that the folder works is like

[70:13]

honestly the the the 90% of the battle.

[70:16]

So, for simplicity, I've compiled the

[70:17]

top recommendations into a quick do and

[70:20]

don'ts guide for you. The first thing to

[70:22]

do is just run backslash init first

[70:24]

anytime you're working in a new folder.

[70:25]

The second is I just use bullet points

[70:27]

and short headings. Try and compress

[70:28]

information as much as possible.

[70:30]

Basically write in like a high

[70:31]

information density style. Don't

[70:33]

[snorts] just voice transcript dump into

[70:34]

your cloudmd. If you wanted to write a

[70:36]

cloudmd for instance using as help

[70:38]

actually voice dump into cloud and then

[70:40]

say turn this into a very high

[70:41]

information density summary of rules and

[70:43]

stuff. Put the most important things at

[70:45]

the top. there's anything that like it

[70:47]

absolutely shouldn't do like never

[70:49]

delete XYZ file or whatever, mention it

[70:51]

up at the very top. The first few things

[70:53]

that AI learns, it tends to remember.

[70:55]

It's sort of like the middle gap of the

[70:56]

prompt. If I were to show you guys what

[70:59]

this actually looks like, basically goes

[71:00]

like this. It remembers a lot of the

[71:02]

beginning. It doesn't really remember

[71:04]

much of the middle and then it's more

[71:05]

likely to remember some of the end. Um,

[71:07]

so this is called your uh primacy bias.

[71:10]

Human beings are like this too, which is

[71:12]

really interesting. And then this is

[71:14]

called your recency bias which means you

[71:16]

know Claude and and us are biased

[71:18]

towards um remembering things at the

[71:20]

very beginning of a stretch and at the

[71:21]

end of the stretch but more so the

[71:23]

beginning which is why you put very

[71:24]

important guardrails at the top. Um

[71:27]

periodically review and prune this like

[71:29]

treat it like living code. If you have

[71:31]

claude constantly update the cloud MD

[71:33]

you will find over time it adds things

[71:34]

that aren't really super necessary. Some

[71:36]

super precise instructions it starts

[71:38]

changing sort of the way that it talks

[71:39]

to you and stuff. So I treat it sort of

[71:40]

like technical debt and then I reduce it

[71:42]

over time. Uh what not to do is don't

[71:45]

dump entire style guides and API docs

[71:47]

into it. This is an unfortunate habit

[71:48]

that I've seen a lot of people do where

[71:49]

they basically are like oh you know I

[71:51]

want this to be my I don't know let's

[71:53]

just say a Panda do companion. So they

[71:55]

go to the Panda API and then they

[71:57]

download the entire thing and then they

[71:58]

try and paste it into the cloudmd. It

[72:00]

ends up being 10,000 tokens and then

[72:01]

keep in mind this is initialized every

[72:02]

single time you run cloud code. Right?

[72:04]

in addition to it taking a little bit

[72:05]

longer because now you have that

[72:06]

initialization time it's also just a

[72:08]

pain in the ass and it's and it's more

[72:09]

costly while reducing claude's quality

[72:11]

as mentioned so don't do that instead

[72:13]

like talk to claude say okay what

[72:15]

specific API endpoints are we going to

[72:17]

need and then give it the whole API and

[72:19]

then just have it like prune it down to

[72:21]

just the specific sections that you need

[72:22]

or specific maybe highle instructions on

[72:25]

how to use this API that maybe is not

[72:27]

super relevant or or trivial I should

[72:29]

say um cloudmd allows you to do what's

[72:32]

called an atlude this is very simple to

[72:34]

just uh you know I I didn't want to

[72:36]

spend too much time on this but

[72:37]

basically if in your cloud.mmd you just

[72:40]

say you know at git.md

[72:43]

and you have a folder called git.mmd

[72:46]

somewhere else in your computer it'll

[72:47]

actually go and it'll like include that

[72:49]

into the cloudmd as you guys can see

[72:51]

that functionality sort of taken care of

[72:53]

by rules but uh just don't add include a

[72:55]

bunch of files unless absolutely

[72:57]

necessary um don't write really vague

[72:59]

rules in general like treat claude like

[73:02]

uh you know a really intelligent savant

[73:04]

style intelligence, but also you know

[73:06]

people that are they tend to be really

[73:08]

intelligent and so on are really

[73:09]

intelligent in one specific little slice

[73:11]

of the field. If you give them too much

[73:13]

rope they'll just hang themselves. So

[73:14]

try not to write like really highle

[73:16]

vague aspirational things unless

[73:18]

absolutely necessary unless it makes

[73:19]

sense. For instance, don't just say be

[73:21]

smart. Don't say make no mistakes.

[73:24]

Claude's not going to understand that,

[73:25]

right? I keep seeing a meme rolling

[73:27]

around Twitter and it's like Claude make

[73:29]

me $1 million. Don't make any mistakes.

[73:32]

and it's like that it's just not going

[73:33]

to that's not going to improve the

[73:34]

quality of its output or anything like

[73:36]

that. Um, in general, you want to keep

[73:39]

it somewhere between like 200 to maybe

[73:41]

500 lines or so max. Um, the

[73:44]

recommendation is not to go any longer

[73:45]

than 500 lines, otherwise again you're

[73:46]

just dumping in a ton of context. And

[73:49]

then don't forget to add rules when

[73:50]

cloud keeps making the same mistake. So

[73:52]

like if you're working with a particular

[73:53]

library or particular software platform

[73:55]

or again a particular API like Panda do

[73:57]

or whatever and they have a very

[73:58]

specific way of going about things you

[74:00]

know every time you load up a fresh

[74:01]

instance of cloud code it's going to

[74:03]

continuously make that mistake which is

[74:04]

going to cost you again in tokens but

[74:05]

then also in context because of quality.

[74:07]

So if you find that it makes a mistake

[74:09]

more than two or three times tell it hey

[74:11]

you know I want you to add this to your

[74:12]

cloud NMD so that this would work the

[74:14]

next time I run it on a fresh instance

[74:16]

of cloud. That's one of my favorite

[74:17]

things to uh to tell it. Okay so these

[74:20]

are just some high level rules.

[74:21]

Obviously, there are more if you want

[74:22]

like a really powerful way of, you know,

[74:25]

finding solid um cloud code tips. Uh and

[74:29]

specifically like Clauded stuff, I

[74:31]

actually go straight over to TwitterX

[74:33]

and then I say, you know, compile the

[74:36]

last month of high ROIC Claude

[74:41]

MD writings. What are the best things to

[74:44]

include? because this technology moves

[74:46]

so quickly rather than me uh you know

[74:49]

trying to like tell you guys to always

[74:50]

include a certain snippet of text in

[74:52]

your cloudmd basically I just have it go

[74:54]

through the last month of Twitter posts

[74:56]

after a moment it'll tell you the most

[74:58]

useful hieroi insights and patterns gro

[75:00]

obviously is uh x's model they have

[75:02]

access to all twitter posts and there

[75:03]

are some extraordinarily intelligent

[75:05]

people on here that basically live

[75:07]

inside of cloud code so I get most of

[75:09]

like my advanced tips from them um and

[75:11]

yeah you know there's there's a lot of

[75:13]

instructions and advice here given in

[75:14]

just the last month or so. Okay, now

[75:16]

that we've talked about the cloud.mmd,

[75:18]

let's talk about a few additional

[75:19]

features that not a lot of people

[75:21]

understand have they have access to

[75:23]

inside of cloud code. The first is this

[75:25]

concept of automemory. So basically in

[75:27]

addition to the cloudmd, there is an

[75:29]

additional tiny little file that's

[75:31]

injected at the top of every session.

[75:34]

And you'll find that anthropic and the

[75:37]

developers of cloud code do a lot of

[75:38]

these injections. It's not just the

[75:40]

cloud MD and it's not just this memory

[75:41]

fo which I'll talk about. They have a

[75:42]

lot tool calls, definitions, lots of

[75:44]

stuff. So, um, the way that memory works

[75:47]

basically is if you tell Claude

[75:49]

something in one instance and you tell

[75:51]

it to remember it, it'll actually write

[75:53]

it to this memory file and then in

[75:55]

another instance when you pull it up,

[75:56]

this is like a global memory file, it'll

[75:58]

it'll remember you. So, if I open up

[75:59]

cloud code again and down here I say um,

[76:02]

I don't know, what's my brother's name?

[76:08]

So, try and ask it some let's say

[76:10]

personal information. um that I wanted

[76:13]

to find out for me. It'll say, "I don't

[76:14]

know your brother's name. You haven't

[76:15]

shared that with me." I say, "Remember

[76:17]

that my brother's name is George."

[76:22]

Now, what it's going to do is it'll save

[76:24]

that to its memory file, okay? Which

[76:28]

already has a few other things like the

[76:29]

fact that my dog's name is Yelpers. You

[76:31]

guys think my dog's name is Yelpers?

[76:34]

Then, if I go to a new fresh cloud code

[76:35]

instance and then I say, "What's my

[76:37]

brother's name?" Notice how this time

[76:39]

we're not going to have that issue. It's

[76:41]

just going to say George. And the reason

[76:42]

why, if we just go back to this very

[76:44]

stereotypical

[76:46]

prototypical example, just continues to

[76:48]

grow. In addition to both the enterprise

[76:52]

uh cloudMD, the global cloudMD and then

[76:56]

the local cloud.MD, MD. You also have

[77:01]

a file here which is separate from all

[77:04]

of those called memory

[77:08]

MD. And Claude will inject this at the

[77:10]

very top of basically every um new

[77:13]

session. So in addition to again this

[77:16]

global section here and then this local

[77:18]

section, we also have a memory and then

[77:20]

we have a bunch of other tool call

[77:21]

definitions and stuff like that which

[77:22]

I'll talk a little bit about later. In

[77:24]

practice, memory isn't super valuable or

[77:26]

anything like that. I mean, claude.mmd

[77:28]

does a lot of that, of course, but uh

[77:30]

you know, it's separate from cloudmd.

[77:32]

You can kind of treat this as claude's

[77:33]

own notes. It's not really your

[77:35]

instruction set. Okay. Next up are

[77:37]

agents. As you see here, we have this

[77:38]

agent subfolder within the cloud local

[77:41]

uh settings folder. This can be pretty

[77:43]

difficult to understand. So, I'm just

[77:45]

going to give you a high level overview

[77:46]

now. And then we're actually going to do

[77:47]

a lot more agent development later on in

[77:49]

the course. But let's just say I want an

[77:51]

agent called tell

[77:54]

me the time MD. And this is a really

[77:58]

simple agent. I basically just want it

[77:59]

to tell me the current time. Um I can

[78:02]

define the tools that it has access to,

[78:04]

the model, the max number of turns that

[78:06]

I can have it autonomously go and

[78:08]

fulfill my request. Um whether I want it

[78:10]

to have global or local memory. I can

[78:12]

give it a little description, a name,

[78:14]

and then also down here just like a

[78:16]

brief little outline of what it is that

[78:17]

I want to do. And so in this case,

[78:19]

hypothetically, I'm just saying this is

[78:20]

a time teller. You know, I basically

[78:22]

want my big agent to talk to my smaller

[78:24]

agent and then say, "Hey, what's the

[78:25]

time?" Very simple and and

[78:27]

straightforward. So, I'm actually going

[78:28]

to open up a new um session here and I'm

[78:32]

going to say, "What time is it? Use my

[78:34]

agent."

[78:36]

And if you haven't already seen the sub

[78:38]

agent tool call looks a little bit

[78:40]

different from what you guys are

[78:41]

probably used to, notice how now we're

[78:43]

opening up this task called tell me the

[78:45]

current time. And what happened is we

[78:47]

see this little in input. What this is

[78:49]

is this is our main agent talking to a

[78:53]

sub agent. And so this main agent

[78:55]

basically said, I see that uh Nick said,

[78:59]

what time is it? And he asked me to use

[79:01]

my agent. Let me check all of my

[79:03]

available agents. It then went through

[79:05]

the agents folder, found that there was

[79:07]

an agent called tell me the time.md and

[79:09]

then said, "Oh, I see there's an agent

[79:11]

here that can tell me the time." Since

[79:13]

Nick asked me for that, this is

[79:14]

obviously the one that he wants me to

[79:15]

use. It then creates a task called tell

[79:18]

me the current time and then sends the

[79:21]

new agent a message saying, "Hey, Nick

[79:23]

wants to know the current time. Please

[79:24]

determine the current time and report it

[79:26]

back." Then at the very end, it says the

[79:28]

current time is 2:23 p.m. MT. Anything

[79:31]

else the agent wanted you to tell me?

[79:37]

Yes. It greeted you with a howdy partner

[79:39]

and then it gave me a little cute cowboy

[79:41]

emoji. The reason for that obviously is

[79:43]

because down here I said also say howdy

[79:45]

partner. And so you can have agents for

[79:48]

a million different things. In general,

[79:50]

one-off functions like tell me the time

[79:52]

aren't really that valuable because you

[79:54]

know your parent agent can sort of

[79:56]

already tell you the time for the most

[79:58]

part. But there are a couple of agents

[80:00]

that do make sense. And so if we split

[80:02]

this into parent and then you variety of

[80:05]

different ways you could call this. Used

[80:06]

to be master slave by the way, which uh

[80:08]

you know had a bunch of issues. They had

[80:10]

to change it. Now, it's like kind of

[80:11]

like parent agent and then child agent.

[80:15]

But if you think about it, there are a

[80:17]

few agents that actually make sense. The

[80:19]

first agent that makes sense is in

[80:21]

general having some sort of research sub

[80:23]

agent. The reason why is because the way

[80:26]

that agents work is they're spawned with

[80:27]

their own context. And so this agent

[80:30]

down here that we just spawned has no uh

[80:32]

no context aside from just this input.

[80:35]

It literally the only text inside of its

[80:37]

um you know prompt is the user wants to

[80:39]

know the current time. please determine

[80:40]

the current time along with you know the

[80:42]

highle instructions that we defined and

[80:44]

tell me the time like that's that's

[80:45]

literally all that it has that's its

[80:47]

whole claw MD essentially

[80:50]

um and so because of this because of the

[80:52]

separation of contacts you know if you

[80:53]

want to keep the total number of tokens

[80:55]

that you use as low as possible in the

[80:56]

parent agent which is usually the

[80:57]

smartest one like the one that you're

[80:59]

paying the big API token usage and stuff

[81:00]

like that for uh instead of trying to

[81:02]

fill in a 100,000 tokens in research

[81:05]

when it goes on the internet and it

[81:06]

looks up trends then it goes checks out

[81:08]

Google analytics and then goes pumps

[81:10]

things into I don't know duck.go So

[81:13]

instead of like filling or polluting all

[81:15]

the context of the parent agent, what

[81:16]

you do is you basically just say, "Hey,

[81:18]

you know, go research

[81:21]

XYZ

[81:23]

and tell me

[81:26]

a summary and then it will go pollute

[81:29]

all of its own contacts window, get it

[81:31]

super long, might use 50 or 100,000

[81:33]

tokens, which is why a lot of people use

[81:35]

the U sonnet model series at the time of

[81:37]

this recording for that purpose. And

[81:39]

then the only thing that actually makes

[81:40]

it back to the parent is just that

[81:42]

summary. So down here this could use

[81:44]

100,000 tokens, right? But then like the

[81:46]

tokens that it transmits back might only

[81:48]

be I don't know like 2k or something

[81:51]

which is if you think about it a cost

[81:52]

savings amount of 50 times or literally

[81:54]

50 times cheaper than whatever the

[81:55]

parent cost would have been. And then we

[81:56]

also get to use um you know a lot of

[81:59]

cheaper uh subm models and stuff like

[82:01]

that like sonnet like haiku and so on

[82:02]

and so forth. So research is really

[82:04]

really good. Um and that's one sub agent

[82:06]

that I would almost always create. I'm

[82:07]

actually going to show you guys how to

[82:08]

create one later for your code and then

[82:10]

also for other automation purposes.

[82:12]

Another one that I really recommend is

[82:14]

basically having like a reviewer agent.

[82:17]

The way that the reviewer agent works is

[82:19]

in contrast with the research agent, you

[82:22]

know, it having no context is actually

[82:24]

the whole point. So basically what

[82:26]

happens is this parent writes a bunch of

[82:28]

code, right? You know, it's like your

[82:29]

index.html or as we're going to see it's

[82:31]

going to be Python scripts or whatever

[82:32]

the heck. It's just going to do a bunch

[82:33]

of code for you. And then after writing

[82:35]

all that code, okay, its context is now

[82:38]

really biased towards the way that it

[82:40]

wrote that code. Basically, you know, if

[82:41]

you think about it, there's like 10,000

[82:43]

tokens and all of those tokens are like,

[82:45]

hey, you know, I should write the code

[82:46]

this way because of whatever reason.

[82:48]

Well, if you want it to write really

[82:50]

really good code, a lot of the time what

[82:52]

you have to do is you actually have to

[82:53]

give it to another version of itself

[82:55]

with no context and then just say, "Hey,

[82:57]

this is the this is the code knowing

[82:59]

absolutely nothing. Do you think this is

[83:01]

good code?" And if the answer to that

[83:02]

question is yes, then obviously it's

[83:04]

good code. But if not, okay, what

[83:05]

usually happens is when you do this,

[83:06]

when you spawn a new agent, then give it

[83:08]

the code, it'll say it's kind of weird

[83:10]

that you wrote it that way. Why did you

[83:11]

write it that way? And then the reason

[83:13]

why is because the initial version of

[83:14]

cloud as mentioned was just really

[83:15]

biased because it had just done all this

[83:17]

thinking and stuff like that. And so,

[83:20]

you know, they do this in in um you

[83:22]

know, like big enterprises stuff like

[83:23]

that. Like you do what's called a code

[83:24]

review where you know a programmer

[83:26]

writes some big long function or some

[83:28]

cool tool or creates a nice app and then

[83:30]

they're so biased about the way to do

[83:32]

things because they've just spent like

[83:34]

10 hours you know hammering a particular

[83:36]

method or a particular approach that

[83:38]

when they give it to a code reviewer aka

[83:40]

another human being the guy looks at it

[83:42]

and he's like what the hell is this? Why

[83:43]

did you do it this way? You could have

[83:44]

done it way easier with another way or

[83:45]

whatever. Or you know hey I noticed that

[83:47]

your security is kind of off. So in this

[83:49]

instance, what the reviewer sub agent

[83:51]

does is it basically takes advantage of

[83:53]

the fact that it has no input and then

[83:55]

it's able to look at the code with like

[83:56]

a totally blank face. And so with this,

[83:59]

you basically say, you know, look at the

[84:01]

code with zero context or no context

[84:06]

and break down

[84:10]

plus improve it. And then what it'll do

[84:13]

is it'll take all of the code. So it

[84:15]

might feed in, you know, like 10,000

[84:17]

lines or something and then it'll return

[84:19]

just the changes to the parent agent and

[84:21]

then, you know, this might be again like

[84:23]

2k tokens or something and the parent

[84:24]

agent will will do the changes cuz it's

[84:26]

usually smarter and then you know now

[84:28]

your code's way higher quality. Finally,

[84:29]

one that a lot of people are using is

[84:30]

sort of this middle one here which is

[84:32]

like QA/ testing. Now this is more of

[84:34]

like an advanced programming thing but

[84:36]

basically in order to determine whether

[84:38]

or not a piece of code works or a tool

[84:39]

works or a piece of software is like

[84:41]

good typically um you can develop a

[84:43]

bunch of tests and then you can subject

[84:45]

your tool or software that you just

[84:46]

created to these tests to figure it out.

[84:48]

Now obviously your parent agent can do

[84:50]

this but um you know this is just

[84:52]

something that would pollute the context

[84:53]

and be tremendously costly both in terms

[84:56]

of tokens but also the intelligence of

[84:57]

the parent model. And so typically what

[84:59]

people do is they'll they'll break

[85:00]

things down into this research sub

[85:01]

agent, a reviewer sub agent, then also

[85:03]

some sort of QA or automated test sub

[85:05]

aent um in big enterprise and that's how

[85:07]

they do like automated testing of their

[85:08]

code, automated test-driven development

[85:09]

and so on and so forth which is similar

[85:11]

to what I was doing earlier when we

[85:13]

designed those websites where you know

[85:15]

we tell it to do the thing it goes and

[85:16]

it does the thing and then it uses some

[85:18]

sort of way to verify that it did the

[85:19]

thing correctly. You can kind of think

[85:20]

of the QA agent as like a way to

[85:22]

facilitate that. It's just with design,

[85:24]

it's pretty easy because you just feed a

[85:25]

screenshot in and then you look at, you

[85:26]

know, the screenshot and if the

[85:27]

screenshots's good, then you're good.

[85:29]

With, you know, back-end development,

[85:30]

obviously, you need a way to determine,

[85:32]

hey, is the thing that I said that it

[85:34]

should be able to do actually happening?

[85:36]

Last but not least, we have skills,

[85:38]

which were previously referred to as

[85:40]

custom/comands.

[85:41]

Now, [snorts] skills are pretty great.

[85:43]

skills basically allow you to automate a

[85:44]

vast majority of I want to say like the

[85:46]

day-to-day knowledge work that you may

[85:48]

or may not be doing especially when you

[85:49]

pair it with tools like Excel or Google

[85:51]

Sheets or whatnot. Now I came up with

[85:54]

this idea of directive orchestration

[85:56]

executions. Um it was this framework

[85:58]

that I put about uh probably about like

[86:00]

four or five months ago just as cloud

[86:02]

was figuring out how skills worked and

[86:04]

and stuff like that and they've since

[86:05]

created skills which I think is actually

[86:07]

a much better alternative to my DOE uh

[86:09]

framework. So I just use skills now. But

[86:12]

basically what these things are are just

[86:14]

like sub agents. These are highle

[86:15]

instructions that you can give to uh the

[86:18]

parent agent. Okay. The one distinction

[86:20]

between sub agent and then skills is in

[86:22]

the sub aent it does it all like a

[86:24]

different agent. In the skill it's like

[86:25]

given to the parent agent and basically

[86:27]

it's just a list of instructions allows

[86:28]

it to do something. So I want to give

[86:29]

you guys a brief little example of what

[86:31]

that might actually look like using a

[86:32]

skill that I developed called shop

[86:33]

Amazon. So heading back to our folder

[86:35]

here, if I go down to skills, you see

[86:36]

that there is now a skill called

[86:38]

shop-mazon.mmd.

[86:40]

Up at the top right hand corner, the

[86:41]

name is shop Amazon. Underneath here is

[86:44]

browse and purchase items on Amazon.ca

[86:46]

via the Chrome DevTools MCP using the

[86:48]

user as to find, compare, or buy

[86:49]

products in Amazon. Then there are a

[86:51]

bunch of highlevel instructions about

[86:52]

how exactly to use um a various like

[86:56]

some various tools to browse Amazon for

[86:59]

me and then find uh products that I want

[87:01]

to do including stop like get purchase

[87:03]

approval. Do not skip this step. So I

[87:06]

mean like I often buy products on Amazon

[87:08]

and to be honest there's just so much

[87:09]

junk on Amazon now that I don't want to

[87:11]

have to spend every you know day hours

[87:13]

of my time like rifling through mostly

[87:16]

you know like uh SEO optimized garbage

[87:18]

which doesn't actually mean anything. So

[87:20]

what I did is I put together a skill to

[87:21]

do that for me. And at the moment um I

[87:24]

require uh something to connect my uh

[87:28]

basically in photography like a bounce

[87:29]

sheet or a reflector with um one of my

[87:32]

stands. So what I want to do is just I'm

[87:35]

going to speak into it and I'm going to

[87:36]

say, "Hey, I'm shopping for something to

[87:39]

connect one of my reflectors to one of

[87:42]

my tripod mounts. I purchased the

[87:44]

reflector a couple days ago and I didn't

[87:46]

realize that I needed, you know,

[87:48]

something separate to kind of clip the

[87:50]

two together. Um, could you shop Amazon

[87:52]

and give me some options that I could

[87:53]

use?

[87:56]

So, I'm just going to press enter here

[87:57]

and then I'm just going to let it go on

[87:59]

its way. We open up the thinking. What

[88:02]

it's going to start with is the user is

[88:03]

asking me to help them shop on Amazon.

[88:05]

Then the user wants to find a reflector

[88:07]

holder or whatever. And now what it's

[88:09]

going to do is actually going to open up

[88:10]

a Chrome tab for me using Chrome

[88:11]

DevTools. and it's going to go and it's

[88:13]

going to look for it. Okay, now it knows

[88:15]

that I'm in Canada, for instance. So,

[88:17]

it's actually looking it up at amazon.ca

[88:19]

up here. It's scrolling through. It's

[88:21]

going to open things up, take

[88:23]

screenshots of various parts of the

[88:25]

page. It's going to read through

[88:26]

everything and so on and so forth. And

[88:28]

uh it'll actually at the end of it get

[88:29]

me a bunch of options according to what

[88:31]

I wrote in my um you know, shop- Amazon

[88:34]

markdown skill. And so, if you think

[88:36]

about it, like this is something that

[88:38]

previously a virtual assistant or

[88:39]

something might have done, right? I mean

[88:40]

this is something that like it I would

[88:42]

have just given to somebody and

[88:44]

delegated away. Hey you know I'm setting

[88:45]

up a photography studio in X Y and Z.

[88:47]

Well now I can actually just write a

[88:49]

skill a highle skill that teaches it how

[88:51]

to use Amazon and then once it goes

[88:53]

through Amazon and you know finds me the

[88:55]

products then just gives me like a big

[88:56]

list of things like this. So what I can

[88:59]

do now is I could say hey you know I

[89:00]

want to buy X Y and Z and then it can go

[89:01]

and actually buy it for me. You know,

[89:03]

obviously, um, I recommend if you guys

[89:05]

are like making purchase decisions with

[89:07]

cloud code, this isn't really something

[89:09]

I'd 100% automate. You know, maybe I'd

[89:10]

have it add all the products to cart and

[89:12]

then I'd say, "Okay, give me the page so

[89:13]

I can review it and then purchase it

[89:14]

myself." Um, but you can automate this

[89:16]

about as crazily in detailed as you

[89:18]

want. What we've done is we basically

[89:20]

made an API out of Amazon and they don't

[89:22]

have one specifically because they don't

[89:24]

want everybody to. With Cloud Skills,

[89:26]

you can do something like that super

[89:27]

easily. The variety of other skills that

[89:29]

you can create. This one's called Upwork

[89:31]

Scrape Apply. I have a bunch that do

[89:33]

like um you know lead scraping for me

[89:35]

more generally. I have skills that

[89:37]

automate the process of sending welcome

[89:38]

emails to new clients. I have skills

[89:40]

that automate the process of building

[89:42]

their deliverables. And what's really

[89:43]

cool is um you're not the only person

[89:46]

that had like you don't actually have to

[89:47]

put the whole skill together yourself.

[89:48]

You can just have Claude help you put

[89:49]

the skill together for a future instance

[89:51]

of Claude. And in practice that's

[89:52]

usually what I do. I'll say something

[89:54]

like hey I want to build a skill that

[89:55]

does X Y and Z. Can you help me format

[89:57]

it? Here's like how skills work because

[89:58]

sometimes it it won't know for whatever

[90:00]

reason. It'll have to go research skill

[90:02]

formatting and stuff like that. And then

[90:03]

it'll say, "Yeah, sure. I could put one

[90:04]

together for you." Then what you do is

[90:05]

you take that, feed that to a fresh

[90:07]

instance of cloud code that has no

[90:08]

understanding what the skill is. See how

[90:10]

it does. If it screws up, you just give

[90:11]

it feedback and say, "Okay, modify the

[90:13]

skill so you do better next time." You

[90:14]

rinse and repeat. And eventually you get

[90:16]

an error rating, which may start off at

[90:18]

like, I don't know, let's say like it

[90:20]

it's only good 70% of the time on your

[90:22]

first. Well, after some changes, now

[90:24]

it's good 80% of the time. Then after a

[90:27]

couple more changes, now it's good 90%

[90:28]

of the time. And then eventually I want

[90:30]

to say you can get to like 98 to 99%

[90:32]

fidelity and accuracy which in any sort

[90:34]

of knowledge field nowadays is more than

[90:36]

enough. I'd say most human beings screw

[90:37]

up more than 1 to 2% of the time. So

[90:39]

we'll cover a little bit more about

[90:40]

skills and how to create them, how to

[90:42]

take pre-existing SOPs and workflows and

[90:44]

stuff like that and convert them into

[90:45]

skills a little bit later on, but for

[90:47]

now just know that they're there. Okay.

[90:49]

So most everything here has now been

[90:51]

covered. Uh, we talked about claud,

[90:54]

we've talked about the cloud.mmd, we've

[90:55]

talked about the local, we talked about

[90:57]

the agents folder, the skills folder,

[90:59]

the rules folder. We only have a few

[91:01]

things left like there's mcps to talk

[91:03]

about, but now is not a good time to, so

[91:04]

I'm going to push that off to later. And

[91:06]

then also the settings.json is a good

[91:08]

thing to mention, but since this deals

[91:09]

with hooks, I'll also talk about that

[91:11]

later. You're now at the point where you

[91:12]

understand, I want to say, you know, 90%

[91:15]

of the internal workings of cloud code.

[91:17]

you understand the file structure, the

[91:19]

organization. You understand the highest

[91:21]

ROI way to build anything, whether it is

[91:23]

a simple website or something more

[91:24]

complex like a full stack app or an

[91:26]

automation. From here on out, it's

[91:27]

really just learning a little bit more

[91:29]

about Claude's various modes. So, plan

[91:31]

mode, dangerously skip permissions, um

[91:34]

you know, uh ask before editing and so

[91:36]

on and so forth. And then we can take

[91:37]

all this and then we can use it to build

[91:38]

something really, really cool. What

[91:40]

we're going to learn about next are the

[91:41]

various permission modes available to us

[91:44]

in Clawed Code. Now, just so we're all

[91:46]

on the same page here, when I say

[91:47]

permission mode, what I'm referring to

[91:49]

is this little button down at the very

[91:51]

bottom of the GUI. And you can toggle

[91:54]

through this button pretty

[91:55]

straightforwardly and easily. And as you

[91:57]

can see here, when we do, we get four

[91:59]

main modes. The first is ask before

[92:02]

edits. The second is edit automatically.

[92:04]

The third is plan mode. And the fourth

[92:06]

is bypass permissions. I should note

[92:08]

that you're not actually going to get

[92:09]

bypass permissions right out of the gate

[92:10]

here, at least not as of the time of

[92:12]

this recording. So, I'll show you guys

[92:13]

how to enable that yourselves. So, we're

[92:16]

going to run through each of these as

[92:17]

well as some extras. And then at the end

[92:19]

of today's module, we're going to focus

[92:20]

significantly more on plan mode. I'm

[92:22]

going to walk you guys through how plan

[92:24]

mode works, why you might want to use

[92:25]

it, and then ultimately how to use plan

[92:27]

mode to build something that I've

[92:28]

personally been wanting to build for

[92:29]

quite a while. So, we're going to do it

[92:30]

interactively together. [snorts] So,

[92:32]

permission modes control how your agents

[92:35]

handle permissions. You also give the

[92:39]

current permission mode to any sub aents

[92:41]

that you employ, which is going to be

[92:43]

pretty important for later. Now, they

[92:45]

tend to inherit the permission context

[92:47]

from the main conversation, but there

[92:48]

are a couple situations in which they

[92:49]

can actually override the mode, too. Um,

[92:52]

for now, I just want you to pretend that

[92:53]

all we're talking about are our current

[92:56]

uh top level agents. We're not focused

[92:58]

on any sub aents or any additional

[93:00]

functionality. Nothing like what we just

[93:01]

talked about earlier. Um, so we have

[93:04]

default. Default is standard permission

[93:06]

checking with prompts. If you guys

[93:08]

remember down here where it says ask

[93:10]

before edits, you guys can think of this

[93:11]

as basically the default. Okay? And so

[93:14]

the default setting is before Claude

[93:17]

makes any changes to any files on your

[93:20]

computer, it has to ask you whether or

[93:22]

not it's okay to do it. And I'll show

[93:25]

you guys what that looks like right now

[93:26]

by saying um you know change

[93:30]

the title of the project to Nick's happy

[93:34]

fun time.

[93:37]

So because I'm in ask before edits mode,

[93:39]

you'll see that before it does any sort

[93:42]

of change, what's going to do is it's

[93:43]

first going to look at the specific file

[93:45]

that defines the title. It's going to

[93:47]

pop open on the right hand side the

[93:49]

exact section of the page that it's

[93:51]

considering updating. So, initially it

[93:53]

said profile name-worklog. Profile name

[93:55]

in this case was Nick. It defined some

[93:57]

really cool badass variable stuff for

[93:58]

me. But because of my dumb request, it's

[94:00]

now saying title equals Nick's happy

[94:02]

funtime and lowercase. You'll also

[94:04]

notice I'm just going to have to remove

[94:05]

my head here so we can see this a little

[94:07]

bit better. You'll also notice that down

[94:09]

at the bottom it says, "Hey, should we

[94:11]

make this edit to index.astro?" That's

[94:13]

the file. And I have three choices. I

[94:15]

can either say yes by clicking or

[94:17]

pressing one, two, saying yes, allow all

[94:20]

edits this session, or three, I could

[94:23]

say no. And finally, I could also say

[94:25]

tell Claude what to do instead. JK,

[94:28]

please don't do this. And so because of

[94:31]

this, it's going to say no changes made

[94:33]

and I will not have actually gone

[94:35]

through the request. Obviously, most of

[94:37]

the time we don't actually do that. We

[94:38]

don't actually make that third uh or

[94:40]

rather we don't click that fourth one.

[94:42]

Um, as you see, it's also kind of

[94:44]

annoying. But generally speaking, if you

[94:45]

guys are working in a codebase that is,

[94:48]

I don't know, really high-risk sort of

[94:50]

high reward thing where like every

[94:51]

change needs to be good or it's going to

[94:52]

screw everything up, you can use ask

[94:55]

before edits. I should note that very

[94:57]

few people are nowadays. We moved away

[94:59]

from ask before edits. Um, most people

[95:01]

now use either the next setting I'm

[95:03]

going to show you or they just bypass

[95:04]

permissions like me entirely. The next

[95:06]

major setting is accept edits. In accept

[95:09]

edits, what we do is we auto accept any

[95:12]

edits to files, but then if you want to

[95:14]

create new files, it'll still ask you

[95:16]

for it. And so, going back to our little

[95:18]

cloud code page here, we move from ask

[95:21]

before edits to edit automatically.

[95:23]

Okay, we can now edit any pre-existing

[95:25]

files. So, what we can do is we could

[95:26]

say, sorry, I actually want you to do

[95:29]

this

[95:31]

update the project to the title.

[95:35]

And because we've selected edit

[95:37]

automatically instead of ask before

[95:39]

edits, it'll actually go through and

[95:40]

it'll automatically update that for me.

[95:42]

See how there was no little panel on the

[95:43]

right hand side. So this is useful when

[95:46]

you want to give the model like cart

[95:47]

blanch control over any pre-existing

[95:49]

files, but you don't want it to like

[95:51]

have any control or any ability to make

[95:53]

new ones. So I'm just going to say

[95:54]

revert the change. And keep in mind that

[95:56]

now because we're in edit automatically,

[95:58]

it can do so without actually having to

[95:59]

pop. The next one is don't ask. Now,

[96:02]

there's no don't ask permission prompt

[96:04]

explicitly set up here. So, if you want

[96:06]

to get to your permissions, you actually

[96:08]

have to go back/permissions and then

[96:10]

continue in a terminal. This is going to

[96:11]

open up a new page for you that's going

[96:14]

to then pump in claude with some

[96:15]

permissions tab. And then you're going

[96:17]

to get a list of all of the different

[96:19]

permissions that you can have including

[96:22]

rules in this workspace. So, as you can

[96:24]

see, uh we have allow, ask, deny

[96:28]

workspace. Okay, so this is equivalent

[96:30]

to our edit all tab. Deny will always

[96:34]

reject requests to use any tools. Ask

[96:36]

will always ask for confirmation before

[96:38]

using tools and allow won't ask before

[96:41]

using any. What's cool is you also have

[96:42]

the ability to add a new rule. So

[96:44]

permission rules are basically where you

[96:46]

give it the name of a tool and then you

[96:49]

either allow it to use the tool or you

[96:51]

force it to ask you for permissions

[96:52]

before using a tool. That obviously

[96:54]

takes us to that logical question. What

[96:56]

are tools Nick? We haven't talked about

[96:57]

them. Well, there a variety of different

[96:59]

ones that cloud code could use. There's

[97:00]

stuff like the ability to fetch things

[97:02]

from the web. There's stuff like bash,

[97:04]

which is the ability to write like

[97:05]

terminal commands and whatnot. And you

[97:07]

know, the purpose of this course is not

[97:08]

to go through every single one of the

[97:09]

tools cuz to be honest, they're always

[97:11]

changing the tools and like the sorts of

[97:12]

tools that we have and stuff. That's not

[97:14]

super valuable, but it's just so that

[97:15]

you know, you can identify and then

[97:18]

change on a like file or tool basis

[97:22]

which things claude code has access to

[97:24]

so long as you're hyper hyper specific

[97:26]

about it using in this case um you know

[97:29]

this little tools output. The next tab

[97:31]

is delegate. Now this is a coordination

[97:33]

mode for agent team leads. Basically,

[97:36]

um, the cloud code now has that feature

[97:37]

called the agent teams feature where a

[97:39]

single agent up at the top can delegate

[97:41]

a bunch of work to a bunch of sub aents.

[97:43]

And so this is the permission that the

[97:45]

agent team lead is given, which

[97:47]

basically allows them to delegate tasks,

[97:49]

although I it's not allowed to do

[97:50]

anything aside from just team management

[97:52]

tools. We'll talk a little bit more

[97:53]

about that later. Then we have bypass

[97:56]

permissions. This is what I've been

[97:57]

using up until now in basically all

[97:59]

instances. Bypass permissions is great

[98:01]

because you can do whatever the heck you

[98:02]

want. I should note that there is

[98:03]

obviously a risk here. There was a case

[98:05]

a little while ago where somebody uh had

[98:07]

cloud code running on bypass permissions

[98:09]

and then I think it was on like a Linux

[98:11]

uh computer or something where there's a

[98:12]

simple terminal command that you could

[98:13]

use to basically delete everything on

[98:15]

your computer. It's like pseudo rm- RL

[98:18]

or RF or something like that. I don't

[98:20]

remember the exact command. I'm sure

[98:21]

Claude would be able to tell you. And uh

[98:23]

basically because of a misinterpretation

[98:25]

of of the request and you know it did a

[98:26]

bunch of research on its own whatever it

[98:29]

eventually thought it had to run this

[98:30]

command. So, it ran the command and it

[98:32]

basically deleted all of the data on the

[98:33]

person's hard drive. They basically had

[98:35]

it bricked and then they needed to take

[98:36]

it in to fix it. I want you to know that

[98:38]

these sorts of things are possible, of

[98:40]

course, and I'm not a lawyer, so don't

[98:41]

sue the hell out of me if this ends up

[98:43]

happening to you, but it's very

[98:45]

unlikely. In practice, this sort of

[98:46]

thing occurs vanishingly small

[98:48]

percentage of the time. And nowadays

[98:50]

with agents getting more and more

[98:51]

autonomy and other things and then more

[98:53]

and more skill and more ability to plan

[98:54]

their own work like we're going to talk

[98:55]

about in a moment with plan mode um you

[98:58]

know most people are shifting towards

[98:59]

using bypass permissions. Bypass

[99:01]

permissions also allows cloud to create

[99:03]

new files not just delete them. That in

[99:05]

addition to editing files can present a

[99:07]

risk. The main risk if we're just being

[99:09]

like businessminded here is actually you

[99:11]

just like you create a bunch of

[99:12]

additional files that maybe you don't

[99:14]

need and uh you know because of that

[99:16]

your workspace can bloat over time. So,

[99:18]

it's pragmatic and pertinent to every

[99:20]

now and then just ask Cloud Code to go

[99:22]

through your files and see if there's

[99:23]

anything in the workspace that just

[99:24]

isn't required anymore. You know,

[99:26]

realistically, as you guys are going to

[99:27]

see when we build this next project, um

[99:29]

Cloud's going to try a bunch of

[99:30]

approaches to do things both on the

[99:32]

front end and the back end, although the

[99:33]

back end um um usually much more often.

[99:36]

And in doing so, it'll accumulate like

[99:38]

different libraries that it probably

[99:39]

doesn't need. It'll accumulate different

[99:40]

files. It'll create temporary JSONs and

[99:43]

and all this fancy stuff. And as a

[99:45]

result of that, if you're not constantly

[99:46]

on top of that, you can have a folder

[99:48]

that has like 10,000 files and it's all

[99:50]

just temp stuff which slows down your

[99:52]

computer and bloat cloud code. I've done

[99:54]

it before. So, we'll talk a little bit

[99:56]

more about context management, how to

[99:57]

effectively do that in one of the next

[99:58]

modules, but I just wanted you guys to

[100:00]

know that for now. In terms of how to

[100:02]

set up bypass permissions, it's actually

[100:04]

non-trivial to do this and uh if it's

[100:06]

the very first time that you're setting

[100:06]

up cloud code, you won't have access to

[100:08]

that. So, head over to the extensions

[100:09]

tab, go down to cloud code for VS Code.

[100:12]

You're going to want to click this

[100:13]

little gear icon and go to settings.

[100:15]

That's going to open up this tab over

[100:16]

here. I'm just going to move it over to

[100:17]

the middle so we could see. You'll

[100:19]

notice that one of the first settings is

[100:20]

cloud code allow dangerously skip

[100:22]

permissions. So, um, it'll recommend

[100:24]

this only for sandboxes with no internet

[100:26]

access. Obviously, mine has internet

[100:28]

access just fine. So, you know, accept

[100:30]

this at your own risk. But if you click

[100:32]

this button, you will now have access to

[100:34]

it down below. There's a few other

[100:35]

settings here like cloud code autosave,

[100:37]

enable new conversation shortcuts,

[100:39]

disable login prompts, and so on and so

[100:40]

forth. Um, I don't really use or change

[100:42]

any of these in practice. Okay. And then

[100:44]

finally, you have plan mode, which is

[100:45]

going to make up the bulk of what we're

[100:47]

talking about next. Plan mode is read

[100:49]

only exploration, which basically means

[100:53]

cloud code can research things using web

[100:55]

tools, so it can go on the internet and

[100:57]

find things out for you. It can read

[100:58]

through all the pre-existing files in

[101:00]

your directory. It can also reason from

[101:02]

first principles and it can kind of use

[101:03]

its own intelligence to figure things

[101:05]

out. And then it can basically take all

[101:06]

of this and put this into a plan

[101:09]

document before presenting it to you.

[101:10]

Now, plan mode is awesome, and I use

[101:12]

plan mode all the time, and basically

[101:14]

anytime I'm doing any sort of build

[101:15]

that's more complicated than a simple

[101:17]

design. The reason why it's so good is

[101:19]

because instead of acting, which in the

[101:22]

real world takes a lot of time and

[101:23]

energy to both do and then undo, all

[101:26]

plan mode does is it just researches all

[101:28]

the factors involved in the build before

[101:30]

doing it. If you work in this like

[101:32]

theoretical plan space and not the

[101:34]

actual like space of the you know the

[101:37]

build and all the libraries and all the

[101:39]

code you will save many many hours of

[101:41]

building over the course of just the

[101:42]

next few days and probably tens and and

[101:45]

hundreds of hours over the course of a

[101:47]

lifetime of using this tool. A minute of

[101:49]

planning saves you 10 minutes of

[101:51]

building. It's just super high leverage

[101:52]

and I'd recommend you. So imagine two

[101:54]

possible scenarios for me. In the first

[101:56]

scenario, you build something with cloud

[101:58]

code. Then you test it and then you

[102:01]

realize that there's some issue with it.

[102:03]

Maybe you're building a simple web app

[102:04]

that you know uh upon login adds some

[102:07]

numbers or credentials to a database. So

[102:10]

you've done this now you've realized

[102:12]

that it's wrong. What that means is

[102:13]

because the approach is wrong. Basically

[102:15]

the time that you spent building while

[102:17]

not completely wasted a big chunk of it

[102:19]

is wasted. Okay. So, not only have you

[102:21]

spent the 15 minutes to build the thing,

[102:23]

not only have you spent the 5 minutes to

[102:24]

test the thing, you also have to rebuild

[102:26]

the thing, which can take 15 minutes

[102:27]

multiplied by however many times you

[102:29]

have to continuously test and retest.

[102:31]

That means that the total amount of time

[102:32]

it takes you is 35 minutes plus a fair

[102:34]

number of tokens, which not a lot of

[102:36]

people talk about, but this can

[102:37]

obviously eat into costs. That is

[102:39]

scenario one. And this is the build

[102:42]

without plan approach. Okay. Now, in

[102:46]

scenario two, which is the build with

[102:48]

plan, what you do is you spend your

[102:50]

first 5 minutes just planning something

[102:52]

super in-depth with Cloud Code's plan

[102:54]

mode. Somewhere during the plan, because

[102:56]

we're f we're we're building a super

[102:58]

like uh granular line item scope here.

[103:01]

We're looking at all the tools and we're

[103:02]

looking at the objects and whatever the

[103:03]

heck. There's a lot that's going on

[103:04]

under the hood. Because we're doing

[103:05]

that, um Cloud Code realizes that it

[103:07]

won't work halfway through and then just

[103:09]

recreates a better plan that does it.

[103:12]

the total amount of time it takes for

[103:13]

you to like get to the building is just

[103:16]

5 minutes plus 5 minutes 10 minutes and

[103:18]

then maybe your actual build time now

[103:20]

because it's like so much better and

[103:22]

faster and stuff like that is only 5

[103:23]

minutes or 15. So if you think about it

[103:25]

like not only have we saved 20 minutes

[103:27]

on a single build, you know, we've also

[103:29]

done so with significantly fewer tokens.

[103:31]

What that means is it's much better to

[103:33]

like do all of your work here basically

[103:38]

during the planning of the spec. And

[103:41]

this is true not only from cloud code

[103:43]

but any sort of programming or really

[103:44]

any sort of project development

[103:46]

as opposed to here which is like where

[103:51]

you know your machines are actually

[103:52]

building this thing like this fantastic

[103:54]

amazing Lego blockbased construction.

[103:57]

I'm just going to pretend that like

[103:58]

we're building some sort of building or

[104:00]

pyramid here, right?

[104:02]

Because, you know, if you screw this up,

[104:04]

what that means is now you have to knock

[104:06]

all these Lego blocks down and then you

[104:07]

have to rebuild it from scratch all over

[104:09]

again. So, better to go off the

[104:11]

blueprint or the architecture diagram or

[104:13]

whatever and make changes there than in

[104:14]

the physical world. The physical world

[104:16]

incurs a fair amount of real costs. By

[104:18]

the way, I know we're working in the

[104:18]

virtual world here, but it's the same

[104:20]

thing as like planning a construction

[104:21]

project, right? you planned construction

[104:23]

projects that you don't run into a

[104:24]

situation where you don't have enough

[104:26]

materials on site and you're like, "Oh

[104:27]

my god, I got to freaking stop

[104:28]

everything for the day and go find

[104:30]

some." So, how do you actually use plan

[104:32]

mode in reality? Well, what I want to do

[104:33]

next is I want to use plan mode to build

[104:35]

out a pretty complicated project. This

[104:37]

project is going to basically be a full

[104:39]

stack web application. It's going to

[104:41]

have a front end. It's going to have uh

[104:43]

authentication and like an interface

[104:45]

where you can log in and it's also going

[104:46]

to have a back end. And we're going to

[104:48]

build it in just a few minutes. The

[104:50]

specific project that I'd like to build

[104:51]

today is basically a proposal generation

[104:54]

platform. I want to automatically be

[104:57]

able to generate proposals, highquality

[104:59]

sales documents that I can then send to

[105:02]

prospects through this web interface. I

[105:04]

want to do it all natively and I

[105:06]

basically want to rebuild the

[105:07]

functionality of I don't know like

[105:09]

docuign or like the hand a doc. I want

[105:11]

there to be all the bells and whistles

[105:13]

on it. I want there to be like the

[105:14]

ability for people to sign but also to

[105:16]

like pay. Uh, I want to have my own

[105:18]

little login screen so that I can give

[105:20]

it to my clients and then maybe my

[105:21]

colleagues and I can obviously also use

[105:23]

it myself. I want to, you know, have

[105:25]

like a couple of templates that I

[105:26]

produce based off of and basically end

[105:28]

to end I want to build a freaking app

[105:29]

today. This is much more complicated

[105:31]

than just a simple landing page, right?

[105:33]

So, how am I going to go about doing it?

[105:34]

Well, the first thing I'm going to do is

[105:36]

I'm actually just going to build out

[105:37]

what I'd consider to be a pretty

[105:38]

straightforward project spec. Uh, which

[105:40]

is just a list of things that I want

[105:42]

this to be able to do. And there's a

[105:44]

bunch of different formatting

[105:45]

methodologies here and like different

[105:46]

ways of doing it. You don't really have

[105:48]

to worry too much about that. All I'm

[105:49]

going to do is I'm basically going to

[105:50]

dump everything in via voice transcript

[105:53]

to a little text tab and then I'm going

[105:55]

to feed that into cloud code and have it

[105:56]

actually format that into a specs

[105:58]

document for me. So I'm going to open up

[105:59]

my voice transcription tool and get

[106:01]

after it. My goal today is to build a

[106:04]

proposal generation platform. I want

[106:07]

this proposal generation platform to

[106:09]

have everything that a common tool like

[106:12]

Pandanda do might have in so far that I

[106:15]

want it to be able to generate endto-end

[106:18]

highquality proposals as okay so I just

[106:21]

did that I have a tremendous amount of

[106:23]

context now what I'm going to do is I'm

[106:24]

actually going to go to a new window in

[106:26]

anti-gravity let's just close out of the

[106:27]

old one I'm then going to open up a new

[106:30]

uh folder so go open folder then here

[106:33]

I'm going to say new one let's just call

[106:34]

this proposal generator creator app.

[106:38]

Once I've created this, I'm I'm going to

[106:39]

dump right in. Then I'm going to go to

[106:41]

clawed code here. Let me zoom in so we

[106:44]

can see this a little bit better. Down

[106:45]

here, I'm going to go um sorry have

[106:47]

bypass permissions plan mode. As you can

[106:49]

see, I'm pretty eager. And then I'm

[106:51]

going to go back here, copy this, and

[106:53]

then just dump all this in. It's fair

[106:55]

amount of white space, so bear with me.

[106:57]

And what I did here is I just I just

[106:58]

dumped in more or less everything that I

[107:00]

wanted to do in the app. So I didn't

[107:02]

specify things in a technical way. I

[107:04]

just told it what I wanted. My goal

[107:06]

today is to build a proposal generation

[107:08]

platform. I want this proposal

[107:09]

generation platform to have almost

[107:10]

everything that a common tool like Panda

[107:12]

might have except for the template

[107:13]

builder functionalities. I just want to

[107:14]

give you a template and have you do it.

[107:16]

Aside from that, I want to be able to

[107:17]

generate end high quality proposals as

[107:19]

static pages that I could send the URL

[107:21]

to the client with. And now it's going

[107:23]

to ask me a bunch of questions about it.

[107:24]

So, what front-end framework do you want

[107:26]

to use? I don't know. Whatever's the

[107:27]

best. So, I'm just going to say this

[107:28]

one. Sure. For e signatures, how legally

[107:31]

robust do you need them to be? Um, I

[107:33]

don't know what that means. I'll just

[107:34]

click the simplest one for Stripe

[107:35]

payments. Will proposals have a fixed

[107:36]

price or variable amounts you set on

[107:38]

proposal? That's a great question. I'll

[107:39]

say variable. Are you using superbase

[107:41]

for the database, too? I'll say

[107:42]

superbase for everything. Cool. Submit

[107:44]

answers. So, what basically this just

[107:46]

did is it crafted a little graphical

[107:48]

user interface for me to ask me some

[107:50]

questions about specific ways that it

[107:51]

wants to do the project. Um, and in this

[107:53]

way, we can go back and forth, which is

[107:55]

quite nice. Okay. Tailwind for utility

[107:57]

CSS shad CN UI for polish. I don't know

[108:00]

what the hell that means. Let's just

[108:01]

click it. Can you share the proposal

[108:03]

template now? Paste it, link it, or tell

[108:05]

me the file path. I'll paste it. Next

[108:06]

message. That sounds great. So, what I'm

[108:08]

going to do now is I'm going to go find

[108:09]

a template of a proposal that I want it

[108:11]

to automatically generate for me. Okay.

[108:13]

So, I have my proposal template over

[108:14]

here. It's pretty sexy. You know, I give

[108:16]

people some problem areas, some

[108:18]

solutions. Um, you know, I talk about

[108:20]

why us. I have a little photo of me,

[108:22]

Alex Ramosi, and Sam Evans up there.

[108:24]

This is pretty sexy. What I'm going to

[108:25]

do next is I'm just going to move this

[108:26]

into my workspace. Onetime project over

[108:29]

here. Here, I'm just going to rename

[108:30]

this to call this proposal template.

[108:33]

That's okay. And then over here, I'll

[108:35]

say great, it's in proposal

[108:38]

template.pdf. And um just because I also

[108:40]

want the design to be really cool, use a

[108:43]

simple clean design, sort of like uh

[108:45]

Apple. Follow the proposal template

[108:47]

design in the actual generation of the

[108:49]

page. For everything else though, make

[108:51]

it kind of apple-esque. Okay. Next up,

[108:53]

it'll read through my proposal template

[108:55]

and then think up what to do next. And

[108:57]

now it is generating a plan for me. It's

[108:59]

figured out the nine-page proposal

[109:00]

document. It's designing some detailed

[109:03]

implementation thing with all the

[109:05]

information, the user flow, and so on

[109:06]

and so forth. What's interesting is it's

[109:08]

giving this to a sub agent. You can see

[109:09]

because it's using the the task feature,

[109:11]

which is um basically coded sub aent

[109:13]

language. As you can see, there's a

[109:14]

tremendous amount of information that

[109:16]

it's going through in order to generate

[109:17]

this. It's also doing some research like

[109:19]

looking up things from Panda just

[109:21]

because I I referenced it. Okay. And at

[109:23]

the end, it's now finished the final

[109:24]

plan file. So, what I'm going to do is

[109:26]

I'm just going to scroll through and

[109:27]

then read it for myself. It's very

[109:29]

comprehensive. Proposal generator

[109:30]

platform implementation plan. We're

[109:32]

going to build a panadoc like proposal

[109:33]

generation platform for leftclick. Users

[109:35]

will sign in, create proposals via AI,

[109:36]

and share public URLs with clients.

[109:38]

Clients will uh view sign canvas

[109:41]

signature and pay. The proposal page

[109:43]

will follow the provided PDF template

[109:44]

design. Also, the app is Appleesque and

[109:47]

minimal. Here's the text stack. I don't

[109:48]

know what most of that stuff means to be

[109:50]

honest, and I'm not going to worry about

[109:51]

it. Proposal template sections cover

[109:53]

your problem areas, your solution, why

[109:55]

us, our team, what working with us looks

[109:57]

like, what you're investing, contract,

[109:58]

signature, payment, database, schema

[110:00]

profiles. I don't know again what the

[110:02]

heck this means, so I'm not going to

[110:03]

worry about it. And then over here, we

[110:05]

have a bunch of routes, API things, file

[110:08]

structures. You know, as somebody that

[110:09]

is not a developer by trade, I'm not

[110:11]

going to focus too much on that stuff,

[110:12]

but it looks like when people sign in,

[110:14]

they hit login. Then there will be a

[110:16]

dashboard page. When they create,

[110:17]

they'll click new proposal, which will

[110:19]

go to dashboard/new. There'll be a few

[110:21]

form fields to fill out like brief

[110:22]

description and pricing rows. They'll

[110:24]

submit it. That'll call opus and then

[110:26]

we'll generate them. And then in order

[110:27]

to copy, we just copy this URL and send

[110:29]

it to the client. That looks pretty

[110:31]

clean to me. I'm sure it's not going to

[110:32]

be perfect, but uh yeah, why don't we

[110:34]

give it a go? So, what I'm going to do

[110:36]

is I'm going to so auto accept. And I

[110:38]

know just because I've done some things

[110:40]

before uh with this tool stack,

[110:41]

Superbase specifically, I'm just going

[110:43]

to go through and I'm going to set up a

[110:44]

Superbase account while it's running me

[110:46]

through all of this stuff. That way I

[110:47]

can kind of you know double up on the

[110:48]

time while this does some work for me. I

[110:50]

can go and do the the Superbase stuff.

[110:52]

So Superbase is a simple database

[110:53]

basically just handles like the login

[110:55]

and also handles like the generation of

[110:57]

records and stuff. First thing that you

[110:58]

would want to do if you were doing

[110:59]

something similar is you just log right

[111:00]

into Superbase. Um set up a new account

[111:02]

if you don't already have one and then

[111:03]

start your project. I'm doing this for

[111:05]

free. So I just started one called

[111:06]

proposal generator and then I'll click

[111:08]

on it which will take me to the project.

[111:10]

Uh somewhere on the left hand side here

[111:11]

we have API keys. API keys are basically

[111:14]

just what we want to give to this so

[111:16]

that it just does everything for me. So

[111:19]

let's see here. We want to give it all

[111:22]

keys. So I'm just going to go copy API

[111:25]

key. And then also I'm just going to

[111:28]

looks like it's asking me some questions

[111:30]

here because it's now oh it's still in

[111:31]

plan mode. So keep in mind we want to go

[111:33]

to bypass permissions mode now because

[111:36]

instead of having to ask every 5 seconds

[111:37]

for things, you know, I want this to be

[111:39]

able to proceed. And then I'm just going

[111:40]

to give it some stuff. We'll say

[111:41]

superbase

[111:43]

uh I don't know secret key. It's going

[111:45]

to give it to it. And I'll also give it

[111:47]

my superbase

[111:50]

public key. Um why am I doing all this?

[111:52]

Because I know it's going to need this

[111:54]

information in order to move forward.

[111:55]

Now in Stripe, I'm going to go over to

[111:57]

one of my accounts and then I'll go test

[111:59]

mode, create sandbox. What this will do

[112:01]

is this will give me like a little

[112:02]

sandbox version of Stripe that I could

[112:05]

use with its own API keys and everything

[112:07]

like that. This way I can uh basically

[112:09]

like you know process the payments and

[112:11]

stuff like that using this test. So here

[112:13]

it is right now. And then if I want to

[112:15]

get my API keys, I have them both over

[112:17]

here. So I'm just going to copy the

[112:18]

publisher key. You know I said I want

[112:21]

you to take payments during uh using

[112:22]

Stripe basically which is why it's doing

[112:24]

this. Let's go public.

[112:28]

And then over here I'll go private key.

[112:31]

Cool. And so now I basically loaded it

[112:33]

up with what I think is everything that

[112:35]

it'll need in order to actually go and

[112:36]

like, you know, connect. So I'm just

[112:39]

going to press enter here. In case you

[112:41]

guys didn't know, when you press enter,

[112:42]

what you do is you basically cue up

[112:44]

another message. So when this is done

[112:45]

with all of its tasks, uh it'll now have

[112:48]

access to all of my keys and stuff. So

[112:49]

now that it's done that task, it's going

[112:51]

to create all the files and it's just

[112:52]

adding all of the information and stuff

[112:54]

like that. Um looks like we have the

[112:56]

superbase anon key. I think that might

[112:58]

be something else that we need. So I'm

[112:59]

going to have to find that information

[113:00]

out. It'll ask me to do this in a

[113:02]

moment, so it's not that big of a deal.

[113:03]

This is here. It just got my API key.

[113:05]

So, it's going to update the ENV file.

[113:07]

And then at the end of this, it's

[113:08]

probably just going to ask me like, hey,

[113:09]

can you also include X, Y, and Z? Now, I

[113:10]

could have, of course, just asked this

[113:12]

thing to start building for me. You

[113:13]

know, I could have just given it all the

[113:14]

specs and said, go for it. But the

[113:16]

planning that I did not only improves

[113:20]

the probability that it'll be able to do

[113:22]

this on a quote unquote one shot, but it

[113:24]

also improves the token efficiency

[113:26]

because it's not going to be exploring

[113:28]

10 different approaches at the time of

[113:30]

building. Instead, you know, it has like

[113:32]

a document it can refer to. And that's

[113:34]

kind of interesting, but human beings

[113:36]

sort of do better that way, too, right?

[113:38]

Like if they're in a business and then

[113:39]

you give them an SOP, standard operating

[113:41]

procedure, or you give them a checklist

[113:43]

or something, or you give them a simple

[113:44]

three-step rule, they always have to

[113:46]

accommodate, they're much much more

[113:48]

likely to actually use those rules. So,

[113:51]

uh, AI is the exact same, at least as of

[113:53]

the time of this recording. And if you

[113:54]

give it like a scratch pad, like a to-do

[113:56]

list, like a checklist, usually quality

[113:58]

improves significantly compared to if

[114:00]

you just have it try and yolo stuff.

[114:02]

Really shown my age with that quote. So,

[114:04]

this isn't at all related to the course,

[114:06]

but uh, check this out. This is a cool

[114:08]

salmon marinade that I just made that

[114:09]

I'm about to cook. Uh, while Claude 4.6

[114:12]

is doing all the work for me. So, oftent

[114:14]

times during the protracted building of

[114:17]

a plan, I'll just step out and I'll like

[114:19]

do some meal prep or I don't know,

[114:21]

sometimes if it's really long, I'll go

[114:22]

hit the gym and by the time that I'm

[114:24]

back, okay, this thing is either still

[114:26]

working or it's just wrapping up its uh

[114:27]

completion. I think right now we're like

[114:30]

6 or 7 minutes in. [snorts] Um, but

[114:32]

what's really cool is you can

[114:33]

parallelize your work. So obviously this

[114:34]

is all about being productive, but there

[114:36]

is also sort of like a time management

[114:38]

component to this as well. Like after

[114:40]

you do a plan and we're building a real

[114:41]

big full stack app here. This is not a

[114:43]

trivial enterprise. After we do that,

[114:45]

like we're going to have to wait a few

[114:46]

minutes. So you know, you can just set

[114:48]

this aside. The value that this thing is

[114:51]

going to get just watching having me

[114:53]

just watch it is quite low. You can

[114:54]

absolutely just set this aside, let it

[114:56]

continue the building, and then come

[114:57]

back either when it's done or when you

[114:59]

hear that little hook chime go off,

[115:00]

which is personally what I use to make

[115:02]

sure I'm always in the loop. Anyway, I'm

[115:03]

going to go marinade the salmon and when

[115:05]

I come back, this app should be done.

[115:06]

Okay, so 3 or 4 minutes later, I just

[115:08]

got back and I see that it is now good

[115:10]

to go. It's just asking me for a few

[115:11]

things. Superbase project URL, which

[115:13]

I'll find, my anthropic API key. I need

[115:16]

to run an SQL migration, give it a

[115:18]

stripe web hook, then ultimately deploy

[115:20]

to Netlefi. What I'm going to do is I'm

[115:22]

going to focus on testing all this stuff

[115:24]

locally and then I'm going to give it

[115:25]

access to all this information. And then

[115:27]

after I'm done, I'll do the pushing and

[115:29]

the deploying and we're going to go

[115:30]

through what that looks like. Keep in

[115:31]

mind, you don't need to have any

[115:32]

computer program experience to do this.

[115:34]

I mean, I didn't really give it anything

[115:35]

that was programming specific. I just

[115:37]

gave it a bunch of needs. And while of

[115:39]

course it went through and did a bunch

[115:40]

of things that were most definitely

[115:42]

programming, I wasn't really a part of

[115:43]

that, which is quite valuable. So, I'm

[115:45]

going to go find this information. I saw

[115:46]

your next public superbase URL and then

[115:48]

my anthropic API key. Okay. So, I see it

[115:51]

says reference using APIs and URLs. This

[115:53]

project ID, so I imagine that's probably

[115:55]

that. Um, I'll say project ID for

[115:58]

superbase is here. and then throw key.

[116:01]

I'll just sign into Claude real quick

[116:02]

and grab. Okay, so then I'm going to

[116:04]

grab this. And then over here, I'm just

[116:06]

going to call it uh proposal generator

[116:09]

app. It's then going to give me a key

[116:11]

that I could use to copy. And no, you

[116:14]

can't steal this from me because I uh uh

[116:17]

I will have deleted it right after this.

[116:19]

Nice try, folks. You'd be surprised at

[116:21]

how many YouTubers don't, which is

[116:22]

hilarious. Like half the YouTube API

[116:24]

keys that you see still work like 6

[116:26]

months later. [snorts] Be careful,

[116:28]

fellow YouTubers. Um, run the SQL

[116:30]

migration is next. So, paste the

[116:31]

contents of this thing into your

[116:32]

Superbase SQL editor. Uh, so I guess I I

[116:35]

need to do that myself. So, I'm just

[116:37]

going to grab this, copy all this, and

[116:39]

then what? Superbase SQL editor and

[116:41]

execute it. Okay, while I'm doing that,

[116:43]

just going to give it this. And then,

[116:45]

where do I get that?

[116:48]

Superbase SQL editor. H. Okay, there's

[116:51]

one right over here. That looks like it.

[116:53]

No clue what the heck I'm doing. Going

[116:55]

to click run. Success. No rows returned.

[116:58]

Awesome. I think that's what's supposed

[117:00]

to happen. Anyway, we'll see. It'll tell

[117:01]

me if there are any issues. Stripe web

[117:04]

hook register this in the Stripe

[117:06]

dashboard and put the whatever secret in

[117:08]

ENV vers. I don't I don't know what that

[117:10]

means and I honestly don't think I need

[117:11]

to do that. So, I'm just going to ask.

[117:13]

Okay, let's test this puppy locally.

[117:15]

Okay, so it's giving me the information.

[117:18]

It's also saying that the local host

[117:20]

thing is ready to go. So, I'm actually

[117:22]

just going to open this up, paste this

[117:24]

in, and see. Cool. I got it. So, it says

[117:26]

I'm going to have to confirm my email.

[117:28]

So, I don't really like that. So, the

[117:29]

first thing I'm going to do is I'll say

[117:31]

looks good. If the user email isn't

[117:34]

confirmed, don't give it to them in a

[117:37]

red error message. That's kind of

[117:39]

unfriendly. Uh just tell them to check

[117:41]

their email after their initial sign up

[117:43]

cuz right now there's no notification

[117:45]

with that.

[117:47]

And then basically, I'm just going to

[117:48]

like work through this step by step,

[117:50]

page by page. Okay. And the first thing

[117:52]

I'm getting is I checked my email inbox.

[117:54]

I'm not seeing an email. So, I'm just

[117:56]

going to give it a message telling it,

[117:58]

hey, you know, first of all, let them

[118:00]

know that they need to confirm their

[118:01]

email. Second of all, actually make sure

[118:03]

that the email is being confirmed cuz

[118:05]

I'm not getting it upon the signin.

[118:06]

Okay. And then it gave me uh the ability

[118:08]

to turn off the toggle email. So, I'm

[118:10]

just going to save that.

[118:12]

So, we now no longer need to confirm the

[118:15]

email. And I'm going to go back here.

[118:16]

Okay. Cool. And it looks like I'm now

[118:18]

into the dashboard. Bottom lefthand

[118:20]

corner, we have what looks to be I don't

[118:21]

know, some Nex.js stuff, I think. I'm

[118:23]

not really sure what this is. This might

[118:24]

just be like some developer stuff. Um,

[118:26]

on the top right hand corner, looks like

[118:28]

we can sign out. So, let me just try

[118:29]

signing out.

[118:31]

Cool. And now in the middle, we can

[118:33]

create a new proposal. Just says

[118:34]

proposals up here. So, click create new.

[118:36]

Now, there's a bunch of information. I

[118:38]

like this. So, why don't I just go my

[118:40]

own information.

[118:42]

I wonder if I just generate proposal if

[118:43]

that's going to work. Let's do a,00500

[118:46]

2,000. Okay. And then AI empowered sales

[118:48]

pipeline. I actually like this. Why

[118:50]

don't we do that? The client needs an

[118:51]

automated lead generation system that

[118:52]

integrates with their existing CRM. They

[118:54]

currently spend 20 hours a week on

[118:55]

manual outreach and want to reduce this

[118:57]

to under five hours while increasing

[118:58]

qualified leads by 3x. Right now, they

[119:01]

want to get to 100K a month. Let's do

[119:03]

that. Okay. Now, for the money shot,

[119:06]

let's um generate proposal.

[119:08]

Click on the button. Don't know what's

[119:10]

going on. No clue whether this is

[119:12]

working. Generally speaking, when you

[119:13]

see a little bar like this with a little

[119:15]

circular thing, um, like this is pretty

[119:18]

poorer in terms of like user experience

[119:21]

because I just don't know if it's

[119:22]

working or not. I'm not really sure. It'

[119:23]

be nice if there could be some sort of

[119:25]

progress, some way that I could see the

[119:26]

thing actually being generated or upon

[119:28]

clicking this, it'd be nice if I went to

[119:30]

a new page. So, I think I'm probably

[119:32]

going to do that. Hey, I'm not sure if

[119:35]

the proposal has been generated. It's

[119:37]

been 10 or 15 seconds right now. Um,

[119:40]

could we do some additional user

[119:42]

feedback after they click the generate

[119:43]

proposal button? Some sort of status,

[119:46]

um, some sort of update. Basically,

[119:48]

there just needs to be some way that I

[119:49]

know that the proposal is actually being

[119:51]

generated, not just hanging all day.

[119:52]

Okay, it did it did end up generating

[119:54]

the proposal after a while. It looks

[119:56]

very clean, but still, I want you to do

[119:57]

this. Okay, so I'm just going to feed

[119:59]

that in here. Um, I'm really liking

[120:01]

this. I mean, look at the logo even.

[120:02]

That's very sexy. Using the same font,

[120:04]

nice confidential.

[120:06]

O, this is so sexy. Look at that. Huh.

[120:08]

Wow. I just built a proposal for this.

[120:13]

What I'm going to do now is just give it

[120:14]

some more feedback. I don't like how the

[120:18]

text immediately under your problem

[120:20]

areas is really constrained widthwise.

[120:24]

You should make that a little longer,

[120:26]

maybe two times as wide.

[120:30]

in each of the bullet in each of the um

[120:33]

sub benefits underneath 01 02 03 04 it's

[120:38]

a little too wide now so make that maybe

[120:40]

75% as wide do the same thing with the

[120:43]

text under your solution

[120:46]

under y us looks great I want to have

[120:48]

that image of myself Alexi and Sam Ovens

[120:52]

in there somewhere so find a way to

[120:54]

include the image in a high quality

[120:56]

manner there's some minor spacing

[121:00]

problems with the we've done this

[121:03]

before. We focus on money and we don't

[121:05]

treat AI as a fad. They're not perfectly

[121:08]

lined up to the numbers 1 2 3 on the

[121:09]

left hand side. Add some images of

[121:12]

myself and Noah.

[121:17]

The what you're investing looks pretty

[121:19]

clean,

[121:25]

but in general there's a bit of a

[121:28]

discord between everything being left

[121:30]

aligned and then the service agreement

[121:32]

being in white at in the middle. Find a

[121:35]

way to fix that.

[121:41]

Okay. And now there's one more thing I

[121:42]

want to do. I just want to verify this

[121:44]

works.

[121:50]

Okay. And now I'm just going to click

[121:52]

sign and pay and we're going to see what

[121:53]

happens. Okay. Cool. Looks like we're

[121:54]

here in the example sandbox. That's

[121:56]

awesome. I'm just going to pump in some

[121:57]

payment information here. Cool. Looks

[121:59]

like the payment went through. And then

[122:00]

we also have this wonderful payment

[122:02]

received button. You can close this

[122:03]

window. That's awesome. Uh okay, great.

[122:05]

So, let's just adjust that final bit.

[122:08]

Excellent. Everything worked great. Um

[122:10]

on the final page where you do the

[122:12]

confetti, make the confetti last a

[122:14]

little bit shorter. The ones on the left

[122:15]

and the right were a little long and

[122:17]

then change will be in touch shortly to

[122:19]

get started

[122:21]

to you'll receive an email with more

[122:24]

details and a link to book a kickoff

[122:26]

call.

[122:27]

Actually, screw that. Let's just give

[122:29]

them a direct calendar link to book a

[122:31]

kickoff call. Why not? That's way easier

[122:33]

and way faster. Okay, so I'm just going

[122:36]

to give it my own calendar.

[122:39]

I'll just give it an example here. And

[122:41]

then boom. I'll just have it go off

[122:43]

again. So, I mean this looks really

[122:44]

clean. So far, I guess there's one more

[122:45]

thing I have to check. I have to check

[122:46]

and see if we can see the proposals

[122:48]

listed. Okay, so yeah, we can. So, can I

[122:49]

click on this? Can we go right back to

[122:51]

the page? Nice. Now, can I just open

[122:53]

this up in some new tab that's not

[122:55]

logged in? Nice. So, the slashp must be

[122:58]

/public. That's really clean. So, I

[123:00]

mean, I like this. I mean, we did this

[123:01]

in just a few minutes. Um, honestly,

[123:03]

very sexy. As you guys could see, I did

[123:05]

very little work. And, uh, yeah, I just

[123:07]

need to find a way to basically um,

[123:09]

standardize the spacing and the width.

[123:10]

Like I don't I don't like how this one

[123:12]

over here is on the left hand side and

[123:14]

then this stuff stretches all the way

[123:15]

out to the right. But this is just a

[123:16]

minor design thing and we can absolutely

[123:18]

significantly upgrade this. God, we even

[123:20]

have the signature here which looks so

[123:21]

cool. I love how that you can now build

[123:23]

your own apps, right? Like you don't

[123:25]

actually have to go to like a big

[123:26]

developer or pay out the ass for some

[123:28]

big platform. You can just like oneshot

[123:30]

an app like this with good enough cloud

[123:32]

code skills. Okay. And it's gone through

[123:34]

and it's updated the widths and stuff

[123:36]

like that. That looks pretty clean. Now

[123:37]

I'm just going to go give it some images

[123:38]

and then it should be good. We're going

[123:39]

to add them to public/ images

[123:41]

apparently. Nice. Looking pretty clean

[123:42]

if I do say so myself. Don't know what

[123:44]

the hell I was doing with uh cuffing my

[123:46]

pants like that. But what are you going

[123:47]

to do? Just looking at what it changed.

[123:50]

It made this a little bit wider, but

[123:51]

then it made this much much smaller. So,

[123:53]

I think what I'm going to do is I'm just

[123:54]

going to enforce like the same width

[123:56]

across the entire page. That probably

[123:58]

makes the most sense. Why don't we just

[123:59]

like constrain it so it'll be like here.

[124:02]

Um I don't know, like here or something.

[124:05]

That way it'll be somewhere in the

[124:06]

middle. Just going to take a screenshot

[124:07]

of this. Hey, this looks good, but I'm

[124:09]

finding it a little too wide at the

[124:10]

moment. I believe we should just

[124:12]

constrain it and um do a bunch of

[124:14]

padding on the left and the right. I

[124:16]

sent you a screenshot of a quick

[124:17]

example. Oh, I guess we didn't actually

[124:19]

do the screenshot, huh? Cuz I mean, it's

[124:21]

good cuz it's like mobile optimized and

[124:23]

stuff, but obviously, you know, on my

[124:25]

actual desktop there's just so much

[124:26]

white space. Let's just center

[124:28]

everything.

[124:30]

Make it scrollable. And then I'm just

[124:32]

going to Yeah, I'm not really sure why I

[124:35]

couldn't take a screenshot of those, but

[124:37]

whatever. That looks good to me. Boom.

[124:39]

Just fed that in. And we should be

[124:41]

pretty good to go, I think. Holy, that

[124:44]

salmon's good. I am definitely doing

[124:46]

that again. [snorts] Anyway, I uh gave

[124:48]

it some more time and it's in centered

[124:50]

most of this. I want to say looks pretty

[124:52]

clean all things considered. uh you

[124:54]

know, we're doing some cutting off of

[124:55]

faces and whatnot, but it's not that

[124:56]

bad. And uh yeah, honestly, this is very

[124:58]

similar to like the quality of a panda.

[125:00]

I guess the last thing I'm going to do

[125:01]

is I'm just going to say stretch the

[125:02]

strategy bit all the way to the end. Um

[125:06]

that probably makes the most sense.

[125:09]

Stretch this bit all the way to the

[125:12]

bounding

[125:13]

boxes of the container, i.e. the white

[125:16]

box should go all the way. Okay, here's

[125:18]

one more thing that I think uh this is a

[125:20]

good opportunity to talk about. A lot of

[125:21]

the time this will tell you to do things

[125:23]

like create a GitHub repo, push the

[125:24]

code, etc. Um, just ask the agent to do

[125:27]

it. Most of the time it can actually do

[125:29]

what it is that it's asking you to do.

[125:31]

Um, if it can, you know, let it try and

[125:33]

then it'll tell you absolutely, hey, can

[125:35]

you do all this for me,

[125:38]

then it'll just tell you what parts it

[125:39]

can do and which parts it can't.

[125:42]

Okay, taking a peek here. Um, it's

[125:44]

telling me to go deploy the project. So,

[125:46]

go here, add new site, import an

[125:48]

existing project. I can do that. Select

[125:51]

we need to build settings should

[125:54]

autofill confirm and click deploy. My

[125:56]

proposal generator is available. That's

[125:58]

funny. This is like the universal domain

[126:02]

name here, right? Like anybody will be

[126:03]

able to access this.

[126:05]

[cough and clears throat]

[126:08]

I'll put an A at the end because I think

[126:10]

it's funny. Okay. Automatically

[126:12]

detected. Next. Uh what else? Confirm.

[126:15]

Click deploy. Okay. Okay. So, go to site

[126:16]

settings and then we need to add all of

[126:19]

this information in. So, I'll do that.

[126:20]

Environment variables import from AENV

[126:23]

file. So, I'm just going to paste this

[126:24]

in.

[126:27]

So, there's this local. Let me grab

[126:29]

that. Okay. And we just imported all of

[126:31]

these. Um,

[126:35]

nice. Oh, that's nice. Um,

[126:38]

now I need to go set up my Stripe web

[126:41]

hook. So, let's just paste that in. Add

[126:43]

a destination. Um, we need to add this

[126:46]

endpoint URL. So, proposal generator. I

[126:48]

don't know exactly what all this stuff

[126:50]

means, but just going to select all. And

[126:53]

then I guess it's just proposal

[126:55]

generator. Okay. And then no

[126:58]

description. I think

[127:01]

that looks good to me. Okay. Everything

[127:03]

is now added. So, go through and then

[127:06]

make sure my site's deployed. I saw some

[127:08]

issue with it earlier. All right. So,

[127:09]

um, this is now going to take whatever

[127:11]

this is. And now that it actually has

[127:13]

access to the app, it should be able to

[127:14]

update it for me. I don't know for sure

[127:16]

to be honest. We'll figure it out.

[127:18]

Hopefully you guys can tell. A lot of

[127:20]

this stuff is me just saying, "Hey, fix

[127:22]

it." And if it can't fix it, what the

[127:24]

hell do I do? And then it just tells you

[127:26]

what to do and then you're good to go.

[127:28]

What's important really is like [snorts]

[127:29]

if you think about it, like the software

[127:31]

engineering stuff, this is like almost

[127:32]

completely automated. I mean, I was

[127:34]

doing more cooking of my salmon rice

[127:36]

bowl than I was actually, you know,

[127:37]

steering the ship uh after a certain

[127:39]

point. And that's because we we made use

[127:41]

of the plan mode so heavily. But what's

[127:43]

important really is like your agency as

[127:44]

a developer and like your ideas and your

[127:47]

willingness and capability to like put

[127:49]

together things. Uh in my case, you

[127:52]

know, I do a lot of proposals. I send

[127:53]

out maybe one every couple of days right

[127:55]

now. At our peak, we were sending like

[127:57]

four or five out a day. And so doing all

[127:59]

that stuff manually was obviously very

[128:00]

time inensive. Well, if I could just

[128:02]

oneshot it with like a little voice

[128:03]

transcript and an AI prompt, obviously,

[128:05]

and then generate my own landing page

[128:06]

like that, that's really valuable for me

[128:07]

as a business. That's something that AI

[128:09]

would not know of right now and would

[128:11]

not really be able to do. So, you know,

[128:14]

allow the AI to be your hands. Um, you

[128:17]

similar to the way that like, you know,

[128:18]

keys and a keyboard are. You're the

[128:20]

person that's coming up with the ideas

[128:21]

and thinking. Okay. So, I'm not sure if

[128:23]

you guys are paying attention while all

[128:24]

of this is occurring. But did you see

[128:27]

this little context tab get filled up?

[128:30]

Cuz this has hit 100% um more than once

[128:33]

at this point. Essentially, what occurs

[128:35]

is this is your total amount of context

[128:36]

available to you. to somebody that's

[128:38]

doing a build, right? Well, when this

[128:40]

reaches a certain uh limit, when it

[128:42]

hits, you know, 99 or 100% or whatever,

[128:44]

what it'll do is it'll take all of the

[128:45]

text that you've written so far, and

[128:47]

it'll compress it down as tightly as

[128:48]

humanly possible, you know, now let me

[128:50]

commit and push. So, netlelfi rebuilds

[128:52]

might literally just turn into netlefi

[128:54]

rebuilding dot. It'll save all those

[128:57]

tokens, but in doing so also increase

[128:59]

the information density of your prompt.

[129:00]

And then it'll basically compact it.

[129:03]

That's what the term is. um so that you

[129:05]

have more information in the same amount

[129:07]

of tokens. So the next prompt that you

[129:09]

use is both higher quality but then also

[129:12]

um doesn't actually run over the token

[129:13]

limit. The unfortunate reality is models

[129:15]

right now only have token limits of

[129:17]

somewhere between 200,000 to about a

[129:18]

million. Some of them have 200,000.

[129:20]

Other ones have a million. The model I'm

[129:21]

currently using is about 200k right now.

[129:22]

And that means that like after 1999,999

[129:26]

tokens go in like there's only room for

[129:28]

one more. Um that's just [snorts] the

[129:30]

way that they're built, right? That's

[129:31]

just their infrastructure. So Claude

[129:33]

does a lot of these like automated

[129:34]

contact management techniques without

[129:36]

really telling you. Um, and that's core

[129:37]

of what we're going to learn after this

[129:39]

project is done. Anyway, I went back and

[129:40]

forth a couple times and now you can see

[129:42]

that we have the app live. It's live on

[129:44]

a public-f facing URL. So I'm going to

[129:46]

go [email protected]

[129:47]

and actually sign in with my previous

[129:49]

account. And now you can see I actually

[129:52]

have access to that same pipeline, that

[129:54]

same page that I had previously. So I'm

[129:55]

going to give that a click. Everything

[129:57]

is nice and centered right now, which is

[129:59]

exactly what I wanted. Super clean. Uh

[130:02]

what's cool too is it stretched the

[130:04]

strategy setup and fee all the way to

[130:05]

the right hand side and then you know I

[130:06]

have the ability to to do my signatures

[130:08]

and whatnot. So suffice to say like this

[130:10]

this worked. This app is now functional.

[130:12]

It's live. It's you know honestly

[130:14]

probably better for my purposes than

[130:15]

Panda was which I was paying out the ass

[130:17]

for. Not that I don't think the

[130:19]

company's cool, but damn is that some

[130:20]

expensive API pricing I think for what

[130:22]

it's doing. In my case I'm doing all

[130:23]

that now basically for free. At least

[130:25]

notifi the deployment solution that I

[130:27]

had available was free. So aside from

[130:29]

the cloud code tokens, you know, it's

[130:30]

one of those things where you spend it

[130:31]

once and then every time I ever generate

[130:34]

a proposal from here on out, it's sort

[130:35]

of fixed now. I mean, we built like an

[130:37]

app here, right? This is a full stack

[130:39]

app, that's what this is. That's why

[130:40]

there's like the login page, there's

[130:41]

stuff on the back end, there's a

[130:42]

database, there's, you know, the front

[130:43]

end and and whatnot as well. But I want

[130:46]

you guys to know that like despite cloud

[130:47]

code and how awesome it is, I'd be very

[130:50]

wary about taking apps that are fully

[130:53]

vibecoded and then publishing them on

[130:55]

the internet. This is sort of my

[130:57]

obligatory safety message because there

[131:00]

are people that are out there that are

[131:02]

using cloud code and similar tools to

[131:04]

try and find security vulnerabilities as

[131:06]

well. And unfortunately, despite how

[131:08]

amazing cloud code is right now, it's

[131:10]

not at the point where it like fully

[131:11]

100% patches everything on the front end

[131:13]

and the back end. So, what this means

[131:15]

is, okay, there are a couple little

[131:17]

safety precautions that I recommend you

[131:18]

have. The first is I'd recommend that

[131:21]

whatever you know URL that you're

[131:23]

putting together or whatnot. It's not

[131:25]

like an obvious or basic URL. Like for

[131:27]

instance, um I wouldn't just go proposal

[131:29]

generated.

[131:31]

I actually get my custom URL and then

[131:32]

I'd make the custom URL something that

[131:34]

you know realistically is not like

[131:36]

trivial. It wouldn't be like google.com,

[131:38]

right? Like not leftclick.ai. I wouldn't

[131:40]

make it short because there are a bunch

[131:42]

of services out there that are scanning

[131:43]

all DNS ranges and also all URLs. uh

[131:45]

which basically mean that like the

[131:47]

shorter and simpler your thing is, the

[131:49]

riskier it is, the more other human

[131:50]

beings will have access to this. Like

[131:51]

there's probably already been I don't

[131:53]

know like 30 or 40 people that have

[131:54]

accessed my service despite the fact

[131:56]

that I just whipped it up. That's just

[131:57]

how it works, right? People are always

[131:59]

constantly scanning the internet and

[132:00]

sending requests. The second is I

[132:02]

wouldn't charge money for these, okay,

[132:05]

without having a developer go through

[132:07]

the authentication, at least the front

[132:08]

end at least once. And I say this for

[132:12]

liability reasons. Like I don't want you

[132:14]

guys to like get a bunch of user data

[132:17]

like usernames, passwords, email

[132:18]

addresses, payment logs and stuff like

[132:20]

that and then have that exposed to bad

[132:22]

actors on the internet. It just isn't

[132:23]

really worth it right now. Like if you

[132:24]

guys are looking to sell apps with this

[132:26]

approach, you know, just pay some

[132:28]

person, you know, a few hundred, have

[132:30]

them look over your app. Let's be real,

[132:31]

the software is not the mode anyway. You

[132:33]

can just give it to them. Screw the NDA.

[132:34]

And just like have them tell you how to

[132:37]

secure your application. Hell, they can

[132:38]

even give Cloud Code some uh some tips

[132:40]

or maybe like a prompt that you could

[132:42]

use to to do it almost automatically.

[132:44]

But I guess what I'm trying to say is

[132:44]

like despite how compelling it may be to

[132:47]

like make these apps public and stuff

[132:48]

like that and then charge people for

[132:49]

their usage, I personally wouldn't. I

[132:51]

personally only use apps right now um

[132:54]

internally within my teams or for my

[132:56]

clients. I do not roll these things out

[132:58]

and then like try and make money from

[133:00]

them off the wider internet when like

[133:02]

the app store or whatever. I've just

[133:03]

seen too many horror stories. Um, we saw

[133:06]

Cloudbot a couple of weeks ago, at least

[133:08]

as the time of this recording, which

[133:09]

later turned into Moltbot, which later

[133:11]

turned into OpenCloud. It rebranded five

[133:13]

million times because every freaking

[133:15]

version of it had major security issues.

[133:17]

And then people were getting prompt

[133:18]

injected and hacked and stuff like that.

[133:20]

And I mean, like, you know, there's a

[133:22]

fair amount of your reputation that goes

[133:23]

with that as somebody in a business

[133:24]

context, but also you are playing with

[133:26]

fire here. This is like, you know, real

[133:27]

human beings, uh, uh, consumer data. So,

[133:30]

I don't want to make safety too big a

[133:31]

part of my thing. It's just Uncle Ben

[133:34]

time. With great power comes great

[133:35]

responsibility. And hopefully you guys

[133:36]

see here. I mean, this took me, I don't

[133:38]

know, 15, 20 minutes realistically end

[133:39]

to end. I was obviously making food and

[133:41]

whatnot, coming back. I wasn't as

[133:42]

efficient as I could have been. [gasps]

[133:44]

But you are certainly wielding great

[133:45]

power right now. And if you're going to

[133:47]

have other people trust you with their

[133:48]

credentials and login and passwords and

[133:50]

everything like that, you need to make

[133:51]

sure that you know you're not using that

[133:53]

power willy-nilly. Next up, I want to

[133:55]

chat context management. Now, for those

[133:57]

of you guys that don't know, context

[133:59]

management is essentially you handling

[134:02]

tokens in a prompt as effectively as

[134:05]

possible. There are many people out

[134:07]

there that overcomplicate the hell out

[134:09]

of this. So, I'm going to do my best not

[134:10]

to. If I open up a new instance of Cloud

[134:13]

Code over here and then I type this

[134:16]

backslash and then scroll down, you'll

[134:18]

see that I have access to a bunch of

[134:19]

really cool functions here. I can

[134:21]

compact, context, cost, debug, innit, I

[134:25]

can do insights. I have the ability to

[134:27]

choose between models, thinking account

[134:30]

and usage, fast mode. Uh we're going to

[134:32]

talk all about this next, but for now I

[134:34]

want to focus specifically on one slash

[134:37]

command called slash context. Look at

[134:39]

what happens when I click this. If I

[134:42]

scroll up and then zoom in a little bit,

[134:45]

you can see here that at the very top,

[134:47]

Claude tells us essentially what is

[134:50]

currently using its context window. For

[134:52]

those of you guys that don't know,

[134:54]

context window in the ter in the um

[134:56]

domain of AI just refers to the total

[134:59]

amount or total number of tokens that a

[135:02]

specific model can deal with at once. So

[135:04]

if you guys remember earlier where we

[135:06]

were doing a build, I said it was about

[135:07]

200,000 for Claude Opus 4.6. That's the

[135:09]

model that I'm currently using. There's

[135:11]

some models out there like um some

[135:12]

sonnet series models that can go up to

[135:14]

one or two million tokens now. Uh but

[135:16]

the number of tokens in a context window

[135:19]

aren't directly related to the

[135:20]

performance of the model. context window

[135:22]

is sort of separate from that. So, Cloud

[135:24]

Opus 4.6 has a context window of about

[135:26]

200,000 tokens. And then you'll see here

[135:28]

that so far I've used 26,400,

[135:32]

which means mathematically I'm 13% of

[135:34]

the way through. You might be asking,

[135:36]

well, Nick, how the hell is that

[135:37]

possible? All you've written so far is

[135:40]

/context. Where are those other 26,398

[135:44]

tokens coming from realistically? And

[135:46]

that's a great question. Immediately

[135:48]

underneath, you could find out for

[135:49]

yourself. And so what I reckon you guys

[135:52]

do right now if you've never done this

[135:53]

before is head over to your own cloud

[135:55]

code instance without even watching any

[135:56]

of this and just type back/context and

[135:59]

look at all of the things that are

[136:00]

currently consuming um your prompt. Now

[136:02]

I should note that this is stuff that

[136:04]

you're actively build for. Okay, this is

[136:05]

not stuff that's free. Despite the fact

[136:07]

that a lot of the time anthropic and

[136:09]

claude um you know they'll add a bunch

[136:12]

of things to your context without really

[136:13]

telling you this is still stuff that at

[136:15]

the end of the day you are paying for.

[136:16]

So, if you submit a bunch of one-off

[136:18]

requests to like individual instances of

[136:19]

cloud, note that there's going to be

[136:21]

your prompt, which it'll bill you for,

[136:22]

but there's also going to be always like

[136:23]

a flat um additional cost of maybe 5,

[136:26]

10, 15,000 tokens or more depending on

[136:28]

how you set it up. Okay, so going down

[136:30]

here under category, you could see all

[136:32]

of the different ways that our tokens

[136:34]

are currently being used and all the

[136:35]

additional tokens that we didn't even

[136:37]

really realize were we're making use of.

[136:39]

The first is your system prompt. Now, if

[136:42]

you guys remember, claude.md takes up a

[136:45]

fair amount of your context. And there's

[136:47]

different types of cloudmds. You have

[136:50]

your global um tilda/.cloud

[136:53]

slash. That's the one that defines all

[136:55]

workspaces, not just the one that you're

[136:57]

currently in. Then you have the

[136:59]

local.cloud right over here in yellow.

[137:02]

Uh in this case, we've broken them down

[137:04]

into individual rule or componentclad

[137:06]

MDs. Underneath you also have capital

[137:09]

memory MD. And then and only then do you

[137:12]

actually, you know, send a message

[137:14]

basically and have your prompt. And so

[137:15]

earlier on, you remember how we had like

[137:17]

26,000 tokens or so? Well, probably, I

[137:19]

don't know, 10,000 tokens or something

[137:22]

like that was just taken up by all these

[137:23]

system prompts. We'll double check in a

[137:25]

second cuz we can actually see the real

[137:26]

number. And then only a couple of

[137:28]

tokens, in this case, two or something

[137:30]

were actually taken up by our our other

[137:32]

request. So that begs the question,

[137:34]

where are you know the other I guess

[137:36]

15,000 or so tokens of the 26,400? In

[137:39]

addition to the system prompt, which to

[137:41]

be clear, this is your claw.md

[137:44]

and rules, you also have system tools,

[137:49]

which is as of the time of this

[137:50]

recording almost 17,000 tokens. Now,

[137:54]

system tools are things like the model's

[137:58]

ability to run bash. That just means

[138:00]

open up a terminal. It's the model's

[138:02]

ability to run web search. That means to

[138:05]

request a web page, have that web page

[138:08]

information brought back, parsed, and

[138:10]

then dealt with. It's the model's

[138:12]

ability to do things like create a plan.

[138:15]

[gasps]

[138:16]

These are all tools and functions that

[138:18]

you don't actually realize that Claude

[138:20]

has access to, but uh it does. And this

[138:22]

is what the claude code developers Boris

[138:25]

Churnney and all the rest of the team

[138:27]

have basically done before you even get

[138:29]

to your own message which is all the way

[138:31]

down over here. Okay, as we see we have

[138:34]

that claw.md stuff. Okay, then we have

[138:37]

the tools. Then we have MCP which I'll

[138:39]

cover in a second. Then we have that

[138:41]

memory MD. Then we have skills. And then

[138:45]

and only then do we actually have our

[138:47]

messages. So there's a lot to go yet.

[138:50]

These tools are constantly changing. And

[138:51]

if you guys want a list of all of them,

[138:53]

you can actually just ask your clawed

[138:55]

model. So I'm just going to say what

[138:56]

tools do you have access to? List them

[138:58]

all and it's going to go through and

[138:59]

it's going to enumerate every single

[139:01]

one. So you see here we have task.

[139:04]

That's what opens up every time we call

[139:05]

a sub agent. There's task output which

[139:08]

is another tool where it like retrieves

[139:09]

the output of the agent. There's bash

[139:11]

which is how you execute shell commands.

[139:13]

Glob is finding a file by pattern. Grep

[139:16]

is searching file contents. Read is just

[139:18]

how it reads files. So you do need an

[139:20]

additional tool for that. Edit is how it

[139:22]

changes things. Write is how it creates

[139:24]

and overwrites new files. Notebook edit

[139:27]

is something specific for a type of file

[139:28]

called a Jupyter notebook. A lot of

[139:30]

people do like data science and stuff

[139:31]

like that in cloud code and Jupyter

[139:33]

notebooks are a big chunk of that.

[139:35]

There's web fetch which is how it calls

[139:37]

uh v various internet sources and then

[139:39]

returns it. This is web search which

[139:41]

allows it to search sort of like Google.

[139:43]

There's todo write. If you guys have

[139:44]

ever wondered where those little to-do

[139:46]

lists come up when Claude Code is doing

[139:48]

stuff, it's that one right over there.

[139:50]

Ask user question. If you guys have ever

[139:51]

wondered where those little graphical

[139:52]

user interfaces come up where it says

[139:54]

pick one, two, three, or tell Claude

[139:56]

something, that's where that comes from.

[139:57]

There's enter plan mode, exit plan mode.

[140:00]

There's skill, which is just a meta

[140:01]

function, which um more or less

[140:03]

orchestrates how you call skills. Then

[140:05]

there's task stop, which is useful

[140:06]

because sometimes cloud needs to stop

[140:08]

something that's running. Okay, so

[140:10]

basically of all of the context, if we

[140:12]

scroll back up here and avoid this MCP

[140:14]

tools, I'll cover that in a second.

[140:16]

Okay, 16,800 tokens are being taken up

[140:19]

by all those tools basically all of the

[140:22]

time. And there's nothing you can do to

[140:23]

fix that unless you want to go in and

[140:25]

make your own version of cloud code or

[140:27]

something. I will say I think that some

[140:29]

of these things are unnecessary. I mean,

[140:31]

I I definitely don't need the Jupyter

[140:32]

notebook calls. I think there are a few

[140:34]

additional features here that maybe I

[140:35]

don't need or we could probably make

[140:36]

them smaller, but this is something that

[140:38]

uh the Cloud Code team is constantly

[140:39]

improving, constantly pruning and and so

[140:41]

on and so forth. Next up, we have the

[140:43]

MCP tools. Now, unlike system tools, MCP

[140:46]

tools are things that you define

[140:48]

yourself, which means every one of these

[140:50]

tools is something that I like basically

[140:52]

put together. This is something that I

[140:53]

connected to uh an MCP server to

[140:56]

basically extend the functionality of my

[140:58]

cloud code. So basically what I'm trying

[140:59]

to say is these right here are default

[141:02]

and these ones right over here you

[141:04]

control. And so you know as a percentage

[141:06]

of my total context I'm spending 2.8% on

[141:09]

customizing my own cloud instance and

[141:10]

then 8.4% which is the default.

[141:12]

Obviously the default ones are a lot

[141:13]

bigger. Um but you know some of these

[141:15]

MCP tools can be pretty valuable. Issues

[141:17]

with some MCP tools are um you know

[141:19]

they're they're really really big as you

[141:20]

guys are going to see when I screw

[141:21]

around with a couple of crappy

[141:22]

libraries. Um so you have to be pretty

[141:24]

selective about how you choose them. And

[141:26]

that's what this next section is down

[141:28]

here called MCP tools. So for instance,

[141:30]

I downloaded an MCP, a model context

[141:33]

protocol toolkit called Chrome DevTools.

[141:36]

This just allows Claude to open my

[141:37]

browser. So what I could do is I could

[141:39]

say, "Hey, open a Chrome instance and go

[141:41]

to nicks.com." If you think about it,

[141:44]

the context that I put together here,

[141:46]

um, let me change this and say, "Great

[141:49]

work. Go to leftclick.ai."

[141:53]

If you think about it, um, you know,

[141:54]

immediately above each of my messages is

[141:56]

obviously all of the tools, right? And

[141:58]

so what these tools are is they're

[141:59]

basically definitions that say, "Hello,

[142:01]

Claude, you have access to the ability

[142:02]

to take a screenshot. If you want to

[142:04]

take a screenshot, just call this

[142:05]

specific tool and it'll do the

[142:07]

screenshotting for you." And so, um,

[142:09]

this is all above sort of my initial

[142:11]

prompt where I say, "Great work. Go to

[142:12]

leftclick.ai." And so when I say go to

[142:14]

leftclick.ai, Claude knows, hm, okay,

[142:16]

like earlier on it said, "If a user asks

[142:17]

you to go to a website, call this tool."

[142:19]

It obviously just references the

[142:21]

specific thing. And as you guys could

[142:22]

see here, it's it's navigating, it's

[142:24]

taking screenshots, and it's basically

[142:25]

controlling my browser right now, which

[142:27]

is really cool. So, that's an example of

[142:29]

a tool that I think is pretty valuable.

[142:30]

Um, that said, there are a lot of tools

[142:32]

that aren't super valuable. And

[142:33]

unfortunately, MCP tends to consume a

[142:36]

fair amount of your context if you're

[142:37]

not careful. As you see here, there's

[142:39]

click, close page, drag, emulate,

[142:41]

evaluate, script, fill, fill form, and

[142:42]

so on and so forth. I'm not going to

[142:44]

cover all these because there's just so

[142:45]

many different MCPS that you could use,

[142:46]

and each of them have so many different

[142:47]

tools. Underneath that, you have memory

[142:49]

files. You guys remember earlier when I

[142:51]

told you that there was this big like

[142:52]

md?

[142:56]

That memory is super straightforward and

[142:58]

in our case that's only 88 tokens. Not

[143:00]

that big of a deal, but it's basically

[143:01]

claude scratchpad as it works. Next, you

[143:04]

have skills. If you guys remember, we

[143:05]

had a claude skills uh skills folder in

[143:09]

another repo. That claude skills folder

[143:11]

basically in our case like I don't know

[143:13]

browsed Amazon and found something for

[143:14]

us. In this one, we don't. Um, so the

[143:17]

only thing it's really storing is just

[143:18]

the skills definition, which in this

[143:20]

case is 61 tokens expressed as a

[143:22]

fraction of the total number of tokens

[143:24]

we have available to us, 200,000. You

[143:26]

can see that that's uh that's not even

[143:27]

0.1%. By the way, as I've communicated

[143:30]

and kept talking with Claude, we've

[143:32]

accumulated more tokens. So you can see

[143:33]

how earlier it was at like 24,000. Well,

[143:35]

now we're at 30,600, right? We've gone

[143:37]

up from, I think, 13% to 15%. So that'll

[143:39]

continue happening as we as we go on.

[143:42]

Next up, of course, you have your

[143:43]

messages. And so in our case, we're

[143:44]

consuming 2.6% 6% of our entire contact

[143:46]

window right now just through messages

[143:48]

and just through back and forth. This is

[143:49]

sort of inescapable or inavvoidable.

[143:51]

Although there are ways to manage your

[143:53]

context a lot more efficiently. You

[143:54]

know, a couple of ways are speaking high

[143:56]

information density ways wherever

[143:58]

possible. Obviously, voice transcript

[144:00]

tools are kind of against that because

[144:01]

they take into account all of your ums

[144:03]

and a's and whatnot. But if you wanted

[144:05]

to be really really efficient, what you

[144:07]

would do is you would take your voice

[144:08]

transcript, pump it into a cheaper

[144:10]

model, one that doesn't cost you as much

[144:11]

money, that's in a separate tab, have

[144:13]

that summarize it into a very tight

[144:14]

request, and then actually send that to

[144:16]

the initial um, you know, Claude agent.

[144:18]

And that's a strategy that I've used to

[144:20]

manage really small context windows in

[144:21]

the past. Obligatory. This is where the

[144:23]

conversation with Claude actually

[144:24]

occurs. I should note that I don't know

[144:26]

if you guys remember, but sometimes you

[144:28]

can ask Claude stuff and then a little

[144:30]

thinking tab will pop up. Well, that

[144:31]

thinking tab isn't actually included in

[144:33]

the messages. You are still build for

[144:34]

this separately, but basically what

[144:36]

happens is um at the time that you make

[144:38]

a request and at the time that the

[144:39]

thinking occurs, it sticks all that onto

[144:41]

the big message chain and then it uses

[144:43]

that to figure out the next thing. So it

[144:45]

uses basically this thinking area. It's

[144:47]

almost a scratch pad to figure out more.

[144:48]

And then um what it does is it collapses

[144:51]

it, disappears it, and then it just

[144:52]

gives you the answer and then it

[144:54]

pretends as if the reasoning or thinking

[144:56]

little section didn't even exist. So

[144:58]

don't worry about thinking here assuming

[144:59]

you have extended thinking on. um that

[145:01]

doesn't really get included although of

[145:03]

course you're still paying for it. And

[145:05]

then finally the bulk of our context is

[145:06]

free space 67.7% which is good for us.

[145:09]

Not really sure why they include that

[145:10]

here but they do. The last thing that

[145:12]

you guys need to understand is this idea

[145:14]

of an autocompact buffer. Now an

[145:15]

autocompact buffer is basically just a

[145:17]

certain amount of space that claude

[145:18]

developers always leave available. Um

[145:21]

and then basically what happens is when

[145:22]

you hit that buffer aka when there's

[145:24]

only 33,000 tokens left it'll

[145:26]

automatically compact all of the

[145:28]

previous conversation history. Now, this

[145:30]

is done automatically, but you can also

[145:32]

do this manually by going /compact. What

[145:35]

happens when you go /compact is it

[145:36]

basically takes all of our conversation

[145:38]

history here. Okay? It'll take this,

[145:40]

it'll take that, it'll take all that,

[145:42]

and then it'll just squash it down into

[145:44]

a very high information density summary.

[145:46]

And so, what I'm going to do is

[145:47]

immediately after it compacts, I'm

[145:48]

actually going to ask it to tell me what

[145:49]

it just compacted. Basically, hey, you

[145:51]

know, tell me what is currently

[145:52]

available in your context. Okay? And as

[145:54]

you can see here, it says, "This session

[145:56]

is being continued from a previous

[145:57]

conversation that ran out of context.

[145:58]

The summary below covers the earlier

[146:00]

portion of the conversation. First,

[146:02]

there's an analysis tab where it

[146:03]

chronologically analyzes your

[146:04]

conversation. First message, user ran

[146:07]

this, then user asked this, then user

[146:09]

asked this, then user asked this, user

[146:11]

asked this, user asked this, and so on

[146:12]

and so forth. Okay? And so, if you

[146:14]

compare all of this to all of the

[146:16]

messages and all of the tool calls and

[146:18]

everything like that we did above, this

[146:19]

will be fewer tokens, right?

[146:21]

Significantly, so probably like three or

[146:22]

4x. Um, and so in this way, gradual and

[146:26]

progressive compaction of a conversation

[146:28]

maximizes the information density. And

[146:30]

then Claude's really good at like not

[146:32]

leaving important things out. Um, so you

[146:34]

tend to have most of the information

[146:36]

that you really want or really need in

[146:38]

this context. They've started also

[146:40]

recently doing something called

[146:41]

autocompaction which is where this

[146:42]

compaction is occurring constantly in

[146:44]

the background for you aka your oldest

[146:45]

messages are just like compacted into um

[146:48]

you know higher information density

[146:49]

summaries and then that's constantly

[146:50]

sort of like a tail behind your current

[146:52]

conversation. That's pretty cool because

[146:54]

if you think about it um you know us

[146:55]

human beings are just not very good at

[146:57]

remaining really concise and being very

[146:58]

precise and constantly updating that

[147:01]

context improves the quality of

[147:03]

subsequent outputs as well as you know

[147:05]

bills you less which is kind of

[147:06]

interesting because uh you know

[147:08]

anthropic whole business model right now

[147:09]

is monetizing claude and and you know

[147:12]

claude and claude code. So the fact that

[147:14]

they're doing this sort of runs contrary

[147:15]

to their interests which is one of the

[147:17]

reasons why I like them as a company.

[147:18]

They're obviously motivated by the

[147:20]

quality of their product more

[147:21]

necessarily than their uh their revenue

[147:22]

and whatnot. So Claude's website here is

[147:25]

really helpful. They have actually a

[147:26]

whole section dedicated to reducing

[147:28]

token usage and minimizing the amount of

[147:30]

what's called context rot that

[147:32]

accumulates in a conversation. Uh I'm

[147:34]

just going to run through them with you

[147:35]

guys. And I want you to know this is

[147:36]

this is constantly being updated. So the

[147:37]

time that you look at it might be a

[147:38]

little bit different from the time that

[147:39]

I'm looking at it. Again, if you guys

[147:41]

want like up-to-date up-to-date tips, I

[147:43]

recommend checking out Twitter, X.com,

[147:45]

talking to Grock, and just saying

[147:46]

summarize the best, you know, strategies

[147:48]

to reduce token usage that users have

[147:50]

been talking about in the last month or

[147:51]

so. So, you have, you know, strategies

[147:52]

like rag, retrieval augmented

[147:54]

generation. You have strategies like

[147:55]

continuously and consistently

[147:57]

compressing the cloudMD. You have

[147:59]

strategies like telling, you know,

[148:00]

Claude to write as concisely as

[148:02]

possible, but then turning on um

[148:04]

extended thinking, which is a feature

[148:05]

I'll run you guys through later, which

[148:07]

basically means you bloat up the

[148:08]

reasoning tokens, but then the actual

[148:09]

token spill uh ends up being very low,

[148:12]

and so on and [snorts] so forth. So, the

[148:14]

number one recommendation that they have

[148:15]

is to manage your context proactively by

[148:17]

using /cost. This helps you check your

[148:19]

current token usage. You can also

[148:20]

configure a status line to display

[148:22]

continuously. In order to configure a

[148:24]

status line in cloud code, you just go

[148:26]

slash status line. You'll notice that

[148:28]

you can't currently do this inside of

[148:29]

the GUI version. So, what you have to do

[148:31]

instead is you have to open cloud in a

[148:32]

terminal here because, you know,

[148:34]

graphical user interfaces don't have a

[148:36]

status line. A status line is basically

[148:38]

this little piece of text that occurs

[148:39]

before. And then you just go slash

[148:41]

status, sorry, status line here. It'll

[148:45]

ask you what you want to put in your

[148:46]

status line.

[148:48]

And so, I'm basically just going to ask

[148:50]

it to include a little like uh like

[148:52]

loading bar with the total number of

[148:54]

tokens that I've used.

[148:56]

update my status line. So, it includes a

[148:58]

little loading bar that is how many

[149:00]

tokens that I've used out of my total

[149:02]

context. So, as you can see, it

[149:03]

converted that into another mini prompt

[149:05]

using a status line setup agent. And

[149:07]

then, um, it's going to do this kind of

[149:08]

cool little status effect. So, I'm

[149:10]

actually going to get to see it down

[149:11]

here. I'll show you guys what that looks

[149:12]

like in a sec. Okay. And as we could see

[149:14]

here, we now have that little bar. So,

[149:16]

13% of my tokens are used up. That's

[149:19]

kind of neat. We also see the current

[149:20]

model. and then you know the the branch

[149:22]

that we're on if you're into programming

[149:24]

with uh repositories and like git

[149:26]

workflows and stuff like that. This to

[149:27]

me isn't like super valuable to be

[149:29]

honest if I'm being frank. I just

[149:30]

thought it was kind of cool. So just

[149:32]

another reason why doing all of this in

[149:34]

the terminal gives you significantly

[149:35]

more latitude. You can't really just

[149:37]

like add a status line to the GUI

[149:38]

version at least not now. But this one's

[149:40]

very hackable. Another thing you can do

[149:41]

is you can add custom compaction

[149:43]

instructions. So um you can actually say

[149:45]

/compact and then give it a prompt

[149:47]

telling it what to prioritize. You could

[149:49]

do this every now and then, which is

[149:50]

obviously quite valuable. Um, you can

[149:52]

use slashclear to start fresh when

[149:54]

switching to something that is

[149:55]

unrelated. So, what I mean by this is if

[149:57]

I just delete this little terminal

[149:58]

instance down here, just go back/clear.

[150:01]

What it'll do is it'll clear the entire

[150:02]

conversation. So, you have no context

[150:04]

anymore. So, now there's no previous

[150:06]

context. If I go back to /context, you

[150:08]

can see that scrolling up to messages,

[150:10]

you know, we have 152 tokens, which is

[150:12]

basically everything that we've done

[150:13]

here so far. Aside from that, you can

[150:14]

use instructions inside of the claw.mmd

[150:16]

to basically try and minimize the total

[150:18]

number of tokens generated as I

[150:20]

mentioned. So you could say something

[150:21]

like, hey, you know, write as succinctly

[150:22]

as possible. You can reason all that you

[150:24]

want because that isn't added to the

[150:25]

context. But when you actually give me

[150:27]

something, just give me the bare bones

[150:28]

information. If I need more, I'll

[150:29]

actually ask you. Choosing the right

[150:31]

model is really big. Um, so if you're

[150:33]

using a really simple sub agent or

[150:34]

something, we'll talk about how to

[150:36]

develop those later on. I recommend

[150:37]

using smaller models like sonnet. These

[150:39]

smaller models are typically less

[150:40]

intelligent, but they have much larger

[150:41]

context windows and then your build

[150:43]

less. So that allows you to like do all

[150:44]

the heavy lifting inside of the sub

[150:46]

agent that's cheaper and then they just

[150:47]

return you those results which is great.

[150:49]

As you see here um the anthropic team

[150:51]

specifies to reduce the MCP server

[150:53]

overhead and that's because as I

[150:55]

mentioned to you guys some MCP servers

[150:56]

just suck. They just have a bajillion

[150:58]

tools. You'll download one and 20% of

[151:00]

your token usage will be gone

[151:01]

immediately. That's obviously quite

[151:03]

costly and then it makes claude much

[151:04]

dumber. So you know there are ways to

[151:06]

reduce MCP server overhead. They have

[151:08]

what's called advanced and automatic

[151:09]

tool search. Now, uh, when MCP tool

[151:11]

descriptions exceed 10% of your context

[151:13]

window, they won't actually load all of

[151:14]

them. They'll just try and search for

[151:16]

them before. So, meaning you'll say,

[151:17]

"Hey, you know, can you open up a new

[151:19]

page in Chrome DevTools or something? It

[151:21]

won't actually have access to all that

[151:23]

immediately. What it'll do is it'll

[151:24]

search first a list of tools using Grap

[151:27]

or something like that, which is its own

[151:28]

built-in search tool, and then it'll

[151:30]

find one that says open Chrome DevTools,

[151:32]

and then it'll load it." That helps you

[151:33]

avoid, you know, massive MCP server

[151:35]

overheads and then obviously wasting a

[151:36]

lot of tokens. Some other tips are to

[151:38]

move instructions from claude MD to

[151:40]

skills. So remember how earlier I said

[151:42]

your claude.mmd should be like 200 to

[151:44]

like four or 500 tokens ma uh lines

[151:46]

maximum. Some people make it even

[151:47]

longer, but you shouldn't. Instead, what

[151:49]

you can do is you can break those down

[151:50]

into specific rules. Then any rules that

[151:52]

are more tasks than rules, you can

[151:54]

actually just turn into skills. So

[151:56]

skills will load on demand, meaning that

[151:57]

uh only when you specifically invoke

[151:59]

them will they be added to your context,

[152:00]

which is quite helpful. You can also

[152:02]

adjust uh extended thinking. We haven't

[152:04]

chatted too much about extended

[152:05]

thinking, but if you go back to claude

[152:07]

here, if you go to slash model, you have

[152:09]

the ability to switch which model you're

[152:11]

using. And then additionally, if you go

[152:13]

over here, there's also a thinking tab

[152:16]

which allows you to turn on and off that

[152:18]

little reasoning or or thinking window.

[152:20]

As mentioned, thinking is pretty

[152:21]

valuable because it avoids you wasting

[152:22]

tons of tokens in the conversation chain

[152:24]

itself. It offloads it to a little

[152:26]

thinking tab. Uh, and what you can do is

[152:28]

you can actually modify the effort level

[152:30]

using /model. You can disable thinking

[152:32]

completely or you can turn the number of

[152:34]

tokens that you give it to like maximum

[152:37]

think from I don't know 8,000 to like

[152:39]

32,000 or more. Now agent teams is

[152:42]

another feature of cloud code which I'm

[152:44]

looking forward to covering with you

[152:45]

guys. But currently it costs a lot about

[152:46]

seven times more tokens than standard

[152:48]

sessions especially when teammates run

[152:49]

in plan mode because every teammate

[152:51]

maintains its own context window. So

[152:53]

they actually kind of recommend against

[152:54]

it if minimizing token usage is the

[152:56]

number one thing that you want to do.

[152:57]

And then finally, um, you know, writing

[152:59]

specific prompts is probably the highest

[153:01]

ROI tip that I could give you here.

[153:02]

Instead of improve this codebase, you

[153:04]

know, you saying something specific,

[153:06]

hey, fix this one feature that I found

[153:08]

in this file, uh, is a lot more precise.

[153:10]

And as a result, you know, despite the

[153:11]

fact that it'll it takes a little bit

[153:13]

more thinking on your end, a little bit

[153:15]

more of your extended thinking. Um,

[153:17]

Claude's token usage ends up being

[153:18]

significantly decreased. Finally, even

[153:20]

Anthropic says that planning for complex

[153:22]

tasks is the way to go because this

[153:24]

significantly reduces the total number

[153:26]

of tokens you use um when you're

[153:27]

actually building solutions. Usually API

[153:29]

calls and calling servers and requesting

[153:31]

web pages and stuff. These load a ton of

[153:33]

tokens into context. So avoiding doing

[153:35]

research entirely is is pretty valuable.

[153:37]

Um once you're at the building stage,

[153:39]

just frontload the research with plan

[153:40]

and worry about it later. Now it's time

[153:42]

to chat skills, which in my opinion is

[153:44]

probably one of the most economically

[153:46]

valuable ways that you can use cloud

[153:47]

code. This is a claude code in aggregate

[153:50]

tutorial obviously. So I don't just want

[153:51]

to talk about skills. If you guys want

[153:53]

to know more about how I personally use

[153:54]

skills and things like skills, I do also

[153:56]

have another course that talks all about

[153:58]

what I call agentic workflows which are

[154:00]

analogous to skills. Um but for now

[154:02]

anybody that's not acquainted with this,

[154:04]

I just want to run a quick demo. So if

[154:05]

we open up thiscloud folder in the top

[154:07]

lefthand side, you can see that we also

[154:09]

have a nested skills folder. And I have

[154:11]

a bunch of different skills here. I have

[154:13]

skills that allow me to classify leads,

[154:16]

create proposals automatically, not

[154:18]

dissimilar to the proposal generator app

[154:20]

that we did before, find outliers in my

[154:23]

niche, um, update and autorely to

[154:25]

emails, edit my YouTube videos for me,

[154:28]

you know, onboard new clients to my

[154:30]

agency, apply to Upwork jobs and so on

[154:32]

and so forth, monitor and then classify

[154:35]

my school posts. I mean, if you think

[154:37]

about it, what this is is this is a

[154:38]

collection of all the things that I

[154:39]

usually do in a daily basis, like for my

[154:41]

own intellectually valuable knowledge

[154:43]

work, the stuff that I basically get

[154:44]

paid for. And then what I've done is

[154:46]

I've just turned them into um checklists

[154:48]

and then I've just given these

[154:49]

checklists over to Claude. So, let's

[154:52]

pretend that I want to do one of these

[154:53]

tasks today. Uh you know, in my case, I

[154:55]

want to scrape some leads. So, what I've

[154:57]

done is I've created a skill up here

[154:58]

called scrape leads that scrapes and

[155:00]

verifies business leads using a service.

[155:02]

Then it classifies with a large language

[155:04]

model, enriches the emails, and saves it

[155:05]

to a Google sheet. Use when the user

[155:07]

asks to find leads, scrape businesses,

[155:09]

generate prospect lists, or build lead

[155:10]

databases for any industry or location.

[155:12]

I then have a goal up top, which is

[155:14]

scrape leads using a particular source.

[155:16]

I have a bunch of inputs. I even have

[155:18]

some scripts that I could use to run

[155:19]

these. And then I have a process. And

[155:21]

this is my checklist. Start with a test

[155:22]

scrape, then do verification, then do a

[155:24]

full scrape, then do LLM classification,

[155:26]

upload to a Google sheet, enrich missing

[155:28]

emails, and so on and so on and so

[155:29]

forth. Okay. So, as you see here, big

[155:31]

big deal. This is a fair amount of time

[155:33]

and energy that, you know, I used to

[155:34]

take to do these lead scraping things as

[155:36]

part of my work is um both for my uh my

[155:39]

dental company and then for left click,

[155:41]

you know, for on behalf of my clients.

[155:43]

Lead scraping is like a major chunk of

[155:44]

what makes a successful cold email

[155:46]

campaign. And I just had to do it myself

[155:48]

every time. It would take an hour or

[155:49]

two. Well, what I can do now is I can

[155:51]

just turn all of my own knowledge into a

[155:53]

skill. Okay? I can define it in markdown

[155:55]

format here and you know I can write it

[155:56]

with cloud and then I can just say

[155:58]

scrape me 1k dentists or 1,000 dentists

[156:02]

in uh I don't know across the United

[156:04]

States. And when I press this button

[156:07]

what's happening now is it's

[156:09]

successfully loading the skill. It's

[156:11]

starting with a test scrape of 25

[156:13]

dentists to verify my quality. It

[156:15]

already, you know, automatically finds

[156:16]

the different filters I want to use and

[156:18]

and so on and so forth. And then it's

[156:20]

going to dump these into a little folder

[156:21]

for me. What it'll do after, according

[156:23]

to my skillspec, is it's going to read

[156:26]

through each of these 25 leads,

[156:28]

sometimes do a little bit of background

[156:29]

research to say, hey, are these the

[156:31]

sorts of leads that I'm actually, you

[156:32]

know, Nick is probably actually

[156:34]

interested on, and then if so, then it

[156:36]

proceeds with a full parallel scrape of

[156:38]

1,000 simultaneously. That occurs quite

[156:40]

quickly. So, in this case, it started

[156:42]

four of these scrapers, and it's just

[156:43]

uh, you know, parallelizing these. So,

[156:45]

I'm going to get 250 from each. To be

[156:46]

clear, previously this probably would

[156:48]

have taken me 15 or 20 minutes to set up

[156:49]

the filters, to set everything um you

[156:51]

know, kind of configure that initial

[156:53]

search, right? And then if I wanted to

[156:55]

do that search of 25, I would have had

[156:57]

to manually verify them myself, which

[156:58]

took me another 10 or 15 minutes. After

[157:00]

that, I would have started the actual

[157:02]

scraper. Then I would have had to like

[157:03]

upload them into a Google sheet. I would

[157:05]

have had to cross reference leads to

[157:07]

make sure they're good. I would have had

[157:08]

to run some additional AI based flows.

[157:10]

And it just would have been a big pain

[157:12]

in my ass. To make a long story short,

[157:13]

now AS capable of doing this for me in

[157:15]

just a couple of minutes. And I'm

[157:16]

running this in terminal because I have

[157:17]

access to what's called fast mode right

[157:19]

now. Essentially, Enthropic's new Opus

[157:21]

4.6 model has launched with the ability

[157:23]

to run two and a half times faster for

[157:25]

approximately three times the price. So,

[157:26]

I'm happy to pay a little bit more money

[157:28]

if it means that I can do all of the

[157:29]

knowledge work that I need to do a

[157:31]

little bit faster. As you see here on

[157:32]

the right hand side, it's now finding a

[157:33]

bunch of my leads for me. It's compiling

[157:35]

them into a list. uh 250 leads done from

[157:38]

that search, 250 leads done from that

[157:39]

search, 250 leads done from that search,

[157:41]

and we just have one more to go. And

[157:42]

what's really cool about skills is it

[157:44]

doesn't need to be right every single

[157:45]

time. It's not like a program. It's not

[157:47]

like I put something together and then

[157:48]

the second that it makes a mistake, it's

[157:50]

done. As you see here, it scraped about

[157:51]

1,000 leads in 87 seconds and now it's

[157:53]

uploading to Google Sheets. And

[157:55]

somewhere along the line, there was an

[157:56]

issue. And the issue was, it turns out

[157:58]

it can't use spaces and stuff like that

[158:00]

in the file. So what it did is it

[158:02]

realized that it made problem. Okay? and

[158:04]

then it uploaded to Google Sheets with

[158:06]

the proposed solution. It went through

[158:08]

and it read through a little bit of like

[158:09]

the API documentation and stuff like

[158:10]

that to do that. This is stuff that I

[158:12]

previously would have had to do and that

[158:13]

try and retry loop just takes forever.

[158:15]

On top of that, what it does is it goes

[158:16]

and enriches the emails for me. And then

[158:18]

what I end up with is I end up with a

[158:19]

list that looks something like this. So,

[158:21]

I just bold this and I make this a

[158:22]

little bit bigger. I've since hidden the

[158:24]

um email columns here just cuz I don't

[158:25]

want to, you know, um show too much

[158:27]

information. We have clinic phone

[158:28]

numbers and stuff like that. Company

[158:30]

phone numbers and addresses. But as you

[158:31]

can see here, we we have tons of

[158:33]

information about dentists that are

[158:35]

across the United States. Looks like a

[158:36]

big chunk of them are in Philadelphia,

[158:38]

New York, um Warstown, Boston, we have

[158:40]

cities. We have everything that we need.

[158:42]

And so what I'd do with this now is I

[158:43]

would take this, then I would send it

[158:44]

into a tool like instantly, which is my

[158:46]

cold email platform. And then I would

[158:47]

immediately start sending. And as I

[158:49]

mentioned, this takes a pre-existing

[158:50]

process that would have taken me at

[158:51]

least half an hour, probably more, and

[158:53]

it turns into one that I literally did

[158:54]

in 87 seconds. So as you can see skills

[158:57]

can be extremely economically valuable.

[158:58]

The question is how do you actually go

[159:00]

about creating them and creating them in

[159:01]

a way that I think is like reproducible

[159:03]

and efficient and so on and so forth.

[159:05]

Well the first thing is uh you need to

[159:06]

know how script or rather skill

[159:09]

structure works. If I just zoom in on

[159:10]

this to make it a lot easier. You can

[159:12]

see that our scrape leads skill is

[159:15]

broken up into a few components. First

[159:18]

we have the folder itself scrape-s. Then

[159:21]

we have another folder inside called

[159:22]

scripts. This runs the program aspect of

[159:25]

the skill. And then finally, we have the

[159:26]

actual skill.md in markdown. So I want

[159:29]

you to treat what we're seeing here in

[159:31]

the skill.md as basically like

[159:35]

the orchestrator of this whole affair.

[159:38]

So the skill.md

[159:42]

is like the checklist

[159:46]

or orchestrator.

[159:49]

You know, in an orchestra, the

[159:51]

orchestrator is the person with the

[159:53]

little I don't know, those sticks. My

[159:54]

sister does some of that, actually,

[159:55]

which is funny. I don't even know what

[159:56]

the hell they're called, but you know,

[159:57]

it's where you kind of wave them around

[159:58]

and do all that stuff. And then what

[160:00]

happens is, you know, the orchestrator

[160:02]

is not the person making, you know, the

[160:03]

conductor, I should say, is not the

[160:04]

person that's making the uh music. What

[160:06]

they're doing is they are orchestrating

[160:08]

the production of music from a variety

[160:10]

of other sources. Inside of scripts,

[160:15]

we have, you know, the actual musicians

[160:17]

themselves, violinists,

[160:20]

you know, the the chists, we have the

[160:22]

pianists and so on and so on and so

[160:25]

forth. And so basically what occurs is

[160:28]

we give it a big checklist of tasks in

[160:30]

the skill.md. We give it a bunch of

[160:32]

reference information and everything

[160:33]

that it needs. And we treat it just like

[160:34]

we treat a junior employee. We say,

[160:36]

"Okay, here's the checklist. Go and do

[160:38]

it." And then where the orchestration

[160:39]

kind of comes in is if there's an issue

[160:42]

with the step-by-step execution of

[160:44]

different subtasks, some of which are

[160:45]

going to be scripts and stuff like that,

[160:47]

then um Claude gets to use its own

[160:49]

native intelligence to fix it in real

[160:50]

time. Not only do they fix it, but then

[160:53]

it also goes in and it updates the skill

[160:54]

so that if there's another issue in the

[160:56]

future or if another instance of cloud

[160:58]

tries running this, it doesn't run into

[160:59]

the same problem. So, as you can see,

[161:01]

they're very, very valuable. They're

[161:02]

more or less exactly the same way that

[161:03]

like a person would go and do a task.

[161:06]

Now, inside of my scripts folder here, I

[161:07]

have, as you can see, a bunch of

[161:08]

different um, you know, actual Python

[161:10]

scripts that have been developed for

[161:11]

this purpose. Do I know anything that

[161:14]

goes on in here? No. I haven't even

[161:15]

looked at this code. This probably the

[161:16]

first time that I'm ever opening up this

[161:18]

file. What I did is I told Claude that I

[161:20]

wanted it to go and, you know, do things

[161:22]

in my checklist and then go create

[161:24]

scripts that would do them all for me.

[161:25]

It's much better to do this than just

[161:27]

tell Claude to do it from fresh and from

[161:29]

scratch every time because obviously if

[161:31]

it's the same thing you need to do every

[161:32]

time, you should like turn it into like

[161:34]

a defined program, right? because then

[161:35]

it's always going to execute similarly

[161:37]

that way. Claude is not actually doing

[161:39]

the executions um themselves. What it's

[161:41]

doing is it's just using the scripts

[161:43]

here just like it uses tools. You know

[161:44]

how it has access to bash and web search

[161:46]

and stuff like that. This is the same

[161:47]

idea. It's just we're doing it

[161:48]

encapsulated in a skill. Okay. So it

[161:51]

takes this information you know it goes

[161:53]

through the skill. It says okay step one

[161:55]

is test scrape. So I need to run this

[161:56]

scrape ampify with this query. Max items

[161:58]

25 whatever the heck that means. Then it

[162:00]

goes it executes this. Once it's done,

[162:03]

it checks the result. You know, if

[162:05]

that's the case, then it goes back and

[162:06]

then it runs the same scraper except

[162:08]

with different parameters. Assuming that

[162:10]

that's good, then it uses this classify

[162:12]

leads LLM script afterwards to, you

[162:14]

know, uh tabulate that information.

[162:16]

Assuming that that's good, it goes into

[162:18]

uh what looks like what looks like

[162:19]

update sheet to like create a Google

[162:21]

sheet and then send it. Assuming that

[162:23]

that's good, it then goes enriches the

[162:24]

missing emails and so on and so forth.

[162:26]

And there's different paths here based

[162:27]

off of um you know, how many people we

[162:30]

want to scrape. I have a few other

[162:31]

skills that I use pretty often as well.

[162:32]

This one's called lit literature

[162:34]

research. And so, you know, if I'm

[162:36]

trying to perform research on a task, I

[162:38]

will actually say go perform a lit

[162:41]

review on the recommended daily dose of

[162:44]

let's say vitamin D and IUD for males in

[162:49]

their early 30s. What this will do,

[162:52]

okay, in addition to reading the claw.

[162:54]

MD to get context about this whole thing

[162:56]

is it'll go through and it'll read this

[162:57]

literature research skill. If I open

[162:59]

this up so that we can all see um the

[163:02]

first thing it's going to do is it's

[163:03]

going to query like this database which

[163:04]

I'm suggesting that it queries. So this

[163:06]

database I think was called PubMed.

[163:09]

After that it's going to um analyze

[163:11]

using this little deep review script.

[163:13]

And you'll notice that you know if I

[163:14]

make this big again um you know it made

[163:16]

some mistakes here right for whatever

[163:17]

reason the first uh query did not

[163:19]

actually work fine but you know it ended

[163:21]

up redoing it over and over and over

[163:22]

again until it figured it out. And so

[163:24]

this is the orchestration aspect that

[163:25]

I'm talking about. You can give it a

[163:26]

checklist, but obviously not everything

[163:28]

goes right perfectly because not

[163:29]

everything goes right perfectly. You

[163:30]

need to give it some flexibility in

[163:32]

order to do your tasks. And that's what

[163:34]

it's doing right now, right? It's gone

[163:36]

through and it's uh you know gone and

[163:37]

created a bunch of literature review

[163:39]

based information for me. Why would I

[163:41]

use this versus let's just say telling

[163:42]

Claude to go find that information

[163:44]

because I've already just put in the um

[163:46]

you know infrastructure to query

[163:48]

specific databases that I really like.

[163:50]

I've uh taught it how to like run

[163:51]

parallel queries so I can do this

[163:53]

research in a tenth of the time. I've

[163:54]

taught it to use models that might be a

[163:56]

little bit less capable but might have

[163:58]

much longer context windows and so on

[163:59]

and so forth. And so this enables you to

[164:01]

find a workflow that works really really

[164:03]

well and then just consolidate it and

[164:04]

then do it the same every time. This is

[164:06]

why I no longer hire. I mean, you know,

[164:08]

my businesses collectively still make

[164:09]

over 300 something thousand per month

[164:11]

right now in profit. Um, that's a lot of

[164:13]

money. I don't have staff members to do

[164:16]

these things for me anymore. Anytime I

[164:18]

want anything done, I'll just tell

[164:20]

Claude to do it with one of these skills

[164:22]

because to be honest, it's the exact

[164:23]

same thing. Anyway, I would have just

[164:25]

hired a contractor to do this sort of

[164:26]

literature research. I would have hired

[164:28]

a contractor to do my lead scraping. Why

[164:30]

why do I have to wait around a whole day

[164:31]

or two for them now if I could just

[164:32]

execute a skill to go do the thing,

[164:34]

retrieve me the results, and then I

[164:36]

don't know, maybe feed it into another

[164:37]

skill in a hundredth of the time for

[164:39]

like a hundth of the cost. Okay, so

[164:40]

while all of this is occurring in this

[164:42]

tab and I'm doing that research, why

[164:43]

don't I show you guys how to actually

[164:44]

create a skill in practice? Um, to make

[164:46]

a skill, it's really straightforward.

[164:48]

You basically just give it like a

[164:49]

bulletoint list of things that you want

[164:50]

it to do. So, I'm going to say today

[164:52]

we're creating a skill. And why don't I

[164:54]

just use my voice transcript tool?

[164:55]

That's way easier. This skill will

[164:58]

design websites in a format that I

[165:00]

really like using a template that I

[165:02]

really like. I want the websites

[165:03]

designed very similarly every time

[165:04]

because I'm going to use them to pitch

[165:05]

people. In short, what I'm going to give

[165:08]

you is I'm going to give you a bunch of

[165:09]

information about a prospect and then I

[165:11]

want you to design a website using a

[165:13]

specific template. The template I'm

[165:14]

going to supply you is this one. And

[165:16]

then what I'm going to do is, you know

[165:17]

how earlier we went through godly. Then

[165:21]

we found a template that we really

[165:22]

liked. Well, I'm just going to scroll

[165:23]

through and I'm going to find a template

[165:25]

that I really like. So, scrolling

[165:26]

through um I don't know, I just want

[165:29]

this to be a simple website that I could

[165:30]

use for let's just do like I don't know,

[165:32]

dentists hypothetically right now. So,

[165:34]

I'm going to go over here and then I

[165:36]

like this build an Amsterdam one.

[165:40]

Okay. And then what I'm going to do is

[165:41]

I'm just going to I think that's it.

[165:42]

Honestly, I think I'm just going to

[165:43]

screenshot this and they'll just make

[165:45]

one pager for Claude. Just going to

[165:47]

screenshot it. Okay. And then I'm going

[165:49]

to go back to my anti-gravity and then

[165:51]

paste it. I want you to use screenshot

[165:53]

functionality to mirror the style of the

[165:55]

website. I'm also going to paste in some

[165:57]

of the HTML so you can use that to

[165:58]

create a style guide, etc. You'll

[166:00]

receive as input um like a Google sheet

[166:03]

with information about a prospect and

[166:05]

then you just create a website that

[166:07]

matches. Uh find web images using

[166:10]

publicly available sources. Make sure

[166:12]

it's really pretty and uh yeah, follow

[166:14]

the template as closely as possible.

[166:15]

Then I'm going to go on the website. I'm

[166:17]

going to let's just make it really wide

[166:18]

because sometimes websites are

[166:20]

different. Um

[166:22]

and then what I'm going to do is I think

[166:23]

I'm just going to copy all of this. It's

[166:26]

really really long, right? I'm just

[166:27]

going to paste it in. So that's going to

[166:29]

be huge. It's going to be a lot of stuff

[166:30]

to paste. 474 lines. And then hm.

[166:33]

Anything else that we need to do? I

[166:35]

don't think so. I guess I just need to

[166:37]

give it an example of some of the input.

[166:38]

So, I'm going to go and then find that

[166:40]

Google sheet that we just had with a

[166:41]

bunch of dentists. I'm just going to

[166:43]

copy all of this information. Then I'll

[166:45]

say example of the data and then I'll

[166:47]

paste that in. Okay. So, I mean, I just

[166:49]

fed in a tremendous amount of

[166:50]

information here, right? Like this is

[166:51]

really, really big. But with our little

[166:54]

fast mode, uh, plus,

[166:56]

you know, some pretty precise

[166:59]

instructions, I think we can probably

[167:00]

generate a cool skill in just a couple

[167:01]

of minutes that does this sort of thing

[167:02]

automatically. And after this, I'll have

[167:04]

a system where I can basically just feed

[167:06]

in a Google sheet and then I can

[167:07]

generate a beautiful customized website

[167:09]

for a prospect in like 2 seconds which

[167:10]

has information about them that clearly

[167:12]

is customized and so on and so forth.

[167:14]

Uh, and then I can just give it to them

[167:15]

as sort of a lead magnet or something.

[167:17]

That sounds pretty fun. And it's already

[167:18]

gone through and it's done some stuff.

[167:19]

Now, I'm not using plan mode for this,

[167:20]

but you absolutely can. I just wanted to

[167:22]

oneshot a skill with this fast mode just

[167:24]

so that I could uh do something while I

[167:25]

was waiting for the literature review to

[167:26]

finish. As you can see, it's loaded in

[167:28]

the skill pattern and structure from the

[167:30]

other skills as well as the claw.md. And

[167:33]

now it's just going to ask me some

[167:34]

information. So where should the output

[167:36]

of the skill be? A local HTML file.

[167:38]

Yeah, let's just use local HTML for now.

[167:40]

How will you provide prospect data?

[167:41]

We'll just do Google sheet URL. For

[167:43]

images, which approach do you recommend?

[167:45]

Yeah, sure. Let's do the Unsplash API.

[167:46]

Should the website be a mockup of what

[167:48]

their business site could like or pitch

[167:49]

page about your services? Mockup of

[167:50]

their site. Cool. That looks great. So

[167:53]

that's sort of its plan mode analogy.

[167:56]

And um this actually initiated plan mode

[167:57]

without me even having to ask.

[167:58]

Basically, if I just make this a little

[168:00]

bigger so you could see the entire chat.

[168:02]

This went through and then turned on

[168:04]

plan mode like on its own. I didn't even

[168:05]

have to ask it to. And that's what

[168:06]

occurs sometimes when you do bypass

[168:08]

permissions. It'll just chase choose to

[168:09]

create a plan for a more complicated

[168:11]

software build. Cool. And now I'm going

[168:12]

to bypass permissions and we're going to

[168:14]

go. While that's occurring, just

[168:15]

scrolling through this literature

[168:16]

review. Looks pretty cool. Gives me a

[168:18]

bunch of information. Apparently 1 to

[168:19]

2,000. So that looks pretty fun. Okay.

[168:21]

And then this looks like the little demo

[168:23]

that we put together. This is a pretty

[168:25]

basic demo. Not that big of a fan to be

[168:26]

honest. So, I think we're going to have

[168:28]

to go do some back and forth. Still, we

[168:30]

did build a website in just a few

[168:31]

seconds for them, which is kind of neat.

[168:32]

Okay, it's now going to take a

[168:33]

screenshot of this page for us. And as

[168:35]

you can see, it's now accumulated like

[168:37]

19 or 20,000 tokens, which is kind of

[168:39]

cool. Um, here's what we got. Full

[168:41]

viewport hero. Okay, so I'm just going

[168:43]

to say not a very big fan of the website

[168:45]

design. I don't think this matches the

[168:47]

website. I'd like you to get pixel

[168:49]

perfect accuracy by screenshotting um

[168:52]

the comparison back and forth. go find

[168:54]

some library that allows you to do this

[168:56]

as necessary. In terms of Unsplash, how

[168:59]

are you currently getting your images?

[169:00]

Let's just do that. That's fine. I don't

[169:02]

really want it to go, you know, force me

[169:03]

to get an API key or something like

[169:04]

that. I'm just going to have it run.

[169:05]

Okay, that's looking a lot better than

[169:07]

what we had before. I like this. Uh,

[169:09]

looks like it took some photos of areas

[169:11]

that were similar to where this place is

[169:13]

located. Then, as we scroll through, we

[169:15]

obviously have the the information and

[169:16]

the template and stuff. I don't like how

[169:18]

a lot of these images are the same, so

[169:19]

I'm just going to say nice job. I don't

[169:21]

like how all these images are the same,

[169:22]

though. get different images. Looks

[169:24]

really clean. Uh we even have like their

[169:25]

phone numbers and stuff like that. So

[169:27]

we're now capable of basically like

[169:28]

oneshotting a website for somebody. And

[169:31]

uh as you can see, we can generate these

[169:33]

super super easily and very quickly.

[169:35]

What I'll do now that we have this is

[169:36]

realistically I'm going to try it with

[169:38]

one row and then just see how quickly it

[169:39]

can put together the site for me. Cool.

[169:41]

Now I'm going to test it with some new

[169:43]

information and let's see how quickly it

[169:45]

can put that together. Cool. We've now

[169:46]

done the same thing with Ben Bennington

[169:48]

Dental Center. So that's neat. We have

[169:50]

some images generated and stuff like

[169:51]

that. Um, it is telling me that the

[169:53]

reason why we have images of dogs and

[169:55]

stuff is cuz I don't want to supply my

[169:56]

Unsplash API key. Uh, you know, if we do

[169:59]

then obviously they'll be much more

[170:00]

dentally oriented. I think that's fine.

[170:02]

Hopefully you guys get the idea. You

[170:03]

could build stuff like this really

[170:04]

quickly. In this case took 30 seconds.

[170:06]

Um, so I mean like what we could do if

[170:08]

we wanted to like build this out as a

[170:09]

service and like actually just like

[170:10]

generate custom websites for people,

[170:12]

send them out and so on and so forth.

[170:14]

Uh, we could turn the skill into a sub

[170:16]

agent. show you guys how to do later

[170:18]

where basically we can spin up 10 of

[170:19]

these simultaneously and basically in

[170:21]

parallel just generate 10 every 30

[170:23]

seconds. That's a per website generation

[170:24]

time of about 3 seconds. And so now that

[170:26]

we're generating them every 3 seconds

[170:28]

with customized information, matching

[170:29]

widths and heights and stuff like that,

[170:30]

making it really custom and sexy.

[170:32]

[gasps] You know, you could do 10,000

[170:34]

leads in approximately 30,000 seconds. I

[170:36]

don't know how long that would actually

[170:37]

take. Let's see. 30,000 divided by 60 is

[170:41]

500. So it might take 500 minutes or I

[170:44]

don't know, 8 hours for a full 10,000

[170:46]

list. But uh yeah, combine that with the

[170:47]

scraper, combine that with you sending

[170:48]

people customized websites, and combine

[170:50]

that with some other skills that I've

[170:51]

set up to like automate the process of

[170:52]

whipping up instantly campaigns and

[170:53]

stuff. And hopefully you guys can see we

[170:55]

get a pretty solid system in our hands

[170:57]

and that took me just a few minutes to

[170:58]

put together. Now that we know all about

[170:59]

skills, let's talk a little bit about

[171:01]

the next logical thing, which is model

[171:03]

context protocol. So now that you guys

[171:05]

understand sort of how skills work,

[171:06]

which to be clear um is that skills are

[171:09]

basically like backend functions that

[171:11]

you can run, scripts almost that use the

[171:15]

flexible intelligence of AI and the

[171:17]

procedural rigor of Python scripts and

[171:20]

other programming tools to do the same

[171:22]

thing every time but also allow you the

[171:24]

flexibility to air handle. So now that

[171:26]

we understand that um let's chat about

[171:29]

model context protocol. And so the way

[171:31]

that I see it is these are just skills

[171:33]

except other people make the skills for

[171:35]

you. And when I say other people, for

[171:36]

the most part, it's like developer teams

[171:37]

and stuff like that. Very similar idea.

[171:40]

You're basically just giving your agent

[171:42]

access to a piece of software and then

[171:44]

just like it calls its own tools like

[171:46]

web search and bash and the Chrome

[171:47]

DevTools MCP and the screenshot, all the

[171:49]

stuff that we've already looked at. Uh

[171:51]

what we're doing here is we're just um

[171:52]

you know, we're just calling them uh but

[171:56]

somebody else is responsible for putting

[171:57]

them together. Now that obviously begs

[171:59]

the question, where do I get um you know

[172:01]

MCPs? Well, you can just go on websites

[172:04]

like mcpservers.org

[172:07]

modelcontext protocol/servers

[172:09]

and then MCP market. I want you guys to

[172:12]

know that not all of these are going to

[172:14]

be 100% safe or secure. These are third

[172:16]

party libraries that people are putting

[172:18]

together basically that try and tabulate

[172:20]

the number one MCP skills and so uh MCP

[172:23]

tools and so on and so forth. Um, but a

[172:25]

lot of these are pretty well vetted at

[172:27]

this point and I'm going to show you at

[172:28]

least a couple that I really like. The

[172:30]

biggest one is probably the Chrome Dev

[172:31]

Tools MCP. This is one that I use

[172:34]

constantly, uh, basically every day,

[172:35]

many, many times, because it allows your

[172:37]

coding agent to control and then inspect

[172:39]

a live Chrome browser. In my opinion, it

[172:42]

is significantly higher quality than any

[172:44]

of the current browser tools that um,

[172:46]

you know, Claude or other platforms have

[172:48]

given us. So I mean like you know I have

[172:50]

this little Chrome extension here that

[172:52]

um I can actually use to control this

[172:54]

instance of Chrome through this cloud

[172:56]

tool. It's developed specifically by the

[172:58]

cloud team and I could say hey um

[173:00]

summarize this page and then what it can

[173:03]

do is it can copy all the text on this

[173:05]

page. So it can extract the page text

[173:07]

and then it can take a screenshot of it

[173:09]

and then it can you know tell me about

[173:11]

it and so on and so forth. I can also

[173:13]

have it do things like click. I could

[173:14]

say okay um you know star this on GitHub

[173:19]

or something like that and then I can

[173:22]

give it some additional instructions and

[173:23]

then it can go through look for the

[173:25]

GitHub link I don't know maybe click it

[173:28]

and then now that you know we have this

[173:29]

thing open it's going to go and it's

[173:30]

going to try and star this puppy so

[173:32]

that's pretty cool but you'll find that

[173:34]

it also takes a fair amount of time and

[173:36]

the Chrome DevTools MCP bypasses that

[173:38]

completely and it's like 100 times

[173:40]

faster and not only is it 100 times

[173:41]

faster because you can weave it into

[173:43]

skillbased scenarios, you can actually

[173:45]

just run um really really procedural

[173:47]

things in the browser that previously

[173:49]

would have taken you like a fair amount

[173:50]

of time to automate. So I mean I already

[173:51]

have access to this right now, but um

[173:53]

for the purpose of this demonstration,

[173:55]

let me just open up a new claude

[173:56]

instance in my terminal and then double

[173:58]

check that fast mode is on. Okay, it

[173:59]

looks like it is. Um you know, all I

[174:01]

would really do if I wanted to download

[174:03]

the MCP for any tool really now is I

[174:06]

would just paste in this definition

[174:09]

which you can find right over here.

[174:10]

Okay, basically all MCP tools are going

[174:14]

to have some sort of JSON that looks

[174:15]

like this where there's a curly bracket,

[174:17]

it says MCP servers, it'll say the

[174:19]

server name. There's a bunch of commands

[174:20]

in args which really don't matter

[174:21]

whatsoever, but basically you just go on

[174:23]

whatever page um of the MCP supplies

[174:26]

this information. You copy this in. So

[174:28]

if you want to install one, all you

[174:30]

really do is you just paste in that

[174:31]

little, you know, JSON snippet that we

[174:33]

saw earlier and we say I want to install

[174:36]

this in my local workspace. It's

[174:40]

important that you say local workspace

[174:41]

here. What it's going to do is just

[174:42]

going to grab that data and then install

[174:44]

it for you. In my case, it's already

[174:46]

installed. Um, so I don't actually need

[174:48]

to change anything, but now I'll say

[174:49]

great, run it. Now, sometimes when

[174:52]

you're using a tool that requires

[174:53]

authentication, um, what it'll do is

[174:56]

it'll force you to go and grab an API

[174:58]

key or an API token or something like

[175:00]

that. So, I'm going to show you guys an

[175:01]

example of using a tool that requires

[175:03]

some API credentials in a second. First,

[175:05]

let's just say, okay, open and navigate

[175:08]

to leftclick AI, then screenshot the

[175:12]

site and tell me about it visually.

[175:15]

So, what it's going to do is it's going

[175:16]

to open up that browser, going to

[175:18]

navigate to leftclick.ai. Now, it's

[175:20]

going to take a screenshot, which I

[175:21]

think it just did. Now, it's going to

[175:22]

read the screenshot, and then it's going

[175:24]

to, I don't know, give me some highle

[175:26]

stuff about the website. So you know

[175:28]

this the header is a simple navbar with

[175:29]

a leftclick logo case studies about

[175:32]

links and a let's talk CTA button hero

[175:34]

sections large bold serif right okay

[175:37]

great go to amazon.ca A and find me a

[175:40]

bunch of cheap but effective light boxes

[175:44]

for my studio. So now I'm going to open

[175:46]

this up. It's going to do the same thing

[175:48]

with Amazon. I'm in Canada, hence theca.

[175:50]

And it's going to start, you know,

[175:52]

pumping in various search terms for

[175:54]

light boxes and whatnot. I don't know

[175:56]

why twilight is recommended to me.

[175:59]

Must say something about my browsing

[176:00]

history. Now it's going through finding

[176:03]

a bunch of light boxes and stuff like

[176:05]

that. It's going to take screenshots of

[176:06]

the page and then uh you know deliver me

[176:08]

a bunch of options that I could choose

[176:10]

from. And you can see all this occur

[176:11]

underneath the tool call. So these

[176:14]

little green boxes are little green

[176:16]

circles I should say are tool calls.

[176:17]

They have the specific name of the um

[176:20]

MCP over here. And then they have the

[176:21]

tool that they're calling from the MCP

[176:23]

over here as well. And what they're

[176:24]

doing here is now that it's taking a

[176:26]

screenshot and stuff like that. It's

[176:27]

giving me summaries of all the

[176:28]

information and it's even recommending a

[176:30]

certain one. Now, a lot of the time you

[176:31]

can also just type in um the name of the

[176:34]

tool you want and then the word MCP

[176:36]

server. And a lot of these tools will

[176:38]

actually have gone through and created

[176:39]

this stuff. That'll take me to the

[176:41]

ClickUp page with MCP server setup

[176:42]

instructions. And then what I'm going to

[176:44]

do is I'm just going to copy over this

[176:45]

stuff just like I did before. Okay. And

[176:47]

then we're going to go back to my agent.

[176:48]

So, I'm going to do is I'll just go

[176:49]

install this MCP. I'm going to paste

[176:51]

this in. This includes all of the

[176:54]

details and documentation here. So,

[176:56]

first thing it's going to do is look for

[176:57]

some sort of configuration file that's

[176:59]

pre-existing. It's not going to find

[177:00]

one. So, it's going to go and then just

[177:01]

make mine. Then eventually what it's

[177:03]

going to ask me to do is go grab my API

[177:05]

key. So, I'll head over here to ClickUp

[177:06]

API and then I'm just going to copy my

[177:08]

API token and then confirm it. And then

[177:11]

I can copy my token in. And then I'll go

[177:12]

back here. Then I'll say great, here's

[177:15]

my API details.

[177:18]

Going to feed that in. And then every

[177:19]

time you install a new MCP server, you

[177:21]

do have to open up a new thing. So

[177:23]

that's what I just did here. It's going

[177:24]

to ask me which workspace I want to

[177:25]

connect to. I have multiple. So I'll

[177:26]

click connect workspace here. Then I can

[177:28]

just go back and then I'll say great do

[177:32]

you have access to my ClickUp MCP.

[177:38]

I'll say awesome create a new content

[177:41]

idea called um Claude Code course. Now

[177:45]

what it's going to do is scroll through

[177:46]

all of my lists. It's then going to

[177:49]

search for various ones that I may or

[177:50]

may not have. So I have lists called um

[177:54]

like content ideas and trends and stuff

[177:55]

like that. and I'm going to ask it to

[177:57]

insert it in my main YouTube queue. So,

[177:59]

I'm going to do that. And now you can

[178:00]

see there's a task called um claude code

[178:02]

course. If I go back here to my ClickUp,

[178:05]

open up the specific task, there's now a

[178:08]

course that's basically been created. I

[178:09]

don't like how the status is archived.

[178:10]

So, I'm going to say the status is

[178:12]

archived right now. And as you see here,

[178:14]

you know, it's now set to to record. So,

[178:15]

that's pretty neat. The last thing I

[178:16]

want to talk about now is if we go

[178:19]

slashcontext and scroll all the way up,

[178:21]

you start to get an appreciation for

[178:23]

just how many tokens can get used up by

[178:26]

poorly drawn or poorly written MCPs. And

[178:29]

so in this case, I'm not saying the

[178:30]

ClickUp MCP is really that bad. It's not

[178:32]

terrible. I've seen many, many far worse

[178:34]

ones, but it does consume a hell of a

[178:36]

lot of tokens. As you see here, just the

[178:37]

ClickUp search um tool consumes 1,600.

[178:41]

The Get Workspace hierarchy is 419. This

[178:43]

one's 1.1K. If we added all of them up

[178:46]

together, as you could see, my MCP

[178:48]

tooling is now taking up almost 20,000

[178:51]

tokens. That's actually now more than

[178:53]

the system tools, which uh previously

[178:55]

used to be really, really big. And what

[178:56]

that means is right off the very get-go,

[178:58]

basically like right at the very

[178:59]

beginning. Uh we are already at

[179:02]

something like 35,000 tokens or so

[179:05]

before I enter my prompt, before I enter

[179:07]

anything. If you take into account the

[179:09]

system prompt as well, we're now at

[179:11]

40,000. you take into account some

[179:12]

memory files and my skills, you know,

[179:14]

are not closer to 45. And this is all

[179:16]

before I've sent a message, right? Keep

[179:18]

in mind that like 45% is, I don't know,

[179:21]

let's just say 45 over 200. That's about

[179:24]

equivalent to a quarter. And so one

[179:27]

quarter of all my contexts. And by the

[179:28]

way, this is the highest quality section

[179:31]

of my prompt.

[179:33]

Like if I were to write actual messages

[179:35]

here, this would be the the highest

[179:37]

quality output. Basically, the highest

[179:38]

ROI section is currently being taken up

[179:40]

by a ton of MCP tools and stuff. Uh, in

[179:42]

addition, you'll compare this to skills

[179:45]

and you'll see that um, scrape leads

[179:46]

only takes up 63 tokens. School monitor

[179:49]

takes up 59, right? Cross niche outliers

[179:51]

takes up 58. So, it's like, oh wow, you

[179:54]

know, a single one of these MCP uh,

[179:56]

tools like update task consumes more

[179:58]

than basically all of my skills

[179:59]

combined. It's kind of like, why the

[180:01]

hell would I even use MCP tooling if I

[180:03]

can just, you know, do a skill instead?

[180:05]

The reason really is just the

[180:06]

convenience of it. MCP, as you see, is

[180:07]

pretty easy to set up. Whereas skills,

[180:09]

as you saw, take a little bit longer.

[180:10]

That skill back there that does those

[180:12]

website designs. Um, that took me, I

[180:13]

don't know, probably like 5 minutes end

[180:14]

to end to create. Once I've created,

[180:16]

it's obviously super efficient and so on

[180:17]

and so forth. But, um, you know, the

[180:19]

ClickUp MCP, all I really had to do is

[180:21]

just like log in and then give it uh,

[180:22]

one line and then and then I did that.

[180:24]

So, basically, the way that I personally

[180:26]

use MCPS is I use them aside from the

[180:27]

Chrome Dev Tools MCP cuz I just think

[180:29]

that's fire. I use it all the time. I

[180:30]

use them to um, very quickly sketch out

[180:32]

whether or not something's possible.

[180:33]

I'll basically go to a new tool that I

[180:35]

want to see if I can integrate and I'll

[180:36]

just say, "Hey, you know, here's the MCP

[180:38]

details. Can we do X, Y, and Z?" And

[180:39]

then if it can do XYZ the first time,

[180:40]

then I'll say, "Okay, this is great. I

[180:42]

want you to take what you just did. I

[180:43]

want you to convert it to a skill

[180:44]

instead and I want you to go and find

[180:46]

like the the API endpoints and stuff and

[180:48]

then build a script that does all that

[180:49]

for me instead of me having to use this

[180:51]

super bloated um MCP tool." By the way,

[180:53]

if you ever wondered why skills consume

[180:55]

so few tokens relative to everything

[180:57]

else, that's because the whole skill is

[180:59]

not actually um loaded into context. If

[181:02]

we go to the scrape lead skill, the only

[181:04]

section here that's actually loaded into

[181:05]

context is this section right up here.

[181:07]

And this in markdown format is referred

[181:10]

to as the front matter of the file. And

[181:13]

so what's really cool is the Claude code

[181:16]

developers realized that they could um

[181:18]

load in a name and description and then

[181:21]

some allowed tools to the front matter

[181:22]

and then only feed that into context.

[181:25]

And then only if Claude really thinks

[181:26]

that it needs to use this. If I

[181:27]

specifically say, hey, use the scrape

[181:29]

leads file, then and only then will it

[181:30]

actually load at all. which means I get

[181:32]

most of the benefits of having access to

[181:33]

a bunch of tools and you know giving my

[181:36]

agent the ability to do a bunch of

[181:37]

things but I don't have to like load all

[181:39]

that into context immediately which

[181:40]

means I get better decision-m at the

[181:42]

beginning because performance in prompts

[181:44]

are typically the best at the very

[181:45]

beginning of said prompt of the context

[181:47]

window I should say and then I also

[181:49]

don't have to pay a lot of money for it.

[181:50]

So just another point towards anthropic

[181:53]

minimizing our total costs which I think

[181:54]

I'd very much appreciate. So just

[181:56]

because this is a practical course I'm

[181:57]

actually going to show an example of

[181:58]

this. I'm going to draft out a task and

[182:00]

then going to try it with an MCP server

[182:02]

which is going to be a tenth of the time

[182:03]

to implement and then if it works I'm

[182:04]

going to build a skill to do it instead.

[182:06]

What I want to do today sort of like my

[182:08]

task is I want to label

[182:12]

my emails. So what I'm going to do if

[182:14]

you think about it the task is really

[182:16]

I'm going to list last I don't know X

[182:20]

emails.

[182:22]

Uh, I'm gonna have Claude read them.

[182:26]

And then I'll also have it label

[182:28]

according to some

[182:31]

se scheme, you know, that I put

[182:33]

together. And in this way, I'm not going

[182:35]

to replace the job of an email manager,

[182:37]

but I'm going to make the job of an

[182:38]

email manager much easier. And if later

[182:40]

on I want Claude to, I don't know,

[182:41]

manage my emails or whatever, well, now

[182:42]

it'll have some pre-existing labels and

[182:44]

organized structures for it. So, first

[182:45]

thing I'm going to do is I'm going to go

[182:46]

back to Claude. Let's go to

[182:48]

anti-gravity.

[182:50]

I'm going to do this in the GUI this

[182:51]

time, not the um other mechanism, not

[182:53]

the terminal, because I don't think fast

[182:55]

mode's super important for this. And I'm

[182:57]

just going to say, "Hey, I want to

[182:58]

organize my personal mailbox. Could you

[183:00]

provide me a list of high ROI labels

[183:02]

that tend to work well for personal

[183:04]

mailboxes?"

[183:06]

Just make sure the thinking tab is on

[183:07]

cuz I want it to really think hard. And

[183:09]

then what I'm going to do is I'm going

[183:10]

to go to one of my personal mailboxes

[183:12]

and then uh I'm going to basically

[183:14]

implement this. I really like

[183:15]

actionbased. That sounds great. Keep

[183:17]

that for now. And then I'm going to open

[183:18]

up one of my mailboxes here. We have

[183:20]

tons of different um emails. Most of

[183:22]

these are spam to be honest or little

[183:24]

demos that I put together for um you

[183:26]

know, whatever purpose. I'm also part of

[183:28]

what looks to be like a Slack workspace

[183:30]

um for one of my businesses. I think I

[183:31]

just did that cuz I wanted to test what

[183:32]

this looked like. Now that that's done,

[183:34]

what I'm going to do is I'm going to see

[183:35]

how I can implement the Gmail MCP really

[183:37]

quickly. Great. This looks solid. How do

[183:39]

I use the Gmail MCP? It's now going to

[183:42]

go and search for Gmail MCP first in my

[183:44]

folders. Um,

[183:47]

and then it'll ask me what it wants me

[183:49]

to do. I want to set one up. So, it's

[183:51]

going to start doing some searches for

[183:52]

Gmail MCP servers. I'm also going to do

[183:54]

some searching myself. There probably

[183:56]

three or four different ones that

[183:58]

realistically work. Um, this looks to be

[184:00]

a pretty interesting repo. So, what I

[184:01]

could do is I could just use this puppy.

[184:03]

That looks nice. I just paste this in.

[184:04]

It looks like I actually beat Claude to

[184:07]

something for once. Now, it's going to

[184:09]

compare.

[184:10]

Great. Let's do it. It's a personal

[184:14]

Gmail. Is that okay? Okay, it's now

[184:15]

going to walk me through. So, I'm going

[184:17]

to give this button a click. Okay, I

[184:18]

went through and I got that data. I'm

[184:20]

now going to paste this in. It's going

[184:22]

to go find the credentials file that I

[184:23]

just uploaded. Now, it can do what it

[184:26]

needs to do. I just need to restart the

[184:27]

cloud code session. So, I'm just going

[184:29]

to open up a new one here. Then, I'll go

[184:32]

back and then I'll say,

[184:34]

"Hey, I want you to label my emails."

[184:37]

Oh, you know, and I don't actually

[184:38]

remember what was that scheme that it

[184:39]

asked. Hey, I want you to label my

[184:41]

emails according to this scheme. So now

[184:43]

it's going to call the Gmail MCP. Okay.

[184:45]

It's going to check the Gmail MCP tools.

[184:48]

Just figured it out. We have a bunch of

[184:49]

pre-existing labels. So it's just going

[184:51]

to create a bunch on its own. The reason

[184:52]

why this is occurring so quickly is

[184:54]

because I'm using their um fast mode. So

[184:56]

it's about two and a half times faster

[184:57]

than usual. It's now reading through a

[184:59]

bunch of emails. And now it's going to

[185:00]

in addition to thinking through them, um

[185:02]

go through and then do set labeling. And

[185:05]

then you know it's just going to

[185:06]

continue doing this for as many emails

[185:07]

as I say. So I think I said that I was

[185:09]

going to do I don't know 15 emails or

[185:11]

something like that. This just did 10.

[185:13]

So, it's 15 inbox emails. Looks great.

[185:16]

Why don't we do this for 100 emails in

[185:17]

total?

[185:20]

Now, if I go back into my email, uh,

[185:23]

which I think was over here, you can see

[185:25]

that I now have different labels. Just

[185:27]

got to refresh that. There's action

[185:28]

required or reference and waiting on.

[185:30]

So, you know, if something requires my

[185:32]

action, some security alerts and stuff

[185:34]

like that, then that's one thing. If

[185:35]

it's a reference, so this is just stuff

[185:36]

that it's storing that, you know, may be

[185:38]

useful for me. And then there's waiting

[185:39]

on down here. So, now that you know I've

[185:41]

demonstrated that I could do this sort

[185:42]

of thing pretty quickly with a setup

[185:44]

that realistically only took me a few

[185:46]

minutes, I want to turn this into a

[185:47]

skill. So, I'm actually going to pause

[185:48]

this and I'll say, "Great, this worked

[185:50]

really well. I'd like to turn this into

[185:52]

a skill called Gmail label." Basically,

[185:54]

what I want you to do is just to call

[185:56]

the Gmail uh API directly and then do

[185:58]

all this labeling for me uh instead of

[186:00]

me having to use MCP because skills are

[186:03]

just a lot more token efficient than

[186:04]

MCPs. Check out my other skills so you

[186:06]

could see an example of how to format

[186:08]

them and so on and so forth. And then

[186:09]

write me a skill that effectively does

[186:11]

this as well as uh uses Gmail scripts.

[186:13]

Feed that puppy in and then press enter.

[186:15]

Now I have some other skills that you

[186:17]

know might have something to do with

[186:18]

Gmail. So if it finds them, then it'll

[186:20]

probably just want to use those. Okay,

[186:21]

cool. Looks like it's rebuilding it all,

[186:22]

which is fantastic. Um, we're going to

[186:24]

do the Gmail label skill directory. So

[186:28]

it's going to pump in somewhere right

[186:29]

around here. Looks like I'm running into

[186:30]

some error here. So we're going to have

[186:32]

to do some debugging. Just going to

[186:33]

paste this in directly. Okay. And it

[186:35]

looks like we're just about to wrap this

[186:36]

up. So now I'm going to select say that

[186:39]

it can see edit my email labels and so

[186:41]

on and so forth. Um now that it's done,

[186:43]

the authentication flow has completed. I

[186:45]

may close this window. Going back over

[186:47]

here. Now it is created with full Gmail

[186:49]

sheets and drive access which allow me

[186:51]

to do this much faster. So you guys

[186:53]

seeing just how much quicker this is.

[186:54]

100 emails immediately fetched. It's now

[186:56]

reading and classifying all of them

[186:57]

using direct API calls instead of MCP

[186:59]

server tools. And then in addition, you

[187:01]

know, as I showed you guys earlier, we

[187:04]

go to Gmail label. The only thing that's

[187:06]

currently being loaded is this. And this

[187:08]

is so much shorter than like the whole

[187:09]

MCP skill stuff. So it fetched all 100.

[187:12]

It's now categorizing them into five and

[187:15]

95. So it looks like zero is waiting on

[187:17]

95 are reference, and then five are

[187:18]

action required. That was way faster

[187:20]

than what we were doing previously,

[187:21]

right? That would have taken probably

[187:22]

like 5 to 10x the time. Looks great. Why

[187:24]

don't we do another 100 and then time

[187:25]

yourselves? Tell me how long it took.

[187:27]

Okay, it's now going to grab all of

[187:28]

these. So, it's just going to continue

[187:31]

the filtering process by, you know,

[187:32]

using some Gmail stuff. Then, it's also

[187:34]

going to add some timing

[187:35]

instrumentation. That's kind of cool,

[187:36]

just because I'm curious. Fetch was 1

[187:38]

second. So, we fetched 100 emails in 1

[187:40]

second compared to previously where it

[187:42]

took significantly longer cuz I think

[187:43]

the MCP tooling had like some built-in

[187:45]

thing. Cool. The end result was it was

[187:47]

36 seconds to fetch, classify, and label

[187:49]

100 emails. About 3.6 seconds per email.

[187:52]

Sorry, 36 seconds per email if you think

[187:54]

about it that way. [gasps] Then, it also

[187:56]

gave me some um you know, breakdowns and

[187:57]

stuff like that of what it is. I could

[187:58]

run this across like my several thousand

[188:00]

outstanding emails if I wanted to. I

[188:02]

could also do things like have it

[188:03]

automated automatically generate replies

[188:05]

to each email. Um, you know, we could

[188:07]

build a sub agent, which I'll show you

[188:08]

guys how to do stuff like that in a

[188:10]

moment where we, you know, split each

[188:11]

into a parallel tasks and so on and so

[188:13]

forth. Sky's is really the limit here.

[188:15]

Okay, next up, I want to chat a tiny bit

[188:17]

about Cloud Code plugins. I personally

[188:19]

don't use plugins a ton, but uh they are

[188:21]

out there and so it's fair if I'm

[188:23]

building a masterclass course all about

[188:24]

Cloud Code, might as well know what the

[188:26]

heck these are. Simplest and easiest way

[188:28]

to access plugins is just go customize

[188:29]

and manage plugins. It'll show you the

[188:31]

plugins that you currently have

[188:32]

installed. You see the only one that I

[188:34]

have installed so far is called

[188:35]

claude-me atthe.mac. Um this is

[188:38]

basically a simple straightforward um uh

[188:41]

plugin that basically just adds all of

[188:42]

the messages that sent any cloud

[188:44]

instance to some memory file and then

[188:46]

claude can run searches over it if I say

[188:47]

hey what did I ask you about 2 weeks

[188:49]

ago? So you know it's marginally useful.

[188:51]

You then have access directly from cloud

[188:53]

to a bunch of other ones that are

[188:54]

somewhat useful. Um, they have like

[188:56]

front-end design for instance, which is

[188:57]

kind of cool. So, this is Anthropic's

[188:59]

own library, which improves the quality,

[189:01]

at least they say it improves the

[189:03]

quality of a front-end work. You can

[189:05]

build sexier and cleaner designs and

[189:07]

stuff like that. Um, you know, I don't

[189:09]

know. It's kind of 50/50. They say like

[189:10]

if you're doing stuff without the

[189:12]

aesthetics prompt, it looks like this.

[189:13]

And then if you're doing it with the

[189:14]

aesthetics prompt, it looks like that.

[189:16]

Personally, I think both of these look

[189:17]

pretty bad. This one definitely looks

[189:18]

better, of course, but it's not like

[189:19]

that much better. Uh, same thing over

[189:21]

here. So, I don't know if the guys that

[189:22]

made this just weren't like actually

[189:24]

crazy front-end devs or anything like

[189:26]

that, but I I personally think my

[189:27]

workflow of just going to one of these

[189:29]

websites and then copying the uh

[189:31]

screenshot over and then moving

[189:32]

everything into Clockout is like way

[189:34]

higher quality. But there are other cool

[189:35]

ones here. Context 7 is pretty nice.

[189:36]

Context 7 basically just allows you to

[189:38]

search through any API doc without um

[189:40]

really having to like know anything

[189:42]

about the API docs themselves. you know,

[189:44]

if you're working with like three or

[189:46]

four different tools, you just install

[189:47]

this as a plugin and then it'll

[189:49]

automatically um shrink and then

[189:51]

compress API documentation from the

[189:53]

sources over to cloud and then it can

[189:55]

read it in a very token efficient manner

[189:56]

and do cool things with. None of these

[189:58]

things I want to say are required.

[189:59]

Vanilla cloud code does really really

[190:00]

well without any sort of extensions or

[190:02]

plugins at the moment. Um but you know,

[190:04]

just worth us chatting briefly about

[190:06]

that. And then there are two major

[190:08]

marketplaces right now that are sort of

[190:09]

uh well sorry one major marketplace

[190:11]

right now that's supported by claude.

[190:12]

this Cloud Code plugins directory which

[190:14]

is in the cloud-plugins-official

[190:17]

repository. Um, you can find all of the

[190:19]

plugins just by going to plugins and

[190:20]

you'll see there's a big list of ones

[190:21]

that they support right out of the box.

[190:23]

So, they have agent SDK dev, they have

[190:25]

code review, they have C# LSP example

[190:28]

plugin, but then there are also open

[190:30]

marketplaces. So, if you go to claude

[190:32]

plug-in marketplace, you'll see that

[190:34]

there are a few other ones that people

[190:35]

have put together here. Um, so this for

[190:37]

instance is the claude code marketplace

[190:39]

put together by a third party resource.

[190:41]

uh say anthropic wants me to take down

[190:43]

this website. That's pretty funny. Um

[190:46]

with you know like chatgbt prompts uh

[190:48]

let's see superpowers. I don't know

[190:51]

exactly what that does. We have the

[190:52]

contact 7 again. A bunch of cloud code

[190:54]

skills that looks like some other people

[190:56]

have put together although not all of

[190:57]

these links are going to work. And uh

[190:59]

yeah you know the the plug-in

[191:00]

installation process is pretty

[191:01]

straightforward as you guys saw earlier.

[191:03]

Um so I I'll leave it at that. I think

[191:05]

plugins are sort of going to be

[191:06]

deprecated and probably just absorbed

[191:08]

into skills at some point. So I don't

[191:09]

want to spend forever on them. Okay. And

[191:10]

finally, we have sub agents, which I

[191:12]

think a lot of people here were waiting

[191:13]

for. I want you guys to know that sub

[191:15]

aents aren't like a cure all. These

[191:17]

things aren't actually that incredible.

[191:18]

Um, you can do more or less everything

[191:19]

that you could do with sub agents as of

[191:21]

the time of this recording just with

[191:22]

like a normal master agent, but sub

[191:25]

agents do speed things up a little bit

[191:27]

and then they also allow you to

[191:28]

parallelize your workflow, which can be

[191:29]

quite useful in specific circumstances.

[191:31]

Um, one major issue that people

[191:33]

currently have with sub agents is they

[191:34]

consume a ton of tokens and then in

[191:36]

doing so can also cost a fair amount,

[191:38]

especially when you go to agent teams,

[191:39]

which as of the time of this recording

[191:40]

is seven times uh the token usage of

[191:43]

just using like one single cloud thread

[191:44]

like I've been doing throughout this

[191:45]

course. But sub agents are still pretty

[191:47]

useful to know. And so the very first

[191:48]

thing I'm going to do is I'm just going

[191:49]

to show you through example and then we

[191:50]

can actually look more into like the the

[191:52]

sub aent spec and stuff like that. So

[191:53]

you know how earlier we built this

[191:55]

system, the skill which fetches,

[191:57]

classifies, and labels 100 emails with

[191:58]

zero failures. What I'd like to do now

[192:00]

is I'd basically like to turn this skill

[192:02]

into a sub agent. So what I'm going to

[192:03]

do is I will remove this so we're not

[192:06]

loading any more stuff into context.

[192:08]

Hey, I'd like you to turn this Gmail-

[192:11]

label flow into a sub aent. The reason

[192:13]

why is because I want you to parallelize

[192:15]

your work. Instead of it taking 36

[192:17]

seconds to fetch, classify, and label

[192:19]

100 emails, I want you to be able to um

[192:21]

spawn 10 sub aents that do all of those

[192:23]

simultaneously and then return the

[192:25]

results. Uh I'd like you to do this

[192:27]

using the sub aent spec. If you don't

[192:29]

know what that is, do a little bit of

[192:30]

research on sub agents. Um, it's an

[192:32]

anthropic and claude code feature that's

[192:34]

quite well supported by our current

[192:35]

workspace structure. And once you've

[192:36]

built the sub agent using sonnet-4.5,

[192:40]

I want you to roll it out as a test and

[192:42]

then show me how much faster it is with

[192:44]

some sort of timing instrumentation.

[192:45]

Okay, so I have all that here. I'm now

[192:47]

just going to feed it into my prompt. If

[192:48]

we open up this little thinking tab,

[192:50]

it's going to start by researching the

[192:51]

sub agents and then building a

[192:52]

parallelized Gmail label flow that

[192:54]

spawns multiple sub agents to classify

[192:55]

emails simultaneously. It'll use sonnet

[192:57]

5 4.5 because it can load much more into

[192:59]

context probably read all my emails and

[193:01]

then it can actually go through this

[193:02]

whole process and then um you know

[193:04]

essentially parallelize it and

[193:06]

significantly improve the probability

[193:07]

and speed that these things are working

[193:09]

well and fast. The very first thing it's

[193:11]

going to do is actually spin up a bunch

[193:12]

of sub aents to do research. So that's

[193:13]

what this task little bubble is right

[193:15]

when it says research cloud code sub

[193:17]

aents. What it's actually doing is it's

[193:18]

giving this task to a sub aent called

[193:20]

the research sub agent. Uh there's

[193:22]

another sub aent as well like the search

[193:23]

sub aent. So, it'll actually search

[193:24]

through my workspace to see if there are

[193:26]

any pre-existing sub agent patterns. And

[193:28]

then because it's capable of spawning

[193:29]

these simultaneously, uh it typically

[193:31]

retrieves the results much faster than

[193:32]

normal. So, that's kind of fun. It's a

[193:34]

little bit meta of cloud code to do that

[193:36]

without really understanding what sub

[193:37]

agents are out of the box. Okay. It's

[193:39]

now going to create a sub agent

[193:41]

directory inside of mycloud folder. And

[193:43]

then it's going to populate it with um

[193:45]

all the sub aent spec parts and and

[193:46]

everything else. And what's really cool

[193:48]

is we're using sub aents alongside

[193:50]

skills in this instance. Um and that's

[193:52]

what I' I'd usually recommend. I don't

[193:53]

recommend just like creating sub agents

[193:55]

for the sake of sub agents unless

[193:56]

they're very specific ones. I'll show

[193:57]

you guys a couple of them in a moment,

[193:58]

but for the most part, like use them

[194:01]

where it makes sense. Use them in

[194:02]

situations where you want to parallelize

[194:04]

the workflow and be a lot faster. Okay.

[194:06]

And then because we just generated the

[194:08]

sub aents in a previous instance, we

[194:10]

actually have to um call the sub agents

[194:12]

in another cloud code instance. So I

[194:13]

just had to make a new one. Basically,

[194:14]

what it's going to do now is spawn a

[194:16]

bunch of sub aents for me. Okay, so

[194:17]

that's what these tasks are. So as you

[194:18]

can see, classify email chunk 1 2 3 4 5

[194:21]

6 7 8 9. So all 10 classifiers are now

[194:23]

running in parallel.

[194:25]

We now have all 10 task outputs here

[194:27]

which is pretty cool. It's now absorbing

[194:29]

all these task outputs and we're

[194:31]

operating at a much higher level of

[194:32]

speed than we were before. Right.

[194:35]

So now it's recording the time and then

[194:36]

it's going to merge and apply.

[194:38]

Classification took 19 seconds while

[194:40]

clock time for a,000 sorry 100 to

[194:42]

complete. And then let's see the total

[194:45]

time speed up. Okay. Okay. So, in this

[194:47]

instance, because we ran the same number

[194:49]

of emails, we did 100 versus 100, um, we

[194:51]

only saved 6 seconds. So, what I want to

[194:53]

show you guys now is I want to show you

[194:55]

guys how to do this um, at scale. So,

[194:57]

instead of, you know, 100 emails, I want

[194:58]

to do a thousand. Excellent work. I'd

[195:01]

like you to classify a thousand. The

[195:03]

benefits of the speed up are most likely

[195:05]

not going to be at the same level of

[195:07]

scale, but they will become evident when

[195:08]

we go at a much higher level of speed

[195:11]

uh, scale. So now we're going to run

[195:13]

1,000 of these, aka 1,000 emails split

[195:17]

into 10 chunks of 100 that are being

[195:19]

classified in parallel with 10 sub

[195:20]

aents. Considering that every time took,

[195:22]

I think like 19 seconds or something

[195:23]

like that per uh I think it's going to

[195:25]

be a lot faster. So we'll see. Okay,

[195:27]

some of these task outputs are now

[195:28]

starting to complete. It's been maybe 15

[195:31]

20 seconds. Not sure exactly how long,

[195:33]

but as they're all coming back um you

[195:35]

see these little gray bubbles turn into

[195:36]

green bubbles. Okay, we ended up having

[195:37]

an issue where the prompt was too long

[195:40]

essentially because all of these sub

[195:41]

aents returned massive strings of text

[195:44]

with every single email uh for whatever

[195:46]

reason when you combine all this into

[195:48]

you know the parent thread just way too

[195:50]

long and it ran out of context. So what

[195:52]

I did is I just copied over everything

[195:54]

and then I gave it to another instance

[195:56]

up here and I basically said hey this is

[196:00]

a little too long right now. Uh, I keep

[196:02]

running into,

[196:04]

you know, prompt too long output. So, I

[196:06]

think we ran out of context. I'd like

[196:07]

you to modify this so we don't run out

[196:08]

of context. If the sub agents don't have

[196:10]

to return the actual text to the parent

[196:12]

agent, that would be ideal. Then I ran

[196:14]

it in parallel for all 10. And uh, now

[196:16]

we're just redoing it. At the end of it,

[196:17]

it labeled 987 out of 989 emails. Um, I

[196:22]

didn't time that end to end. If I had to

[196:24]

guess, it' probably be somewhere around

[196:25]

like a minute or so, which means we are

[196:27]

now classifying a,000 emails in a

[196:29]

minute, whereas 100 was at 36. And this

[196:31]

is really the power of sub agents. Sub

[196:32]

aents basically allow us to take some

[196:34]

query and then split it up into 5, 10,

[196:38]

15, 20, whatever, run them all um, you

[196:41]

know, synchronously at the same time.

[196:43]

And then once they're done, they just

[196:44]

take the outputs of each of these

[196:46]

threads and then combine them into the

[196:47]

main one. And so, you know, there's a

[196:50]

couple of other use cases for sub aents,

[196:51]

but for the most part, it's going to be

[196:52]

something like this. Like, if you really

[196:54]

wanted to use sub aents in an

[196:55]

economically valuable fashion, this is

[196:56]

usually how you would do so. Uh, as of

[196:58]

the time of this recording, sub agents

[197:00]

are fantastic, but keep in mind like

[197:01]

most of the time they're going to be

[197:03]

less intelligent than the parent agent.

[197:04]

And so you want to reserve the parent

[197:06]

agent for taking the outputs of each of

[197:09]

these sub aents and combining them and

[197:10]

doing something with them, not just

[197:12]

spawning, you know, 500 things in

[197:13]

parallel to to to run for no reason. Um,

[197:16]

strategically speaking, some other

[197:18]

things about sub agents are try and make

[197:20]

the task definitions as simple and as

[197:21]

straightforward as possible. Like I

[197:23]

could have given every one of those sub

[197:24]

aents more context. I could have said,

[197:25]

"Hey, I don't just want you to do the

[197:26]

classification. I want you to do

[197:27]

everything. I want you to do the

[197:28]

classifications, the merges, the

[197:30]

applying the labels, etc. But because

[197:32]

the sub aents are dumber and because

[197:33]

we're spawning a bunch, you know, we're

[197:34]

multiplying probabilities here. If

[197:36]

there's like um even a I don't know,

[197:38]

let's say there's a 95% chance that the

[197:40]

sub agent is going to work, right?

[197:41]

That's a 5% chance that it's not going

[197:42]

to work. And the way in statistics that

[197:44]

you calculate the probability of a bunch

[197:46]

of things occurring in sequence is you

[197:47]

just multiply them out. So what this is

[197:49]

is this is 0.95 * 0.95 * 0.95.

[197:53]

Basically, what this is equivalent to is

[197:54]

0.95 raised to the 3. And so if we spawn

[197:57]

three sub aents, okay, the total

[197:59]

probability that all three of them will

[198:00]

work the way that we wanted them to, if

[198:02]

I just go back over here, is 0.95 raised

[198:05]

to the three here. So 85, aka 85.7%.

[198:10]

You know, I mean, if I'm running 10, the

[198:12]

probability is now down to 59%. If I'm

[198:15]

running, I don't know, 50, then the

[198:16]

probability is down to 7%. Obviously, I

[198:19]

want to maximize the probability that

[198:20]

all of these sub aents complete in the

[198:22]

time that I've allotted to them and

[198:23]

stuff like that. not only for you know

[198:25]

my own token count issues and my

[198:26]

consumption. So you guys see back here

[198:27]

like I'm now at 173 bucks in additional

[198:30]

usage on top of my cloud code usage. Um

[198:32]

not just from this course idea but I'm

[198:34]

doing a fair amount. Um but also for

[198:36]

like completeness's sake if I malform

[198:38]

the output and then my parent agent

[198:40]

can't you know collect it all right and

[198:41]

do something right with it. Well then

[198:43]

what I've done is I've just basically

[198:44]

wasted that whole query because uh sub

[198:46]

agent prompts are ephemeral. They only

[198:48]

exist for like a short period of time.

[198:49]

Their context windows are all

[198:50]

self-contained. Do I really want to

[198:52]

rerun that thing 100 times? Even if it's

[198:53]

cheaper, probably not, right? Next up, I

[198:55]

want to show you guys how to create what

[198:56]

I'd consider to be the three most useful

[198:58]

sub agents as of right now. So, what I'm

[199:00]

doing is I'm actually having Claude Code

[199:02]

create these as we speak. One's called

[199:03]

Code Reviewer. The other's called

[199:05]

Researcher, and the last one's going to

[199:06]

be called QA. And we're going to insert

[199:09]

all three of these agents into this

[199:10]

folder here alongside email classifier.

[199:12]

And then I'm going to update my cloud.MD

[199:14]

to reference the proposed workflow. Then

[199:16]

I'm going to show you what all that

[199:17]

stuff looks like. Now, in order to use

[199:18]

agents, what we actually have to do is

[199:20]

we have to um exit a a specific instance

[199:22]

that we generated the agents in.

[199:24]

Otherwise, we're not going to see them

[199:25]

as available in our task definition. So,

[199:27]

I'm just going to create a new instance

[199:29]

of cloud code. What sub agents do we

[199:31]

have access to? I also refreshed this so

[199:34]

we could see them all.

[199:37]

And as we can see, we have four. We have

[199:38]

code reviewer, QA, research, and an

[199:40]

email classifier. Okay. What is the

[199:42]

proposed

[199:44]

workflow every time we develop

[199:48]

some software?

[199:49]

What I want it to do now is I want it to

[199:51]

go through and then tell me first we

[199:52]

write the edit the code in the parent

[199:54]

agent. Then we code code code review

[199:55]

which spawns a code reviewer sub aent on

[199:57]

the change files fixes any blocking

[199:58]

issues. Then we do a QA spawning a QA

[200:01]

sub agent on the code generates tests

[200:02]

runs them reports results and fixes

[200:04]

failures. Then finally we do a ship. So,

[200:06]

now that we have all that ready, let's

[200:07]

actually go and then let's use our new

[200:09]

workflow on the flow that we just

[200:10]

created before. So, I think it was the

[200:12]

Gmail- label. Use our new workflow on

[200:15]

Gmail- label. It's the skill that looks

[200:18]

through my inbox and then labels emails.

[200:21]

So, what I want to do is I want to read

[200:23]

through the Gmail label skill to

[200:24]

understand what we're working with. So,

[200:26]

it's going to read the skill. Then, it's

[200:27]

also going to go through all of the

[200:28]

scripts. Then, I basically want to take

[200:30]

these scripts and then apply our little

[200:32]

flow. So the first thing it's going to

[200:34]

do is run the code review agent on all

[200:35]

four scripts. And as you can see here,

[200:37]

we can run these in tandem in parallel.

[200:40]

So first we're going to code review and

[200:41]

then we're also going to generate tests

[200:43]

and run them for the Gmail label

[200:45]

scripts. So we're going to use both of

[200:46]

these and then we're going to use them

[200:47]

to feed back to our parent agent. Our

[200:49]

parent agent is going to make changes to

[200:50]

this code and significantly improve the

[200:52]

quality of said code. Now is this like

[200:53]

required to do every single time? No. As

[200:55]

you guys could see, we capable of

[200:57]

writing some pretty damn good code

[200:58]

without knowing a lick of code. Um, with

[201:00]

just like the vanilla cloud code

[201:01]

installation, this sort of stuff becomes

[201:03]

more and more valuable when you're

[201:04]

working at enterprise and you're

[201:06]

creating code that requires uh the

[201:07]

ability to one be like really secure and

[201:10]

uh verifiable by both agents and then

[201:12]

human beings if they read them. And then

[201:14]

two to like account for all possible

[201:15]

edge cases. You know, in my case, I

[201:17]

don't really care too much about

[201:18]

counting for all possible edge cases

[201:20]

because most of the software I'm making

[201:21]

is for my own internal tooling. you

[201:23]

know, it's like a one-off landing page

[201:24]

for a client to use, that sort of stuff.

[201:26]

You know, if I'm working in a big

[201:27]

business, working in a versell or I'm

[201:28]

working in an open AAI or working in a,

[201:30]

you know, I don't know, Oracle big

[201:32]

database or whatnot, the stuff becomes

[201:34]

significantly more important. And that's

[201:35]

where, um, these sorts of code design

[201:37]

patterns become valuable. Okay, so we're

[201:38]

still waiting on the output of the other

[201:40]

task, but if I scroll down here, you can

[201:41]

see there's actually some

[201:42]

recommendations already. Um, this is

[201:44]

being provided inside of this task

[201:45]

output. So, it's not written very well

[201:47]

or nice. So, we're going to have to

[201:48]

squint a bit, but code is correct,

[201:50]

readable, and handles errors

[201:51]

appropriately. Batch fetching uses 100

[201:54]

per batch, but could use the Gmail API

[201:55]

max of a thousand requests per batch.

[201:57]

That means that we could significantly

[201:58]

improve the total efficiency of this

[202:00]

flow. Uh, and that's one piece of value

[202:02]

that the code reviewer's already given

[202:04]

for us. Then, we have some callback

[202:05]

stuff. So, basically, it's identified an

[202:07]

error or an issue, which is quite

[202:09]

useful.

[202:10]

um it's giving us some insights on the

[202:12]

readability and you know little

[202:14]

commenting that we could be doing to

[202:15]

make the code better and so on and so

[202:17]

forth. Okay, now the tests are

[202:19]

completed. So it looks like we've passed

[202:21]

most of the test. There's only one that

[202:22]

had a wrong exception and now it's

[202:24]

feeding in all of this information to

[202:26]

the parent agent. The parent agent is

[202:27]

going to go through and do the fix. So

[202:29]

16 to 18 characters.

[202:32]

It's going to jump through accepting

[202:34]

uppercase and variable length hex IDs.

[202:36]

No idea what that means, but of course,

[202:37]

this agent is now thinking dozens of

[202:39]

times faster than I'd be able to. So,

[202:40]

I'm just going to trust that it's doing

[202:41]

well and then uh frontload all of this

[202:44]

double-checking, triple checking, QA,

[202:46]

and so on and so forth to minimize the

[202:47]

possibility of longerterm errors. So,

[202:50]

that looks great. We've now run our new

[202:51]

flow, which uh has, you know, yielded

[202:53]

significantly better benefits. Okay,

[202:55]

great. now use the research sub agent to

[202:58]

go and find me the best um MCP server

[203:03]

currently available for Panda do.

[203:06]

So now I want to show you guys the value

[203:08]

of the research sub agent. This is now

[203:10]

spawned one of my research. So it's

[203:12]

going through it's doing tons of

[203:14]

research simultaneously

[203:17]

trying a bunch of different you know

[203:18]

search queries and so on and so forth.

[203:20]

It's now returned uh one of the web

[203:22]

search um results and as you can see

[203:25]

it's also doing tons of different like

[203:27]

HTTP requests and stuff like that

[203:28]

simultaneously. Now I should note that

[203:30]

like we already technically have a

[203:31]

research sub agent built in but you can

[203:33]

modify that research sub aent flow by

[203:35]

telling it hey you know I want you to

[203:36]

use specific sources. I want you to

[203:38]

trust these websites. I want you to you

[203:39]

know preferentially go directly to the

[203:41]

API docs and stuff like that. And so

[203:43]

that's what that research sub agent

[203:44]

allows us to do. allows us to research

[203:45]

things the way that we typically

[203:46]

research things which is going to be

[203:48]

different from just like doing a general

[203:49]

Google request for I don't know good

[203:51]

APIs for Panda do. So again just to

[203:53]

really impress upon you the value of

[203:55]

these um really a big chunk of value is

[203:59]

it's cheaper to use Sonnet as of right

[204:04]

now versus Opus. And so rather than do

[204:07]

your research or do your low uh you know

[204:11]

leverage or low ROI stuff like reading

[204:13]

through a large amount of data to

[204:14]

extract something, it's better to use

[204:16]

the cheaper models. The next is that

[204:18]

it's parallelizable

[204:20]

which just means that you can spin up

[204:22]

multiple simultaneously and then wait

[204:23]

for all their inputs as opposed to going

[204:25]

one at a time. Like for instance, if

[204:27]

this is us and this is sort of our task

[204:28]

flow. Um let's say you know this is sort

[204:31]

of the serial method which is what we

[204:32]

were doing before. Let's say every

[204:34]

search takes one minute. So you know

[204:36]

this is task one takes one minute. This

[204:38]

is task two which takes one minute and

[204:41]

then this is task three which takes one

[204:44]

minute. I guess this is two and then

[204:46]

this is three. That means in order to

[204:48]

get to you know

[204:51]

the start of our query to the end of our

[204:53]

query cloud code takes 3 minutes in

[204:56]

total. Right? Well obviously u the

[204:58]

parallel approach here is a lot better.

[205:00]

we start and then what we do is we just

[205:03]

spin up three different boxes here

[205:07]

simultaneously

[205:09]

and now these all take 1 minute and you

[205:13]

know by the time that we end what we've

[205:14]

done is we basically taken one minute

[205:17]

because each of these are executing

[205:18]

sidelong sort of um with each other. The

[205:20]

last major benefit is the way that the

[205:22]

context works. And so there's some

[205:24]

situations like a, you know, reviewer

[205:26]

sub agent where it's actually beneficial

[205:28]

not to have any of the context of the

[205:30]

code. It's not to have any of the biases

[205:32]

of the decision-m of the previous parent

[205:34]

agent. And sometimes, you know, choosing

[205:36]

a different model to do some of the

[205:37]

reasoning can uh, you know, reveal

[205:40]

things that maybe the parent agent

[205:41]

didn't necessarily think of. Sometimes

[205:43]

it makes more sense to look at the

[205:44]

ground at your feet and for instance the

[205:46]

dumbness rather than look up in the sky

[205:48]

at like all the complex advanced stuff.

[205:50]

Same thing with sort of like a QA agent.

[205:52]

The value of both of these is they don't

[205:54]

necessarily know what's going on um in

[205:56]

terms of the broader world. All they're

[205:58]

really focused on is the code itself,

[206:00]

the way that it was written. And so they

[206:01]

get to optimize objectively at like the

[206:03]

way to make that thing as efficient as

[206:05]

possible. And that's sub agents in a

[206:06]

nutshell. Doesn't have to be any more

[206:07]

complicated than that. It's basically

[206:08]

just a folder structure and it's very

[206:10]

similar to skills. My recommendation is

[206:12]

use this in conjunction with things like

[206:14]

skills to accomplish pre-existing

[206:15]

workflows. Um, many times faster because

[206:18]

of parallelization, but don't rely on

[206:20]

sub agents because a lot of the time the

[206:21]

time it takes to spin up a sub agent for

[206:23]

a simple query can be just as long as it

[206:25]

would take to use just a parent agent to

[206:26]

do the thing instead. While sub agents

[206:28]

sound really sexy and obviously

[206:29]

everybody wants to have giant fleets and

[206:31]

swarms of them working for you on your

[206:33]

behalf, um, be pragmatic and be

[206:35]

efficient here. And now it's time to

[206:37]

discuss one of Claude Code's most

[206:39]

commonly hyped and misunderstood, but

[206:41]

also pretty powerful features, agent

[206:43]

teams. If you're unaware, Claude Code

[206:46]

recently unveiled new functionality

[206:47]

where you can orchestrate a team of

[206:49]

agents, and you actually don't do the

[206:51]

orchestration yourself. You can actually

[206:53]

spin up a team of agents that are

[206:55]

managed by another agent for you, and

[206:57]

then all you really need to do is just

[206:58]

report back to that manager agent, let

[206:59]

them know what you want to do, and so on

[207:01]

and so forth.

[207:02]

>> [sighs and gasps]

[207:02]

>> Obviously, given the fact that this is

[207:04]

pretty interesting at first glance, a

[207:05]

lot of people are pretty stoked about it

[207:07]

and they've made tons of videos talking

[207:08]

all about how agent teams run their

[207:10]

whole life and have revolutionized

[207:11]

programming and so on and so forth.

[207:13]

Hopefully, in this module, I'm going to

[207:14]

show you that this is more of the same.

[207:16]

And agent teams are just another way

[207:18]

that you can parallelize your workflow.

[207:19]

So, the way I want you to think about

[207:21]

agent teams are basically just a more

[207:23]

advanced version of sub aents.

[207:25]

Basically, both agent teams and sub

[207:27]

aents are a mechanism of

[207:29]

parallelization.

[207:30]

like we had earlier when I showed you

[207:32]

that example of doing a bunch of

[207:34]

classification. You know, we have a task

[207:37]

and we could do the task one by one. And

[207:40]

if we do the task one by one, what we're

[207:42]

doing is we're incurring a fair amount

[207:44]

of fixed time cost. Not to mention,

[207:46]

there are some instances where task

[207:48]

steps aren't even necessary. And so if

[207:50]

each of these are 1 minute, obviously

[207:52]

that's 1 minute plus 1 minute plus 1

[207:54]

minute equals a total time of 3 minutes

[207:56]

to complete the task. Multiply this by

[207:58]

60, you get an hour, an hour, an hour, 3

[208:01]

hours. Uh I'm sure you can start

[208:03]

understanding why we parallelize work.

[208:05]

Much better to be able to spin up three

[208:07]

separate solutions, have those operate

[208:10]

simultaneously and then merely integrate

[208:13]

their results into one thread. Okay, in

[208:16]

a situation like this, assuming 1 2 3

[208:18]

take 1 minute, obviously the total time

[208:20]

spent is about 1 minute. So just like

[208:21]

sub agents allows one agent to spin up a

[208:23]

bunch of these different tasks and then

[208:25]

parallelize them. So too do agent teams.

[208:28]

It's just they operate one level even

[208:30]

higher. Instead of splitting one thread

[208:33]

into three, what you end up doing is you

[208:35]

basically end up splitting as many

[208:37]

threads as you want into as many

[208:40]

subthreads as you want as well. And so

[208:43]

in this specific case basically I have

[208:45]

one what's called team lead agent. And

[208:49]

this team lead agent, as opposed to

[208:51]

doing one, two, three, you know, four,

[208:54]

five, and six himself, what he's doing

[208:57]

is he's splitting things up into two

[208:59]

separate agents here, having them both

[209:01]

run three sub agents on their own and

[209:04]

then combine that into uh, you know, one

[209:06]

call. At the end of it, this agent then

[209:09]

combines them back into the main thread

[209:11]

and then can reason about things and so

[209:13]

on and so forth. much in the same way

[209:15]

that you know if you think about it um

[209:17]

organizational hierarchies work you'll

[209:19]

have like a manager up here in a

[209:21]

business and then you'll have you know

[209:23]

for the better lack of better words like

[209:25]

grunts uh down at the bottom. The

[209:27]

manager tells the grunt what to do. The

[209:29]

grunt goes does what they want and then

[209:32]

reports back. So too do we have sort of

[209:35]

this um same system with uh sub aents

[209:38]

and now manager agents as well. And then

[209:40]

you basically sit outside of this whole

[209:42]

thing just watching it all occur and

[209:43]

then nudging different people within the

[209:45]

organization or letting the team lead

[209:47]

know you want to change something where

[209:48]

necessary. So if you break things down,

[209:50]

sub agents own all of the context window

[209:53]

and the results return to the agent that

[209:56]

called them. So in our case, we have a

[209:58]

parent agent, we have a child agent. Our

[209:59]

child agent owns its own context window

[210:02]

and the results every time always go

[210:04]

directly to the person or the agent, I

[210:06]

should say. Look at me

[210:07]

anthropomorphizing these damn things

[210:09]

that called it. On agent teams, they own

[210:12]

their own context window completely.

[210:13]

They're also fully independent and so

[210:15]

they don't necessarily have to return

[210:17]

their results back to the caller. In

[210:19]

fact, agent teams can communicate

[210:21]

between them. So earlier where we saw

[210:23]

the grunts communicating with the

[210:25]

manager, grunts also have the ability to

[210:27]

basically communicate between each

[210:28]

other. And while I think that this is

[210:31]

ultimately less powerful or less

[210:32]

effective than communicating with the

[210:33]

manager because the manager is

[210:34]

responsible for synthes synthesis, there

[210:37]

are some instances where you know Grunt

[210:38]

one does have a interesting revelation

[210:41]

or timesaver for Grunt 2 that could save

[210:42]

him a fair amount of time. And in that

[210:44]

way um this sort of cross contamination

[210:47]

and cross-pollination of ideas while

[210:48]

consuming significantly more tokens can

[210:50]

lead to a better quality final product.

[210:52]

And that takes us to communication,

[210:53]

right? Um, with sub agents, you always

[210:55]

report back to the main agent only. But

[210:57]

here, teammates can message each other

[210:58]

directly. Basically, what occurs in an

[211:00]

agent team is they build this mutual

[211:02]

scratch pad, which is almost like a like

[211:04]

a message board or a BBS board, if you

[211:06]

guys remember from way back in the day.

[211:07]

It's like a forum. It's like their own

[211:09]

mini Reddit. And they'll post tasks that

[211:11]

they're currently working on. If they

[211:12]

have any questions, they'll ask specific

[211:14]

people that are responsible for those

[211:16]

things. Uh, and they'll always just have

[211:17]

that stored in their context. So if

[211:19]

they, you know, have a question from one

[211:20]

person, they can prioritize that

[211:22]

question and then go and find it in, I

[211:24]

don't know, their context and

[211:25]

immediately reply. In that way, you

[211:27]

could save individual agents significant

[211:29]

amounts of time. Terms of coordination

[211:31]

here, the main agent manages all the

[211:32]

work. But with agent teams, it's a

[211:34]

shared task list with self-coordination.

[211:36]

So just like we had a little Trello

[211:37]

board or maybe, you know, a ClickUp uh

[211:40]

task list or something like that, so too

[211:42]

do these agents work off the JSON

[211:43]

equivalent.

[211:45]

They say that sub aents are best for

[211:46]

focused tasks where only one result

[211:48]

matters whereas agent teams are best for

[211:50]

complex work requiring discussion and

[211:52]

collaboration. You know this is just one

[211:54]

of those like little marketing isms. The

[211:55]

definition between focused task and

[211:58]

complex task is very very fuzzy and

[212:00]

there is no real delineation between

[212:02]

them. Sort of like how there's a certain

[212:03]

point at which a hill becomes a mountain

[212:05]

but nobody could tell you exactly how

[212:06]

many feet high the hill needs to be or

[212:09]

whatever, right? It's just one of those

[212:11]

things where when you know you know. And

[212:13]

finally, the token cost of sub agents

[212:14]

are quite low, relatively speaking,

[212:16]

whereas agent teams are very, very high

[212:18]

because every teammate is actually a

[212:19]

whole separate cla instance. So when you

[212:22]

scale up and spin up a bunch of these,

[212:24]

you can use a fair amount of tokens

[212:25]

quite quickly. Now, I should note that

[212:26]

agent teams are not enabled by default

[212:28]

because they are what we call an

[212:30]

experimental feature. This may not

[212:31]

necessarily be true by the time you're

[212:33]

watching, by the way, but for now they

[212:34]

are. Um, they have set them to off

[212:38]

essentially by default. And so only

[212:39]

advanced users really get to peer behind

[212:41]

the curtain and and use them. The way

[212:43]

that you enable them is you edit your

[212:46]

settings.json in your current workspace

[212:48]

and you just create this sort of little

[212:50]

string. You have this curly brace. You

[212:51]

have in env. You have cloud code

[212:54]

experimental agent teams. You set that

[212:55]

to one and then you have some closing

[212:56]

curly brackets. You don't need to worry

[212:58]

too much about that. We'll do that in

[212:59]

like 5 seconds. Finally, the cool thing

[213:00]

about agent teams as mentioned is you

[213:02]

can't just it's not only that you can

[213:04]

communicate with the parent agent, you

[213:06]

can communicate with all of the agents.

[213:07]

So if uh I don't know you want to

[213:09]

context switch and tell agent 3 in the

[213:11]

se sequence to do something different

[213:13]

than it was currently doing. You can

[213:14]

absolutely do that really easily. There

[213:16]

are two different ways to do so. There's

[213:18]

what's called in process mode and then

[213:19]

split pane mode at least as of the time

[213:20]

of this recording. One is where you

[213:22]

basically just like alt tab through all

[213:24]

of them. The other is where there's just

[213:25]

multiple panes and so you'll see agent

[213:27]

one over here. You'll see agent two over

[213:28]

here. Agent three over here. And then

[213:30]

you'll kind of get their feed. Um, I

[213:32]

will note I've done this before,

[213:33]

unfortunately, because cloud code

[213:35]

renders your uh it's not just like a

[213:37]

simple text terminal. Basically, they're

[213:39]

like rendering this 2D image constantly

[213:42]

on your screen. It can consume a fair

[213:44]

amount of compute. So, I don't actually

[213:45]

like using it that way anymore. I I

[213:46]

basically always use an in process, but

[213:48]

I'll run you through what that looks

[213:49]

like if you did want to use split pane

[213:51]

mode. And then obligatory agent team

[213:52]

tokens cost way more because you're

[213:55]

spawning tons of different cloud

[213:56]

instances and every single one has its

[213:58]

own context window and can do its own

[214:00]

stuff. So, if you have like 10 active

[214:02]

agents running, you're going to consume

[214:03]

about 10 times the context, if not more,

[214:05]

because there's also going to be some

[214:06]

coordination and communication um lag

[214:08]

and overhead. So, they have some

[214:10]

recommendations here. They say use

[214:11]

Sonnet for teammates. Keep teams really

[214:13]

small because every teammate runs its

[214:15]

own context window. So, token usage is

[214:16]

roughly proportional to team size. Keep

[214:18]

the spawn prompts focused. We don't know

[214:20]

what those are, so I'll tell you that in

[214:21]

a second. Teammates will load their own

[214:23]

cloud MD, MCP servers, and skills

[214:25]

automatically, but everything in the

[214:26]

spawn prompt will also add to their

[214:28]

context from the start. clean up teams

[214:30]

when the work is done. So, you can

[214:31]

actually roll them down or shut them

[214:33]

down. And then, yeah, you know, agent

[214:34]

teams are disabled by default because

[214:35]

they don't want anybody blowing $10,000

[214:37]

on agent teams in a day, which uh you

[214:40]

can absolutely do if you're not careful.

[214:41]

That's why limits are so important.

[214:42]

Okay, so first things first, we have to

[214:44]

actually enable agent teams. So, I'm

[214:46]

just going to jump over here to this

[214:47]

URL, and then I'm just going to copy all

[214:49]

of the text on this page, and I'm going

[214:51]

to go over to anti-gravity. Open that

[214:54]

puppy up. And just for the purposes of

[214:56]

this example, I'm actually just going to

[214:57]

open a new folder. So, go to my Mac and

[214:59]

then I'll say agent teams example. Okay.

[215:03]

Going to open that and then what I'm

[215:05]

going to do is go over to Claude, paste

[215:07]

this in, and I'm going to say enable

[215:10]

agent teams. I'm going to go bypass

[215:12]

permissions. Close this puppy out so we

[215:14]

can all see it. Maybe bump this out a

[215:17]

bit so you guys can always see the text.

[215:19]

So, it's now added my um settings.json

[215:22]

here, and it's kind of fixed it. Okay,

[215:24]

so this is now good to go. And it's

[215:25]

enabled this across uh my global

[215:27]

workspace. So, it's not actually even in

[215:29]

my file. Let's start with a really

[215:30]

simple example of agent teams so I could

[215:32]

show you the parallelization aspect. And

[215:34]

then what we'll do is we'll actually go

[215:35]

into an open-source codebase and I'll

[215:37]

use agent teams to act as both uh code

[215:40]

reviewers and then also debaters to

[215:42]

debate between each other until they

[215:44]

determine consensus on how to make the

[215:45]

code even better. So, our first super

[215:47]

simple example is going to be I'm

[215:48]

designing a simple personal website for

[215:50]

Nick Sarrive. Generate three agents

[215:51]

using a team and create three

[215:53]

fundamentally different designs. Open

[215:54]

all three once done and I'll compare,

[215:56]

contrast, and give feedback.

[215:59]

Also,

[216:02]

make sure they know everything there is

[216:05]

to know about me. So, nobody is waiting

[216:09]

on anything. Okay, so I'm using the

[216:12]

terminal for this just because the

[216:13]

terminal UX is much nicer for agent

[216:15]

teams than the GUIX. I'm sure that'll

[216:17]

change at some point, but yeah, I also

[216:19]

have fast mode on up here, which is just

[216:20]

allowing me to do this a little bit

[216:22]

faster. And so, as you see, what's

[216:23]

occurred is the agent, this parent agent

[216:26]

here, Opus 4.6, sort of made the

[216:27]

executive decision for its very first

[216:30]

task basically. Oh, that's so cool. I

[216:33]

didn't even know I could do this to do

[216:34]

research um on Nick. And so, after it's

[216:37]

done the research, basically, it's now

[216:39]

going to spin up um you know, three

[216:41]

agents. One for site one, another for

[216:43]

site two, and another for site three. I

[216:45]

really got to figure out how to do this

[216:46]

with hotkeys. It's super annoying.

[216:49]

Um, and then these three agents are

[216:50]

going to go working on this thing

[216:52]

simultaneously and independently. And

[216:53]

then they're going to combine those

[216:54]

three websites back into just like we

[216:57]

did with sub agents, sort of that main

[216:58]

thread. Um, but what's cool is, you

[217:00]

know, these three different agent teams

[217:02]

since they're all individual cloud code

[217:03]

instances. They get to do a variety of

[217:04]

different um things. They also get to

[217:06]

like access their own agents, use their

[217:08]

own codebase and stuff like that. So

[217:10]

what's really cool is we have three

[217:13]

agents now working in parallel. The

[217:14]

first is called design minimalist. The

[217:16]

second is called design dark. And the

[217:18]

third is called design warm. I ask for

[217:19]

fundamentally different types of

[217:21]

designs, which is why they're doing

[217:22]

this. Now, if you wanted to see all

[217:23]

these agents run simultaneously, all

[217:24]

you'd have to do is just go shift up or

[217:26]

down. And so, right now, I'm in the team

[217:29]

lead context, but I could actually go

[217:31]

down here and then press enter. And now

[217:32]

I'm in the design dark. As you see here,

[217:34]

we got a ton of information here with

[217:36]

some uh context about who Nick Sarif is.

[217:38]

And then it says, "You're designing a

[217:39]

personal website. Create a single

[217:40]

self-contained file." It's now creating

[217:42]

a bold dark tech website. We could also

[217:45]

go up to the main team lead. And then

[217:46]

you can see that it's let me know that

[217:48]

the design minimalist is done and it's

[217:50]

still waiting on design dark and design

[217:51]

warm to finish their build. So I mean

[217:53]

like how exactly is this different from

[217:55]

um I don't know like sub aents right

[217:57]

now. Well uh it's different from sub

[217:59]

aents in that you can treat every one of

[218:02]

these as basically having its own whole

[218:04]

claude code instance available to it.

[218:06]

Okay, whereas before every individual

[218:08]

sub agent only had access to the

[218:10]

contacts that the parent agent gave.

[218:11]

Realistically, what I could do is I

[218:13]

could add a claw.md and all three of

[218:15]

these would have access to claw.md um

[218:17]

you know, style guides and stuff like

[218:19]

that. So, I'm going to take a look at

[218:20]

this. Okay, saying that it's all done

[218:22]

now. And it actually shut down all three

[218:24]

of those agents as well, which is

[218:25]

really, really important. If they're

[218:26]

constantly running in the background, um

[218:28]

you're also going to be computing uh

[218:30]

consuming compute resources just as well

[218:32]

as you are tokens. [gasps] Now, I'm

[218:33]

going to compare which ones I like more.

[218:35]

This one up here is building at the

[218:36]

intersection of AI and human ambition.

[218:38]

Wow, look at that. That's nice. Jeez.

[218:41]

insane. It's got a couple things wrong

[218:43]

here. Definitely have more than 150k

[218:44]

YouTube subs, but what are you gonna do?

[218:46]

Looks like it does have my links, which

[218:48]

is kind of cool. This is like uh you

[218:50]

know, dark coding one. Look at that.

[218:52]

Isn't that neat? And [snorts] this one

[218:54]

over here is uh very interesting.

[218:56]

There's no picture of me on it, but hey,

[218:57]

what are you going to do? [laughter]

[218:59]

That's my little nightclub promotions

[219:01]

party business. That's a hell of a

[219:03]

throwback. And uh yeah, what happens if

[219:05]

I click this? Okay, cool. We go we go

[219:06]

back to our YouTube. That's really

[219:08]

exciting. So, I mean, like I don't know,

[219:09]

maybe h

[219:12]

maybe I really like

[219:15]

uh the first one. So, now what I'm going

[219:17]

to do is I'm going to go back and I'm

[219:18]

going to say, "Hey, I really liked the

[219:20]

warm narrative option. Looks great. I'd

[219:23]

like now I'd like you now to spin up

[219:24]

three more agents. I then want you guys

[219:26]

to do research on um

[219:30]

effective design principles and

[219:33]

copywriting principles that convert. Uh

[219:36]

once done, I want you to spin up a bunch

[219:38]

of agents to iterate on this design and

[219:41]

come out with their own flavors or

[219:43]

versions then to report back to me. So

[219:45]

now what I'm doing is I'm taking uh you

[219:46]

know this winning design here, the warm

[219:48]

one. It's going to take this warm

[219:50]

beautiful thing and then I basically

[219:51]

wanted to like iterate on it even more.

[219:53]

And as you saw this occurred pretty

[219:54]

quickly, right? I mean this took me

[219:56]

maybe like 2 minutes or so. Is it

[219:57]

perfect? No. But um because it's not

[220:00]

perfect, I basically just want to have

[220:01]

Claude do a bunch of iterations on it

[220:02]

and then give me what I consider to be

[220:04]

an even better version, which I think it

[220:05]

can do pretty quick. So, it's going to

[220:07]

spin up a bunch more. We have research

[220:08]

copy, research design, and research

[220:10]

examples. This is a good um you know,

[220:12]

actual use case here. It's doing three

[220:15]

research agents in parallel. We have one

[220:18]

that's figuring out like strong design

[220:20]

principles based off of, you know,

[220:21]

winning combinations. There's another

[220:23]

that's doing some copyrightiting

[220:24]

fundamentals. And then the third that is

[220:26]

looking for highquality creator sites.

[220:28]

So Ali Abdal guy that I like, Hormosi,

[220:30]

obviously Danco. These guys are perfect.

[220:33]

More or less exactly what I'm looking

[220:34]

for. So it's going to go do a bunch of

[220:36]

research on them. And then it's going to

[220:37]

incorporate that in presumably some

[220:39]

other type of designer. I could see the

[220:41]

status by going shift up and down. So,

[220:43]

this person here, research copy, it's

[220:45]

looking up uh I don't know, best hero

[220:48]

copy formulas, personal brand, scannable

[220:50]

web copy, best practices, David

[220:53]

O'ilyriting Principles, headlines that

[220:55]

work. Right? If I go down here to

[220:57]

research examples, this agent is now

[221:00]

writing up a bunch of highquality

[221:02]

website styles. It's then analyzing the

[221:04]

websites and, you know, giving me all of

[221:06]

the copy and stuff like that.

[221:07]

Presumably, it's going to integrate this

[221:08]

into something nice. [gasps] Then if I

[221:10]

go back up to the team lead, then I can

[221:12]

see that it's, you know, basically just

[221:13]

waiting on all three of these to finish.

[221:15]

What's cool is these three all have

[221:17]

their own token usages as you see here.

[221:19]

So 53,000. This one here is 56,000. This

[221:21]

one here is 50,000. When they finish,

[221:23]

um, it then says idle and it tells you

[221:25]

how many seconds that the agent is idle.

[221:27]

This is, you know, mildly useful.

[221:29]

Obviously, not utilizing your clawed

[221:31]

agents is one of like the biggest issues

[221:32]

with them. So, what this thing is going

[221:34]

to do is basically wait for these other

[221:35]

two to finish and then if these other

[221:37]

two um don't finish after a certain

[221:38]

amount of time, it'll actually just wind

[221:40]

down the research design agent to stop

[221:41]

consuming my compute and stuff. Probably

[221:43]

the research examples is going to take

[221:45]

the longest time just cuz I think that

[221:46]

that's like less of a a clearcut

[221:49]

definition of done, but we'll see. And

[221:50]

then what's really nice is these are

[221:52]

cheaper models, right? 58,000 tokens on

[221:55]

the cheaper model, 56,000 tokens on the

[221:57]

cheaper model, then only 2,000 tokens on

[221:59]

the most expensive model. And so we

[222:01]

haven't actually integrated all of that

[222:02]

stuff back into the main yet. Um, but as

[222:04]

these finish, they will eventually, you

[222:06]

know, take all of their tokens and then

[222:07]

bring them back in. And so this token

[222:09]

count will uh will increase

[222:10]

significantly. Okay, now that all three

[222:12]

of these are done, we've collapsed these

[222:14]

three agents into uh the team lead. Now

[222:17]

we have these big design principles doc,

[222:20]

research copyrightiting doc, you know,

[222:21]

research site example doc. And because

[222:24]

I've empowered the uh team lead to be

[222:26]

able to spin up new agents based off of,

[222:28]

you know, various things like the

[222:30]

conversion rate, the the copy, the

[222:32]

creative, and the style, it's now

[222:34]

generating new ones. So, there's an

[222:36]

iterate dark iterate conversion. I don't

[222:39]

know how many of this these it's going

[222:41]

to spin up, but it's definitely going to

[222:42]

spin up some. In the meantime, we also

[222:44]

have these really dense research

[222:45]

summaries. So, I can actually open this

[222:47]

research design principles doc if I just

[222:50]

um scroll down a bit. So you can see we

[222:52]

now have things like there's a Z pattern

[222:55]

layout. Since the I starts in the top

[222:56]

left and moves to the top right, your

[222:58]

nav and CTA should be a particular

[222:59]

places. There's also an F pattern layout

[223:01]

and different actionable recommendations

[223:03]

on color psychology and so on and so

[223:05]

forth. I mean this is a tremendous

[223:06]

amount of text. Is this the most

[223:07]

efficient way to like get all this

[223:09]

across? Probably not. But because these

[223:10]

models just think so much quicker than

[223:12]

we do at this point, we don't really

[223:13]

need it to be as efficient. We can

[223:14]

actually just throw a tremendous amount

[223:15]

of text at a prompt and it can actually

[223:17]

do a pretty good job. What I really like

[223:18]

about this is it took key inspirations

[223:20]

from different people. So in this case,

[223:22]

Justin Welsh's upside down homepage. I

[223:24]

really like Justin Welsh. That's great.

[223:26]

Dan Co and Seahill Bloom's dark premium

[223:28]

bold typography. Origin story is some

[223:30]

sort of cinematic centerpiece. Like it's

[223:32]

taken inspiration from all these

[223:33]

different people. Then it's combining

[223:35]

them with slightly different

[223:37]

copyrightiting directions to create

[223:38]

things that are ultimately new and

[223:40]

presumably going to be quite different.

[223:42]

And you know, I think a lot of people

[223:43]

rag on agents and AI as not really being

[223:46]

creative. Like what is creativity? Um,

[223:48]

if not just like combining things over

[223:50]

and over and over again in like a

[223:51]

million different combinations. I'd

[223:52]

wager most things that you probably

[223:54]

consider to be creative are things that

[223:56]

like whose pre-existing pieces and

[223:58]

principles existed before and AI just

[224:00]

combined them into something that maybe

[224:02]

hadn't really been put together in that

[224:03]

way. There are certain sentences that

[224:04]

have never been said before or written

[224:06]

before. You could be the first to write

[224:08]

one. Some of them are quite creative.

[224:09]

Okay. And we are done. So the first site

[224:11]

here is I help aspiring a entrepreneurs

[224:12]

build their first 25K month automation

[224:14]

agency. I like this. This is really

[224:16]

clean. That's actually quite the value

[224:17]

prop. We do have an issue with the

[224:18]

button obviously. So the thing is this

[224:20]

model does not uh was not given the

[224:22]

ability to screenshot. I bet you if I

[224:24]

did that would have been pretty

[224:26]

straightforward. So this is a good

[224:27]

opportunity for me to update the

[224:28]

cloud.md and say hey you know you can do

[224:30]

some screenshots still. This looks

[224:32]

really great. Step one watch the free

[224:34]

training. Step two join maker school.

[224:35]

Step three build your agency. I mean,

[224:37]

honestly, the fact that this is just a

[224:38]

couple of minutes. This is so much

[224:40]

better than what um I could have done in

[224:42]

an equivalent amount of time, it's not

[224:43]

even funny. And not only did I generate

[224:45]

one, I generated three. So now I have a

[224:48]

dark one, right? That's pretty clean. I

[224:50]

like that. This must be the Danco one.

[224:54]

There has to be a faster way to matter.

[224:55]

Oo, that's clean. Right? Again, it's

[224:58]

taken that main website and then it's

[225:00]

iterated on it based off of different

[225:02]

styles and different approaches, which

[225:04]

is more or less exactly what you do in

[225:05]

any sort of copywriting and and so on

[225:07]

and so forth. So, I really like this

[225:08]

one. I mean, this one to me is probably

[225:10]

my favorite. You want to build an

[225:12]

automation business, but you don't know

[225:13]

where to start. I really really like

[225:14]

that. Um, so I think I'm actually going

[225:16]

to take that. Great work. Uh, buildin

[225:19]

screenshot functionality because you

[225:21]

don't have the ability to screenshot. A

[225:22]

couple things stand out. Also, get uh

[225:24]

pictures of me to put on the site.

[225:29]

Let's choose the first one, which is the

[225:32]

conversion machine. I think it's the

[225:35]

conversion machine, right? Yep. Also, we

[225:38]

need to update some stats. We have 2,100

[225:41]

or 2,200 people in Maker School right

[225:43]

now. You can check that out just by

[225:44]

googling Maker School. And then, uh, let

[225:47]

me see what else do we have. Grab the

[225:49]

image of me, Alexi, and Sam Ovens, and

[225:52]

put that somewhere on the site and add

[225:54]

more to the site. Right now it's good,

[225:56]

but I want it longer and with pictures

[226:00]

of me. Also, see if you could build some

[226:03]

sort of animation on the main homepage.

[226:05]

I think that would add a significant

[226:07]

amount of visual appeal. Right now, it's

[226:10]

pretty vague. I do quite like the

[226:12]

gradient, though. While you're at it,

[226:14]

spin up another three and continue doing

[226:17]

more iterations, more sections, etc. As

[226:19]

you can see, we're now searching

[226:21]

significantly more of the total space of

[226:24]

possible websites here because not only

[226:26]

did I spin up, you know, three initially

[226:28]

to build me these and then three

[226:30]

iterations on the one that I liked, I'm

[226:32]

now spinning up another four um based

[226:34]

off of the one that I really liked from

[226:36]

that previous iteration. And so in that

[226:38]

way, if you think about it, like what

[226:39]

we're doing is we're taking this idea of

[226:42]

what I want. We're testing a few

[226:45]

variants. We're seeing which ones

[226:47]

actually look good. These are two nos.

[226:50]

We're spinning up even more. We're

[226:52]

seeing which ones of these I really

[226:54]

like. Okay, these ones are all now. And

[226:57]

now we're spinning up another four. And

[226:59]

you know, eventually if you continuously

[227:01]

do this process, you'll get to a website

[227:06]

or a web app or a property that's like

[227:10]

five times better because we have

[227:14]

essentially instead of just picking one

[227:16]

option and stopping there, uh we've

[227:18]

really thoroughly explored the space of

[227:20]

all possible opportunities and options.

[227:22]

And so that's something that agent teams

[227:23]

really help with. I know my text is kind

[227:25]

of slanting up, but bear with me. And

[227:27]

while I'm doing that, we see that some

[227:28]

of these are already starting to finish.

[227:29]

So, iterate scroll just finished. That

[227:31]

was pretty fast. Looks like the

[227:33]

editorial magazine style site completed

[227:35]

with all 13 sections as well. We got the

[227:37]

conversion site fully rebuilt with all

[227:39]

the changes now. And now we're just

[227:40]

waiting on this split. There it is. It's

[227:42]

now going to open all four of these. And

[227:44]

so, for 150,000 tokens or whatever the

[227:46]

hell um I just spent essentially, I've

[227:49]

now been able to draft up what I'd

[227:51]

consider to be a pretty clean and sexy

[227:53]

website. I have that picture that I was

[227:55]

looking for. or I have this. I mean,

[227:57]

this is great, right? One thing I'm

[227:59]

missing is that little um video page,

[228:01]

but hopefully it's clear. I mean, I

[228:02]

could build God, websites are just the

[228:05]

the tip of the iceberg in terms of what

[228:06]

you could build. Have my picture here. I

[228:08]

got my little business part B in a show.

[228:10]

That's me during co doing a little

[228:11]

videography shoot. Um that's when we

[228:14]

played bowling down in the Philippines.

[228:15]

I mean, like this stuff's super

[228:17]

straightforward. Also, I really like

[228:18]

this other editorial site. I might end

[228:20]

up just choosing that. That's super

[228:22]

clean, right? Those harsh corners and

[228:24]

the photos and stuff. Very nice. Okay.

[228:26]

But if you just use agent teams to

[228:27]

design a bunch of websites, you're

[228:29]

honestly leaving tons of potential on

[228:30]

the table. Most people are kind of

[228:32]

uncreative and so obviously most of the

[228:33]

demos you're going to see on the

[228:34]

internet are going to be like, "Watch me

[228:36]

rebuild this website 400 ways like I

[228:38]

just showed you." Um, you can go a lot

[228:39]

deeper than that. And actually, the

[228:40]

number one recommended use for agent

[228:42]

teams right now, at least my recommended

[228:43]

use, is using it on pre-existing repos

[228:46]

to do a tremendous amount of research in

[228:47]

a short period of time. So, what I'm

[228:49]

going to do next is I'm actually going

[228:50]

to go over here. I'm going to delete all

[228:51]

of these websites that I built because

[228:53]

the websites are basically only worth

[228:55]

the tokens that they're printed on.

[228:57]

Okay, I'm going to full screen this and

[228:58]

I'm going to say um clone this and then

[229:01]

open an anti-gravity instance inside of

[229:03]

it. Then I'm going to paste in one of

[229:06]

the repos for OpenClaw, which uh I've

[229:08]

made some rather scathing videos of.

[229:11]

OpenClaw is totally open source, which

[229:13]

means you can muck around the code, take

[229:15]

a peek at the way that things were

[229:16]

written, make improvements if you really

[229:18]

wanted to, and so on and so forth. Looks

[229:20]

like it doesn't know what anti-gravity

[229:22]

is. Anti-gravity

[229:24]

the app. It's like VS Code. Okay, cool.

[229:27]

And it ended up opening up Open Claude

[229:30]

inside of this. As you see, we are now

[229:32]

like in the folder of OpenCloud, it's

[229:35]

just instead of it being on GitHub, it's

[229:37]

now on our computer. And so that's just

[229:39]

a quick and easy hack. You can basically

[229:40]

do whatever the heck you want with these

[229:42]

repos. Once you're inside, I'm just

[229:43]

going to open in the terminal because I

[229:45]

think I can probably go significantly

[229:46]

faster in the terminal. Um, let me just

[229:49]

open [clears throat] this up. Okay, I

[229:50]

have it right down over here. I'm going

[229:52]

to pop this puppy open. Make it go full

[229:55]

screen by clicking that button in the

[229:56]

top right. And now I'm going to use

[229:58]

agent teams to go through this massive,

[230:01]

massive file and then make improvements.

[230:03]

Taking a look at this prompt, I've wrote

[230:04]

open clause great, but there are a bunch

[230:06]

of security issues. I don't know exactly

[230:07]

where they all are yet, but I want you

[230:09]

to find them. First, create a team with

[230:10]

10 teammates to look through the

[230:12]

codebase very quickly. Split things up

[230:14]

logically based on file size, etc. Then

[230:17]

spin up four agents to document all of

[230:19]

the security issues and a fifth and

[230:21]

sixth debate agent that plays devil's

[230:22]

advocate back and forth. Use sonnet for

[230:24]

each teammate so as to make use of the

[230:26]

longer context window. When you've

[230:27]

identified all the security issues, then

[230:29]

spin up one agent per security issue and

[230:31]

make changes. Ensure each agent works

[230:33]

only on the security issue it is given

[230:34]

to minimize overlap. And if one agent

[230:36]

steps on another agent's toes, have them

[230:38]

rectify by talking back and forth. Now,

[230:40]

I'm not going to fix this codebase

[230:42]

throughout the course of this video

[230:43]

because that'll probably take several

[230:45]

hours for it to go through, make

[230:47]

changes, and then obviously there's Q&A

[230:48]

and testing and so on and so forth. This

[230:50]

is pretty similar to the workflow that

[230:52]

the creator of this godforsaken repo.

[230:54]

Uh, and if you're curious about why I

[230:56]

have strong opinions on this, just check

[230:57]

my channel for uh one of my videos from

[230:59]

like two weeks ago or so. But uh this is

[231:01]

pretty similar to the workflow that

[231:02]

they're currently using in order to

[231:03]

manage things. But suffice to say, you

[231:06]

can use an approach like this on

[231:07]

basically any open source library, not

[231:09]

just to identify security issues, but

[231:10]

also to improve the product. You could

[231:12]

come up with different uh product

[231:14]

angles. You could have it, you know, go

[231:16]

through spawn five agents each that

[231:19]

propose different product ideas, and

[231:20]

then you could have like debate agents

[231:21]

that debate back and forth about why

[231:23]

this would not be a good idea. And in

[231:24]

doing so, they come to a consensus and

[231:26]

improve the quality of the product um at

[231:28]

the end of the day. So what this just

[231:29]

did is it spun up and listed all of the

[231:31]

products here so that I could build a

[231:33]

simple and straightforward way of

[231:36]

basically um splitting this work up. So

[231:38]

now we have 10 scanner agents that are

[231:40]

running in parallel across the codebase.

[231:42]

This first one here has 83k lines. The

[231:44]

second one has 43 42 42 35 49. So

[231:48]

they're not all the same obviously, but

[231:49]

lines aren't all equal. So maybe this

[231:51]

did some additional work uh behind the

[231:53]

scenes or under the hood. Now this is

[231:54]

going to consume a lot of tokens. You

[231:55]

see here, we're already at 1.3 million

[231:57]

uh and counting. And you know, I'm

[231:59]

consuming a fair amount of my own token

[232:01]

budget to do this, but I figured it

[232:02]

would just be interesting for us to do.

[232:04]

If you're operating at like a massive

[232:06]

scale like this with dozens, if not

[232:07]

hundreds of these things, you know, you

[232:08]

will eventually spend several thousand

[232:11]

on said tokens. And so, you need to be

[232:12]

prepared for that. Don't spin up an

[232:14]

unlimited number of agents if you're not

[232:16]

capable of paying the money for set

[232:18]

unlimited number of agents, obviously.

[232:20]

And be wary that the tokens that you are

[232:22]

using here are tokens that uh

[232:23]

unfortunately you will never get back.

[232:25]

You can't spin this thing up and then

[232:26]

ask for a refund on any of these. So be

[232:29]

careful, I guess, to make a long story

[232:30]

short. However, if you do have the

[232:32]

money, you can basically convert it and

[232:34]

translate it directly into time as in

[232:36]

time savings. Um, what I've done here is

[232:38]

I've taken 1.3 million uh $1.3 million

[232:41]

$1.3 million Sonnet 4.5 tokens and I've

[232:44]

basically immediately translated them

[232:45]

for probably several hours of my time

[232:47]

because I don't actually have to go

[232:48]

through this or do this a lot slower

[232:50]

with like a more intelligent agent. So

[232:52]

now that we've done this, the next step

[232:53]

is we've compiled all of these security

[232:56]

uh possibilities I should say. We're now

[232:59]

spawning specific agents all about

[233:02]

particular security issues. So we have a

[233:06]

command injection and code execution

[233:08]

agent, an authentication and

[233:09]

authorization agent, a path traversal

[233:11]

plus SSRF plus info disclosure agent,

[233:14]

crypto plus race conditions plus config

[233:16]

agent, challenges findings as notreal

[233:18]

issues is devil number one. That's

[233:20]

devil's advocate. Then devil number two

[233:22]

says argues findings are real and need

[233:24]

fixing. And so basically these agents

[233:25]

are all going to report over to these

[233:27]

puppies. And these two are going to

[233:28]

debate back and forth between each other

[233:30]

to determine whether or not this is

[233:32]

something that's real, whether or not

[233:33]

this is something that's actually super

[233:34]

important. They're going to take

[233:35]

different uh principled positions and

[233:38]

attempt to see whether these findings

[233:39]

are not real issues or whether these

[233:41]

findings are real and need fixing.

[233:42]

Usually when you have two agents work

[233:44]

adversarily against each other like

[233:45]

this, the end result is higher quality.

[233:47]

This is actually the core of a big chunk

[233:48]

of machine learning um which is what AI

[233:50]

used to be called a few years back, not

[233:52]

just large language models. generative

[233:54]

adversarial networks for one of the

[233:55]

first image models for instance and they

[233:57]

worked in a very similar fashion. You

[233:58]

had something that generated and then

[234:00]

you had sort of like an adversary and

[234:01]

these two just went back and forth and

[234:03]

back and forth until you got a really

[234:04]

high quality result. So I can actually

[234:05]

scroll down here and see what these two

[234:07]

are saying. So these are literally

[234:08]

having a conversation right now. These

[234:10]

are actually discussing things. Looking

[234:12]

at devil number two, it's sending round

[234:14]

one its counter arguments. Now we're

[234:16]

going back here and they're basically

[234:17]

like fighting verbally. Mind you, sticks

[234:20]

and stones may break my bones, but AI

[234:21]

words will hurt you. Uh, to determine

[234:24]

which is the best path forward. This

[234:26]

message over here, this wasn't mine.

[234:28]

This was a message from the team lead.

[234:30]

Basically, a devil number one responded

[234:33]

to team lead saying, "Hey, here's a key

[234:34]

finding." Team lead responded back

[234:36]

saying, "Hey, keep going and let me know

[234:38]

when the debate finishes. When it's

[234:39]

done, we're good to go." So to be clear

[234:41]

here, over the last, I don't know, maybe

[234:43]

15 minutes or so of this specific um

[234:45]

agent team instantiation, I've spent

[234:48]

close to probably 80 or so dollars

[234:51]

directly on this one query. And that's

[234:53]

what I mean by trading money for time. I

[234:55]

mean, like obviously if I had a team of

[234:57]

developers doing this, you know, they

[234:59]

probably would have been more accurate,

[235:00]

but it also would have taken them

[235:01]

presumably several weeks to do the level

[235:03]

of research that this agent was capable

[235:05]

of doing in just a few minutes. Um I

[235:07]

traded $80 for that time. And so in some

[235:09]

instances that's worth it, but in a lot

[235:12]

of other instances it isn't, which is

[235:13]

why agent teams need to be handled

[235:15]

pretty carefully. They're almost like a

[235:17]

nuclear weapon, just one aimed directly

[235:18]

at your wallet. Now we've done the

[235:20]

debate back and forth. The two have had

[235:22]

a great conversation. And so basically,

[235:23]

they found 15 total flaws. What it's

[235:26]

doing, this is now spawning 15 fixer

[235:28]

agents, one per isolated security issue

[235:30]

or grouped when they touch the same

[235:31]

file. Now, I don't obviously want this

[235:33]

to consume all of my tokens, so I'm just

[235:35]

going to cancel this and I'll say shut

[235:37]

in caps. shut everything down ASAP. It's

[235:40]

not going to shut down all active agents

[235:42]

immediately. Unfortunately, just due to

[235:43]

the nature of this um the shutdown

[235:45]

request doesn't occur immediately. It's

[235:46]

not just like we're, you know, alt f4ing

[235:48]

this whole puppy. Um there's a little

[235:50]

bit of time because every individual

[235:52]

agent is still in the middle of a query

[235:53]

while it's doing the thing. Um so, you

[235:55]

know, you're probably still going to

[235:56]

consume a little bit of token usage. Not

[235:58]

going to be that crazy, but it is going

[235:59]

to be a little bit. Um but yeah, you

[236:00]

know, I've consumed enough at this point

[236:02]

to know that this is something that I'm

[236:04]

probably not going to want to do unless

[236:05]

I'm hellbent on improving the OpenCloud

[236:07]

repo, which I am not. And that takes us

[236:08]

to the final module in this course,

[236:10]

which is one on git work trees. Now, git

[236:13]

work trees used to basically be what

[236:15]

agent teams are today. Essentially, you

[236:17]

could have multiple agents all running

[236:19]

on their own individual what's called

[236:21]

GitHub repo or GitHub branch. And in

[236:23]

doing so, these agents could all work on

[236:25]

individual features, which allowed them

[236:27]

to do what they needed to do before

[236:29]

ultimately merging back to the main

[236:30]

branch. To visualize this for you,

[236:32]

imagine we start with a job over here at

[236:34]

main. This is our main branch. And then

[236:37]

there's some bug. So what we do is we

[236:39]

spin up a branch called hotfix. Now this

[236:41]

is given to a different agent. We then

[236:43]

have another branch called develop which

[236:45]

is given to a different agent. Then

[236:46]

finally a branch called feature which is

[236:48]

given to a different agent. So basically

[236:50]

what occurs is we have one agent over

[236:51]

here extending on this branch. One agent

[236:53]

over here extending on this branch. One

[236:55]

agent over here extending on this

[236:56]

branch. Then one agent over here

[236:58]

extending on this branch. And

[236:59]

essentially each of these go through

[237:01]

their own development process similar to

[237:02]

the agent teams like we just saw here

[237:04]

just managed through GitHub instead of

[237:06]

um just the anti-gravity IDE. And then

[237:08]

when they're done what they do is they

[237:09]

merge the results back into the mage

[237:11]

branch. Now if you're not a big into

[237:12]

programming and you haven't used GitHub

[237:14]

before this idea of a merge can be

[237:15]

pretty difficult to understand but

[237:17]

basically every branch just stores a

[237:19]

copy of the folder. And so this master

[237:21]

folder is basically the same thing as

[237:23]

this new feature folder with just a

[237:25]

couple of minor differences. And it's

[237:26]

usually the new feature itself. So when

[237:28]

you merge, what you do is you're just

[237:30]

tabulating a list of all the changes

[237:32]

between these two and then you're taking

[237:33]

the new changes from the new feature

[237:35]

branch and then applying them to the

[237:36]

master branch. Um this merge process can

[237:39]

typically be pretty messy and so having

[237:41]

agents around to mediate the merges and

[237:43]

so on and so forth can be quite useful.

[237:44]

So first of all, I have a really simple

[237:46]

website setup here called leftclick-

[237:48]

agency. I made this for my own website a

[237:50]

while ago and um you know had AI do the

[237:53]

vast majority of the work in a very

[237:54]

similar sort of workflow to what I just

[237:56]

showed you guys a moment ago with agent

[237:58]

teams. And what I want to do is you know

[238:00]

I want to design additional pages here.

[238:02]

Uh one page that's really long is not

[238:04]

enough. So in addition to this homepage

[238:06]

I also want to design an about page, a

[238:09]

contact page and a services page. And I

[238:12]

want to use the get work tree workflow

[238:16]

in order to do this. Now, because I've

[238:18]

stored information on what I mean by git

[238:21]

workree in my cloud.md,

[238:24]

which is basically that we use git work

[238:25]

trees for parallel development with

[238:27]

cloud code, where every work tree is an

[238:28]

isolated working directory sharing the

[238:30]

same git history, allowing multiple

[238:32]

cloud code instances to work on

[238:33]

different tasks simultaneously without

[238:34]

interference. Okay, this already knows

[238:36]

what to do. The very first thing that it

[238:38]

did was it basically took my main

[238:41]

repository which was just called

[238:43]

leftclick- agency and it made three

[238:46]

different ones. It made one called

[238:48]

leftclick- agency-services that's a new

[238:50]

folder. Another called leftclick-

[238:53]

agency-about which is another folder and

[238:55]

then another called leftclick- agency-

[238:58]

contact which is a third folder. So

[238:59]

basically what it's doing now is it's

[239:01]

creating new GitHub repositories, new

[239:04]

individual feature branches to work on

[239:06]

different pages for me. Now it did this

[239:08]

using the agent team functionality. And

[239:10]

the reason why I did this is just

[239:11]

because it's much faster and they get to

[239:13]

work on different GitHub repos

[239:14]

simultaneously. The only real advantage

[239:16]

to using git work trees I think at this

[239:18]

point is just that when you use git work

[239:20]

trees what you're doing is you're not

[239:21]

actually modifying the main folder. Like

[239:23]

if you look up here we're not actually

[239:24]

modifying any of this right now. What

[239:25]

we're doing is we're basically creating

[239:27]

a new folder in our, you know, uh,

[239:29]

GitHub repository and you can see them

[239:31]

right over here. Um, and then working in

[239:34]

those different folders individually.

[239:36]

So, for instance, we have leftclick-

[239:38]

agency. This one here is my main folder,

[239:41]

right? But then we have leftclick agency

[239:42]

about. This is a new branch that's

[239:44]

working specifically on the about. Then

[239:46]

we have contact. This is a new branch

[239:48]

working specifically on the contact

[239:50]

page. And then the finally we have

[239:51]

services, which is a new branch working

[239:53]

specifically on the services page. And

[239:54]

so the reason why this is valuable to

[239:56]

people that are non-programmers is

[239:58]

because you reduce the possibility of

[240:01]

two different agents working on the same

[240:03]

file uh which will occur. You will get

[240:05]

what are called agent conflicts over

[240:07]

time naturally as you have multiple

[240:08]

agents working on multiple things in the

[240:10]

same base. And the reason why is because

[240:11]

files aren't perfect separations of

[240:13]

functionality. You know you'll have one

[240:14]

file and then that file will have like

[240:16]

the snippet of a little bit of code

[240:18]

that's used by another file. And so in

[240:20]

that way there's there's never like

[240:21]

perfect separation. So if an agent

[240:22]

really wants to like totally encapsulate

[240:25]

a function or something, sometimes it'll

[240:26]

have to dump around from both and when

[240:28]

that happens, it'll step on the toes of

[240:29]

another one. So anyway, when you use

[240:31]

work trees in this way, you just

[240:32]

eliminate that um from being an option

[240:34]

completely. Uh basically, there's just

[240:35]

no way that these two can step on each

[240:37]

other's toes because they're actually

[240:38]

all working in separate folders

[240:40]

simultaneously. And because they work in

[240:41]

separate folders, that also means if

[240:43]

they do make changes, those changes

[240:45]

don't always perfectly harmonize right

[240:46]

away. And that's where that merge step

[240:48]

comes into into play. basically um you

[240:50]

know now after we work on these three

[240:52]

different branches what we also have to

[240:54]

do is we need to unify them through some

[240:57]

sort of merge uh function. You can see

[241:00]

the prompt for the general purpose

[241:01]

services.html one here is you're

[241:03]

building the servicesh page for

[241:05]

leftclick agency work in the work tree

[241:07]

at this folder create the file in here

[241:10]

don't modify the index.html you know

[241:12]

there's tons of information if I go back

[241:14]

here we'll see the same thing for

[241:16]

contact.html HTML. And so all you really

[241:18]

need in order to have a workflow like

[241:19]

this that minimizes um you know

[241:21]

dependency risks is just have a cloudmd

[241:24]

that outlines what to do with git work

[241:27]

trees. I'll include this file down below

[241:29]

so you guys have everything that you

[241:30]

need. But taking a look at the

[241:31]

about.html here which is one of the

[241:34]

files that this thing just whipped up

[241:35]

for me. Um you know we've now basically

[241:37]

finished the page. It's used some

[241:39]

placeholder little flasks here because I

[241:41]

wasn't sure what I wanted to do for

[241:42]

images. Um, and you know, I can add

[241:44]

however much information I want here to

[241:46]

really flesh it out. Yeah, this looks

[241:47]

pretty clean to me. Our principles ready

[241:49]

to work with us. We have That's really

[241:51]

clean. I didn't realize I could do that.

[241:53]

Uh, likewise with the contact. HTML

[241:56]

page. So, now we have a beautiful

[241:57]

contact. HTML page with like a little

[242:00]

send us a message form and so on and so

[242:01]

forth. I wonder if that works. Wow, it

[242:03]

even has some validation. That's pretty

[242:04]

neat. Okay. And then after it's done,

[242:06]

what it'll do is it'll merge everything

[242:07]

together. So, we also have um services

[242:11]

HTML up here, too, which is really

[242:13]

clean. This looks like a real chunky

[242:15]

page, which probably explains why it

[242:17]

took much longer. And it looks like it

[242:18]

even um estimated some prices for me,

[242:20]

which is pretty nice. So, yeah, suffice

[242:22]

to say, get work trees, while not

[242:24]

necessarily the end all beall, can be an

[242:26]

extra layer of insulation if you guys

[242:27]

are using something like um you know,

[242:29]

agent teams or even if you guys are

[242:31]

using sub agents um just using some sort

[242:33]

of merge functionality like I talked

[242:35]

about. If you guys want more on that,

[242:36]

I'll include the cloud.mmd below so you

[242:38]

guys have everything that you need.

[242:39]

Okay, so we've talked a lot about using

[242:41]

cloud code to build cool software apps

[242:42]

and stuff like that. The last thing I

[242:44]

want to talk about is basically just

[242:45]

automating or significantly streamlining

[242:47]

the process of deploying things to the

[242:48]

internet. You guys remember that first

[242:50]

site that I made and then the proposal

[242:52]

generator and stuff like that. I use a

[242:53]

simple service called Netifi to

[242:55]

basically push my work live. And that

[242:56]

service works really well for static

[242:58]

sites. I'm not affiliated with them

[242:59]

whatsoever, by the way. Use whatever the

[243:00]

heck you want. Um, but what I want to

[243:02]

talk about next is using something

[243:03]

analogous to that just for backend

[243:05]

functions and skills and scripts and so

[243:08]

on. So what I'm going to do here is I'm

[243:10]

going to whip up a open conversation.

[243:13]

I'm going to jump into bypass

[243:14]

permissions and I'm going to say deploy

[243:15]

a simple API endpoint that returns happy

[243:17]

birthday Nick if it's my birthday or no

[243:19]

birth today MF if it's not. And what I

[243:22]

want to do is I want to show you guys

[243:23]

how easy it is to basically whip up your

[243:25]

own URL that does something for you.

[243:28]

This is more of an advanced feature for

[243:29]

people that are into automation and

[243:31]

workflow building and stuff like that.

[243:33]

But basically, these services um in my

[243:35]

case I'm using one called modal allow

[243:37]

you to whip up like publicly available

[243:40]

endpoints or publicly available URLs

[243:42]

that you can use and integrate within

[243:44]

other applications. A lot of the time

[243:45]

applications will use things called web

[243:47]

hooks to send and receive information to

[243:49]

and from them uh to you know send events

[243:52]

and trigger various pieces of

[243:53]

functionality. And this is a quick and

[243:54]

easy way that you can basically create a

[243:56]

URL that does that for you as well as

[243:58]

integrate it into things like no code

[244:00]

platforms like naden, make.com, zap

[244:02]

year, lindy, etc. So I have my endpoint

[244:04]

right over here. What I'm going to do is

[244:06]

I'm going to take this curl. Okay, which

[244:08]

you may be wondering like what the

[244:09]

heck's going on over here. And then um

[244:10]

I'm actually going to open up my own

[244:12]

terminal instance and I'm going to paste

[244:13]

that in. And so basically what I've done

[244:15]

to make a long story short is I have

[244:18]

generated my own API. Zooming in here.

[244:21]

Okay, what I've done is I've sent a

[244:22]

request to my own website which was nick

[244:25]

nicholas arrive--thrack-check-

[244:28]

birthday.Motal run and then I sent some

[244:31]

authorization credentials and stuff like

[244:33]

that. And now it's sending me back um

[244:35]

you know a little message which is

[244:37]

basically saying no birthday today MF

[244:40]

cuz it's not my birthday. So I'm going

[244:41]

to do is I'm going to go back here and

[244:42]

just to make it even clear for you guys.

[244:44]

Okay, this is awesome. Remove the

[244:45]

authentication. I want to be able to

[244:47]

access this with my browser using a

[244:49]

simple get and then I want to have like

[244:50]

a cute little happy birthday or no

[244:52]

birthday message. What I'm going to do

[244:53]

now is I'm going to show you that this

[244:54]

is analogous or equivalent to just a

[244:56]

website. And so what you can do as well

[244:58]

is you can basically take whatever you

[245:00]

want, whatever piece of functionality

[245:01]

and then immediately deploy like single

[245:03]

URLs that people can access to do things

[245:05]

which you may not think is super

[245:06]

important. Um I just opened this up and

[245:08]

we have our own little website here.

[245:10]

But, uh, as you saw there, I mean, all

[245:11]

all I did was I literally sent like one

[245:12]

little message and then boom, it it

[245:14]

bumped this on like made this a publicly

[245:16]

accessible website. You can do this with

[245:18]

anything. You can do this with the

[245:18]

websites that we've designed so far. You

[245:20]

can do this with the web apps that we've

[245:21]

designed so far. Uh, and it's just like

[245:22]

the simplest and easiest way to get

[245:24]

something web accessible. whether you

[245:25]

are giving a URL to somebody to have

[245:26]

them do something with uh creating some

[245:29]

additional functionality in your app,

[245:31]

logging user visits for things like you

[245:32]

know ad campaigns and marketing uh

[245:34]

campaigns or um doing direct connections

[245:37]

via web hooks and no code platforms like

[245:39]

make.com naden etc. So how do you do it?

[245:41]

My favorite service right now is one

[245:43]

called modal. This is basically uh

[245:45]

marketed as AI infrastructure that

[245:46]

developers love. It's super easy and

[245:48]

straightforward to set up. And every

[245:49]

time you click on the page, it expands

[245:51]

this damn square thing, which is super

[245:54]

super cool to look at. I love cubes.

[245:56]

Clearly, their team has spent a lot of

[245:57]

time and energy designing this website.

[245:59]

I wonder if they used cloud code.

[246:01]

Anyway, [snorts] what you have to do

[246:02]

first, you have to sign up. So, I'm just

[246:03]

going to go over here into an incognito

[246:04]

tab. I'm going to pretend that I don't

[246:06]

have an account yet. Then, I'm going to

[246:07]

click sign up. Then, I'm going to

[246:09]

continue with Why don't we continue with

[246:11]

Google? Then, I'm just going to sign in.

[246:12]

Cool. We are now signing in. And the

[246:14]

very first thing that happens is you'll

[246:15]

have some little onboarding screen that

[246:17]

says welcome to modal. So I'm just going

[246:18]

to say personal and how did we hear

[246:20]

about us? Uh social media. I don't know.

[246:22]

I just want to use this for other. Then

[246:24]

I'll click get started.

[246:26]

What it's going to do now is it's going

[246:27]

to give me access to all sorts of stuff.

[246:29]

And in the top right hand corner, as you

[246:31]

see, it's given us $5 in credits. You

[246:33]

can actually claim up to $30 in credits

[246:35]

um just by doing a few additional like

[246:36]

little onboarding tasks, adding a card

[246:38]

and stuff like that. I should note that

[246:40]

I've been using Model for quite a while

[246:41]

now. It's probably been like a few

[246:42]

months and I think I'm still at like

[246:44]

$4.50

[246:45]

of credit on my main account where we

[246:47]

probably have like an API request coming

[246:48]

in every day or two. So, yeah, pretty

[246:51]

cool stuff. Um, definitely a lot of

[246:52]

usage there with the $5. It's way

[246:54]

cheaper of a service I want to say than

[246:57]

um like a lot of the no code tools and

[246:58]

automation platforms that I was using

[247:00]

before like make.com and naden. Over

[247:02]

here, what you need to do is create an

[247:03]

API token. So, I'm going to click new

[247:05]

token. I'll say for what did I what did

[247:08]

I actually have over here? That was

[247:09]

pretty interesting. not genuine. Okay,

[247:12]

let's do that. [gasps] And then we

[247:14]

actually have the token. So, I'm just

[247:15]

going to copy the server. And then what

[247:17]

I want to do is I just want to paste

[247:18]

this in. And um in the claw MD, there's

[247:21]

instructions where basically you can

[247:22]

just give it a new token and then it'll

[247:24]

go and create um you know, all of the

[247:25]

stuff for you. So, I'm going to include

[247:27]

this in, you know, the description down

[247:29]

below. You guys can take a peek at this.

[247:30]

If you're new to this, all you have to

[247:32]

do is just do what I just showed you.

[247:33]

And then now you have the ability to

[247:34]

basically run this on any account.

[247:36]

[gasps] And you know this because this

[247:38]

new URL that I just popped up here, this

[247:40]

is on a different um service now. It's

[247:42]

on my Nick J. Wells account, not my

[247:44]

Nicholas account, which I was on just a

[247:46]

moment ago. But let's say you want to

[247:47]

extend this. You don't just want to do a

[247:48]

simple URL that I don't know like tells

[247:50]

you whether or not it's your birthday.

[247:52]

You actually want to do something for

[247:53]

business purposes. Well, here's where

[247:54]

things get really interesting. What you

[247:56]

can do is you can take a skill that

[247:58]

you've developed before. Then you can

[248:00]

just put it up on a URL so that every

[248:02]

time you or somebody else accesses URL,

[248:04]

it immediately triggers the workflow.

[248:06]

Let me show you what I mean. Remember

[248:07]

how when we chatted about skills, I had

[248:09]

this one called scrape leads. What if I

[248:11]

just copy this and then paste this

[248:13]

directly into this folder? I'm also

[248:15]

going to wrap it in a dotcloud and then

[248:18]

a skills folder just for organization

[248:19]

sake cuz I could tell this is probably

[248:21]

going to get pretty complex if I don't.

[248:22]

Okay. And now I have it inside

[248:24]

of/skills/scrape.

[248:26]

Now what I'm going to do is I'm going to

[248:27]

say this is great. What I'd like you to

[248:29]

do now is I'd like you to put the

[248:31]

scrape-ads workflow online. I want to be

[248:34]

able to access it via a simple URL.

[248:36]

Basically, when I access scrape-s, I

[248:39]

want a little form to pop up and ask me

[248:41]

what I want to scrape. I then fill out

[248:43]

that form and then you execute the

[248:46]

scrape-s workflow and then return me the

[248:48]

leads in a CSV file when it's done. Now,

[248:50]

this has taken us probably less than 2

[248:52]

minutes in total. I just filled out the

[248:54]

request. We now have a URL. Just going

[248:56]

to open up this URL, which is, as

[248:58]

mentioned, the same as any other URL.

[249:00]

The search query I'm going to do is I'll

[249:01]

just do dentist. I'll say United States.

[249:04]

We want, I don't know, 100 results.

[249:06]

Let's make it really small. Now that

[249:08]

we've clicked, we're just going to take

[249:09]

a few minutes to do the actual scrape.

[249:11]

The instructions I gave it were to

[249:12]

immediately download the CSV right as

[249:14]

this is done. Okay. And then the top

[249:15]

rightand corner, I have my leads dentist

[249:18]

100. So, I'm just going to take a peek

[249:19]

at this. And we have the data right over

[249:21]

here. Okay, looking pretty good. We have

[249:24]

100 leads. Most of these look like

[249:25]

dentists, if not all. We also have a

[249:27]

bunch of additional data about them,

[249:28]

which is pretty badass. So, I could use

[249:30]

this to build a really cool campaign.

[249:31]

And yeah, hopefully you guys now see the

[249:33]

power in having something as simple as

[249:35]

modal available to both whip up really

[249:37]

quick web pages and internal tooling and

[249:39]

even some external tooling as well as

[249:41]

use this to do things like run

[249:43]

workflows, right? You can build your own

[249:44]

API call or build your own API endpoint,

[249:47]

I should say. It really just a couple of

[249:48]

keystrokes and that's that. I hope you

[249:50]

guys enjoyed learning everything and

[249:52]

anything to do with cloud code today.

[249:54]

You now have everything that you need to

[249:56]

build the foundational base of

[249:58]

knowledge, whether or not you guys are

[249:59]

programmers or completely nontechnical

[250:01]

people coming into this to learn how to

[250:03]

do things like build simple apps,

[250:04]

websites, or or workflows. I had a blast

[250:07]

teaching you guys this sort of stuff. If

[250:09]

you've ever wondered how to monetize

[250:10]

work like this, whether it is custom app

[250:12]

development or workflow building,

[250:14]

definitely check out Maker School. It's

[250:16]

my 90-day accountability program where I

[250:18]

guide you through step by step and quite

[250:19]

literally every single day through a

[250:21]

sequence of actions necessary to get you

[250:23]

your very first customer. And I also

[250:25]

guarantee that you get your first

[250:26]

customer by the end of a 90-day period.

[250:28]

If you don't, I give you all your money

[250:29]

back. That's my last and only pitch of

[250:31]

this video. Aside from that, I hope you

[250:33]

guys like what you saw. If you guys have

[250:34]

any questions or need help with anything

[250:36]

that I mentioned in the video, just drop

[250:37]

it as a comment down below. Aside from

[250:39]

that, have a lovely rest of the day and

[250:40]

I'll catch all y'all in my next course.

[250:42]

Bye.

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