AI as the Philosopher's Stone: Marc Andreessen on the Future of Work

If we didn't have AI, we'd be in a panic right now about what's going to happen to the economy. We've actually been in a

regime for 50 years of very slow technological change in the face of declining population growth. The timing

has worked out miraculously well. We're going to have AI and robots precisely when we actually need them. The

remaining human workers are going to be at a premium, not at a discount. >> How big of a deal is the moment in time

that we are living through right now? >> This is a very, very historic time. AI is the philosopher stone. Now we have a

technology that transfers the most common thing in the world which is sand converted into the most rare thing in

the world which is thought. >> We spent a lot of time with the most cutting edge AI forward founders. The

most leading edge founders are thinking of can you have [music] entire companies where the founder does everything.

>> There's all this concern that young people jobs are not going to be there for them. AI is replacing them.

>> Everybody wants to talk about job loss but really what you want to look at is task loss. The job [music] persists

longer than the individual tasks. >> What's your sense of just the future of three very specific roles? Product

manager, engineer, designer. There's like a Mexican standoff happening between those three roles. Every coder

now believes they can also be a product manager and a designer because they have AI. Every product manager thinks they

can be a coder and a designer. And then every designer knows they can be a product manager and a coder. They're

actually all kind of correct. What happens is the additive effect of being good at two things is more than double.

The additive effect of being good at three things is more than triple. You become a super relevant specialist in

the combination of the domains. >> People aren't fully grasping how much this changing. And people who really

want to improve themselves and develop their careers should be spending every spare hour in my view at this point

talking to AI being like, "All right, train me up." Today my guest is Mark Andre, one of the

most seinal figures in tech and in business. He invented the web browser, built the world's largest venture firm.

He's also a multi-time founder and an investor in essentially every generational tech company and is also

one of the most clear-minded, lateral, and insightful thinkers about both the past and the future of technology. In

this very special conversation, we chat about how unique and significant the moment that we are all living through

right now is, what skills he's teaching his kids to thrive in the AI future, what happens to product managers,

designers, and engineers in the coming years. where [music] moes exist in AI, what the most AI native founders are

doing differently, and so much more that is just scratching the surface of this very deep and important conversation.

You are going to walk away from this chat being smarter about what is going on in the world right now and where

things are heading. A huge thank you to my newsletter community and focus on X for suggesting topics [music] and

questions for this conversation. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite

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Mark Andre after a short word from our sponsors. Today's episode is brought to you by DX, the developer intelligence

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can too at brex.com. Mark Andre, thank you so much for being here and welcome to the podcast.

>> Awesome, Lenny. Thank Thank you. It's great to be here. >> I want to start with just a big picture

question. I have a billion directions I want to go, but I think this is going to give us a little bit of a frame of

reference. How big of a deal is the moment in time that we are living through right now?

>> This is a very very historic time. I think 2025 was maybe the most interesting year in my entire career and

and probably life and I think I would expect 2026 to exceed that. >> Wow, that says a lot.

>> Yeah, I've se I've seen some stuff. So, um it feels like two things are happening. one is the the the trust that

a lot of people have had in kind of what you describe as kind of legacy institutions around the world is I I

think in kind of full scale collapse right now. By the way, there's a lot of data data to support that. And so I

think there's just there's there's like a lot of structures and orders and uh institutions that people have just

relied on for a long time that have just proven to not be up for the up for the challenge. And then kind of

corresponding with that is the national and global conversation have become like let's say liberated. Um, and so, you

know, this sort of incredible revolution that we have in in kind of, uh, you know, what I've described as freedom of

speech, freedom of thought, um, ability for people to openly discuss things that maybe they couldn't discuss even a few

years ago, you know, is just dramatically expanded. And I think that's that's now on on a one-way train

for just a much broader range of discourse. And then, you know, there's also just these like incredibly massive

geopolitical shifts that are happening. And obviously, the the US is changing a lot, Europe is changing a lot, China is

changing a lot, Latin America, by the way, is changing a lot. very dramatic, you know, events playing out down there

right now, you know, kind of all over the world. Like I think a lot of assumptions are being pulled out in the

into the daylight and and re-examined. And and then it's kind of the fact that all these things are happening at the

same time, right? And so you've got all of these countries and industries, you know, where things are kind of

increasingly upheaval, but you have AI is this kind of new technology that's going to really affect things. And then

you've got, you know, people, you know, citizens being able to fully participate, uh, and being able to argue

things out. So, it's it's kind of like those three kind of big mega things are kind of all colliding um at the same

time. And I I think we're probably just the very beginning of all three of those. And those all feel like kind of,

you know, historical, you know, moment shifts, you know, comparable in magnitude to maybe the fall of the

Berlin Wall in 1989, you know, maybe maybe the end of World War II. Um you know, kind of moments like that. It

certainly feels like that. >> Good God, [laughter] what a time to be alive.

>> Yeah. In terms of the AI piece, which is where a lot of people are trying to figure out what to do, what do you think

isn't being priced in yet in terms of the impact AI is going to have on say the world or just people listening?

>> The I think at I think at this point I think it's pretty clear with it with you know our technology hats on that like

this stuff is really working now right and so there there was this you know kind of you know when when there was a

chat GPD moment you know three years ago it was only by the way only three years ago right? um was the chat GPD moment

and and the big question was all right this this is like incredibly fun and creative and like we have machines now

that can compose Shakespeare and silence and rap lyrics and like you know this is amazing but then there was there you

know there's this big question like can you can you harness this technology for reasoning um and for you know problem

solving in domains that like really matter you know medicine and science and and and law and so forth um and and you

know it turns out the answer to that is yes right um and you know the the last 12 months and especially the last even

just the last three months have really proven that like AI can really do like you know you're seeing it all now you

know you can actually you know AI is now developing new math theorems um you know there you know over the holiday break

you know there's sort of the what it feels like the AI coding thing you know really hit critical mass uh and the

world's best you the world's best programmers right including like Lisbald's you know for for the first

time over the holiday break basically said yeah AI is now coding better than we can and so that you know that's

that's incredibly incredibly powerful and I think we we all you know kind of I think assume that AI now is going to get

really good at reasoning um in in any domain do in which there are verifiable answers and so that that you know that's

going to include like many very important domains. So um so like for the technology feels like it's it's it's

moving fast and and it's going to be working really well. Um I think the thing that is not well understood I I

think a lot of people have a I think you know a lot of people in the industry have kind of what I would describe as

this one-dimensional thing which is okay as a result of the technology not working AI just kind of sweeps sweeps

the world and changes everything. And I think that's that's kind of the wrong that's kind of the wrong frame. I think

it's based on an incomplete understanding of of the world that we live in or the world that we've been

living in for the last you know 80 years and I would call out two things in particular. So one is it has I think

it's felt to us like in the US and the west for the last you know whatever 30 years or 50 years it's felt like we've

been in a time of great technological change but actually if you look for actually evidence of that like in stat

in statistical evidence of that analytical evidence of that like you basically can't find it. Um and in

particular um economists have a way of measuring the rate of technological change in the economy that is

productivity growth which which we could talk about what that means but basically it's it's a it's sort of the

mathematical expression of the impact of technology uh on the economy and productivity growth for the last 50

years has actually been very low not very high so we all feel like it's been very high there's been lots of

technological change what's actually happening is it's it's been very low and in fact the pace of productivity growth

like in the US is is running at like a half of what it in my lifetime, in our lifetimes, it's been running at about a

half the pace um that it ran in um between 1940 and 1970. And it's been running at about a third the pace that

it ran between about 1870 to about 1940. And so statistically in the US in the west technology progress in the economy,

technology impact the economy has actually slowed way down. And so we, you know, the AI thing is is going to hit,

but it's hitting an environment in which we, we have actually had almost no technological progress in the actual

economy for a very long time. So we could talk about that. And then there's this other like just incredible thing

that's happening, which is the the, you know, s the de demographic collapse, right? It's sort of a western

phenomenon, an increasingly global phenomenon, which is, you know, the rate of reproduction of the human species is

is in rapid decline. And you know there are many countries you know including the US where you know the rate of

reproduction is you know under two you know meaning meaning that you know many many countries around the world by the

way including China which is a really big deal are actually going to depopulate over the next century um and

so you have this kind of precondition that says there's actually been very little techn technological progress

happening in the world um and the world is going to depopulate um and so AI is going to enter the world a world in

which those two things are true and I think it's inc this is incredibly important because we actually need AI to

work in order to get productivity growth up, which is what we need to get economic growth up. And we actually need

AI to work because we're going to need, you know, we're going to need machines to do all the jobs that we're not going

to have people to do because we're we're literally going to depopulate we're going to depopulate the planet over the

next hundred years. And so I I think the interplay of these factors is is going to be much more interesting and and

frankly more more more complex than a lot of people have been thinking. >> I'm going to follow this thread about

kids. I know you have a kid and one of my most my favorite lenses into how people think and what they value is what

they're teaching their kids, what they're steering their kids towards. >> Are there specific skills or I don't

even careers that you're steering your kid towards? >> The way I think about this and you know,

yeah, we we have a 10-year-old and so, you know, we and we actually homeschool and so we we we think a lot about this.

Um so I think the way to think about the impact of AI on on people on specifically people as individuals I

think it's it's it's actually you know a lot of people just focus on kind of this you know this kind of very I would say

straightforward and or overly simplistic view of just literally job gains you know job losses which we could talk

about but there's two specific things at the level of like an individual person and individual kid so I think it's

pretty clear that AI is going to take people who are good at doing things and it's going to make them very good at

doing things right and so It's going to be a tool that's going to sort of raise the average kind of across the board.

And you know, look, you see that playing out already. You know, anybody who's in a position where they need to, you know,

write something or design something or write code or whatever, if they're if they're pretty good at it today, they

use they use AI and all of a sudden they're very good at it. And so there there's sort of that aspect to it. And I

think the the the way the education system very large is going to teach is going to kind of teach AI is is going to

be based, you know, hopefully a lot on that. But then there's this other thing that's happening which we're also

starting to see and we're really seeing it particularly in coding right now. Um where the really great people are

becoming like spectacularly great, right? Um and so you just you kind of use it use the term you think about like

the supermpowered individual, right? So the individual who is like really good um at coding or really good at making

movies or really good at making songs or really good at designing you know making art or whatever whatever those things

are or or you know or podcasting or you know hopefully venture capital you know if if you're very good at it and you can

really harness AI you can become spectacularly great uh and like super productive right and you know I'm sure

you have a lot of friends in this in this category as well but like you know the the really really good coders are

experiencing this right you know, my friends who are really good coders are like, "Oh my god, all of a sudden I'm

not twice as good as I used to be. I'm like 10 times as good as I used to be." And so I think at the at the unit of

like n equals one of like an individual kid, I think the question is kind of how do you get them in a position where

they're kind of this kind of supermpowered individual such that they're going to be really kind of deep

in whatever it is they're going to do, but they're going to they're going to be deep in a way that's going to let them

fully use the power of AI to be not just great, but to be like spectacularly great. Um, and and I think that that

that's that's going to be the real, you know, that that that that that's the real opportunity and that, you know, at

least that's what we're shooting for and that's what I would encourage parents to shoot for.

>> So, what I heard there is essentially agency, this word that we see on Twitter all the time is building uh agency, them

not waiting for someone to tell them what to do, figuring out what to do. >> Yeah. Yeah. So, this this this thing

with this this term agency that's become very very um you know, very popular um [laughter] certainly California for the

last couple years. It's really interesting because it's it's I had a lot of trouble with this early on

because I'm like agency. What are they talking about? And what what they're kind of talking about is like, you know,

initiative, you know, um you know, willingness to, you know, you could just do things. Um

you know, uh what is it? Uh the the demo bird has the great term live player. Um you know, you you you can be like a

primary participant in events. And at first I was like, well, yeah, like that's kind of obvious, right? like of

course and and then I'm like oh actually it's not so obvious anymore because kind of your your point I think so much of

our society is based on like there are all these rules and everybody gets taught kind of by default you're

supposed to follow all these rules right and then everybody if you like break the rules like everybody gets freaked out

it's like oh my god he broke the rules and so like we we we have somehow worked our our way our way kind of you know I

don't know psychologically sociologically you know kind of into a state in which I guess the natural

assumption for a lot of people is you know the thing that you for example you want to train kids to do is like follow

all the rules. Um, and you know, you could argue that kind of you know, for example, the you know, the school

system, the K through2 school system or whatever has gotten kind of more and more focused on that over time. And it's

like yeah, it's like no, you you should actually and again, especially at unit unit n equals one, like of your kid.

It's like and look, there's there's something to be had. We I just had this conversation my 10-year-old last night

actually. I I I rolled out uh uh the concept of uh you know, in order to lead, you must first learn to obey,

right? In order to you know, issue orders, you must learn how to follow orders. and you know you kind of try to

keep keep him with some level of structure in his life and not just and not just pure agency but yeah I mean and

so look you know some rules are important and so forth but yeah no look there there is like a huge b there's

just a huge premium in life on being somebody who is able to like fully take responsibility for things fully take

charge run an organization lead a project create something new um and you know maybe yeah that that has been maybe

a little bit diminished in our culture over the last 30 years it you know it's it's healthy you know that that you know

that that there's now a term for that that that is coming back back into vogue and then and then and again that's how I

view AI for kids is like okay AI should be the ultimate letter on the world for a kid with agency to be able to say okay

I can actually be a primary contributor right whether that's I can be a primary contributor in everything from you know

developing new areas of physics to writing code to being an artist uh you know to writing you know to writing

novels like you know whatever that thing is I I can fully participate in the world I can really change things and I

and I that that feel that The combination of that idea combined with this technology feels very healthy to

me. >> What is that quote about? Give me a lever and I'll move the world.

>> And I'll move the world. Yeah, that's exactly right. Well, so it's actually funny you mentioned that. So the the um

the uh the the early kind of scientists including like Isaac Newton were super obsessed with with you know this concept

of alchemy, right? It's like you know they you know they you know they developed like you know Newton he's like

developed Newtonian physics and he developed like calculus and all these things but the thing he was really

obsessed with was alchemy which was the thing he could never get to work right and and and alchemy was the

transmutation of lead into gold which meant the transmutation of something that was very common which was lead into

something that was very rare and valuable which was gold. And you know they there was this the he spent you

know decades trying to figure out this thing called the philosopher stone which would be basically the the machine or

the process that would would be able to transmute the rare you know the common thing into the rare thing led into gold

and he never figured it out and you know it's incredibly frustrating nobody ever figured that out and now we literally

with AI have a technology that transfers sand into thought [laughter]

>> just blew my mind >> right the the most common thing in the world which is sand converted into the

most rare thing in the world which is Right. And and so AI is it is it is the it is the philosopher stone. Like it it

is that it it actually is that and it's just this incredibly powerful tool. Um and and that's where I that's where I

get so excited. I mean and again this is what we're doing with our 10-year-old which is like all right a primary thing

that we want to make sure to to do is to make sure that he knows fully how to leverage and and get and get benefit out

of the philosopher stone, right? Which is uh you know which is to say AI and that that and then you know that's

certainly central to everything we're teaching him. you know, there's there's this meme going around that um you know,

Silicon Valley people don't let their kids use computers. And I I just I I there may be a handful of people who are

like that. I I don't you know, I don't know. Um I I think it's more honestly the other way around, which is uh the

you know, the more you're kind of plugged into stuff in Silicon Valley, the more important it is to make sure

that your kids actually fully understand this and know how to use it. And that's certainly the mode that we're in. And

that's that's certainly the mode that I would encourage parents to think about. >> I did not know your kid was

homeschooled. That is super interesting. There it's almost a statement on, you know, education in today's day. Maybe is

there any thoughts there? I'm just for folks that maybe aren't in your tax bracket that want to help their kids be

successful, maybe homeschooled, maybe not. What what advice would you have? >> This is the challenge and again this

this kind of goes to how you're you know kind of your original question which is education there's two completely

different ways to talk about think about education. The way that's usually thought about and talked about is kind

of at the level of like a nation, right? So, so you know, it's like a national level issue or maybe a state level issue

in the US, which is basically like how do you educate all the kids? And of course, that's incredibly important. And

of course, you're going to need like some level of large scale system like the, you know, the national K- through2

school system or something like that, you know, in order in order to do that. Um, but then there's this other question

which is like at n equals 1 for an individual kid like what can you do with with an individual kid? Um, and so I'll

just give you kind of the ultimate, you know, kind of the ultimate answer to that question, which is it's been known

for centuries that the ideal way to teach a kid at the unit of n equals 1, by far the ideal way to do it is is with

one-on-one tutoring. Like if you just have an individual kid and the goal is to maximize an individual kid, by far

you get the best results with one-on-one tutoring. And and this is something that like every royal family knew in history.

It's something that every aristocratic class knew in history. There's all these amazing examples. Alexander the Great

was tutored by Aristotle. He took over the world, right? Like, you know, many of the great kings and queens and you

know, royal families and aristocrats and so forth, you know, over the course of centuries. Um, you know, kind of always

had always had this approach. There's actually also statistical evidence, um, analytical evidence that this is

correct. Um, there there's this, you know, massive question in the field of education, which is how do you improve

educational outcomes? And basically it turns out it's just it's very hard to improve educational outcomes except

there's one method that always does it which is called the it's called the bloom two sigma effect which is there's

one method of education that routinely raises student outcomes by two standards of deviation and will take a kid from

the 50th percentile to the 99th percentile and that's oneonone tutoring right so again if you go back to like at

n equals one you have a kid and a tutor and they're in this like you know very tight loop with each other you know

where the kid is able to constantly kind of be on the leading edge of what they're capable of doing and they can

they you know they they can move incredibly past and they get kind of correction in real time, you get these

better outcomes. But, you know, to your question, like it's never been economically feasible for anybody other

than the richest people in society to be able to provide one-on-one tutoring for kids. AI provides the very real prospect

of being able to do that, right? Because obviously now, right, if you have a kid that's like super interested in

something and they can talk to, you know, an LLM about it and they can ask an infinite number of questions and they

can get instantaneous feedback. Um, and in fact, you can even tell an LLM it's like, you know, teach me how to do the

following. And you can say, you know, wow, that's like I don't quite understand what you're saying. Like,

dumb it down for me a little bit. Um, okay, now quiz me, you know, do I actually understand this? Like, people

can just do this today, right? Um, and so I I think there's this like massive opportunity for for parents, you know,

in in many walks of life to be, you know, with with with a little bit of time and focus, uh, to be able to say,

okay, you know, my my kid's probably still going to go through a traditional education system, but I'm going to

augment this with AI tutoring. Um, and of course there, you know, and of course there's going to be tons of startups,

right? And there already are that that are going to try to build on all the all the products and services for this. Khan

Academy, you know, on the nonprofit side has a big push to do this. Um, and so, you know, I think the the broad answer

might be a hybrid approach with schools plus onetoone tutoring through AI. Um, there's also this great, you may have

heard there's this great school new private school system called Alpha, um, in which everything I just described is

kind of the basis of their philosophy, which is, you know, it's a combination of in-person schools and teachers, but

it's also, you know, heavily based on AI and AI tutoring. And so I I think there's like a there is a magic formula

in here um that I think is going to apply much more broadly. Um and I and it really for parents interested in this I

now would be a great time to really start to think hard about that um and and to look at the options.

>> It's interesting because there's all this concern that young people uh jobs are not going to be there for them. AI

is replacing them. On the flip side, there's what you're describing here. It feels like people coming into learning

today are going to be move so fast and learn so much more. And where where do you sit on this

divide of like young people are in big trouble or they're actually going to be the ones winning in the end?

>> Yeah. So the job the job substitution job loss thing is just it's very reductive. It's it's I think it's an

overly simplistic model. And again it goes back to what I said at the very beginning which is we've actually been

in a regime for 50 years of very slow technological change in the economy. And so you know again like I said it's like

at a half the rate of of the previous era and then a third the rate of like 100 years ago. And so we're we're coming

out of this kind of phase where we've had like almost no technological progress in the economy. We've had

remarkably little job turnurn as a result of that relative to to any historical period. And so even if AI

like ticks up, even if AI triples productivity growth in the economy, which would like be a massively big

deal, it would take us back to the same level of job turnurn that was happening between 1870 and 1930. And if you go

back and you read accounts of 1870 to 1930, people just thought the world was a wash with opportunity. Right? at that

rate of technological transformation, kids were able to like develop new careers into new areas of of of the

economy, building new kinds of products and services. I mean, you know, a huge part of our of everything in our modern

world today was kind of invented and uh and proliferated kind of during that period. Um, and so even if AI like

triples the pace of economic change in the economy, it's going to just translate to like a much higher rate of

economic growth is going to transfer translate to a much higher rate higher rate of job growth. And you know there

there will be some level of like task level and job level substitution that will take place but that will be swamped

by the macro effects of economic growth and innovation uh that will happen and that then corresponding to that there

will be you know there there will be hiring blooms you know I quite honestly I think all over the place and then

again go back to the the other thing which is like this is all happening in the face of declining population growth

and and and increasingly population shrinkage. Um and so human workers in many many many countries over the next

you know 10 20 30 years are going to be at more and more of a premium u literally because you're going to have

shrinking population levels. You know we don't really want to get into you know politics particularly but it does feel

like the world broadly is going is is going to reverse course on on on the rates of immigration that we've had for

the last 50 years. it seems to be kind of a broad-based you know kind of thing happening um you know kind of with you

know rise in nationalism you know concerns about the rate of immigration and immigration historically in

countries like the US you know it's it's kind of eb and flowed over time based on kind of how you know kind of how the the

national mood shifts and so if you sort of combine in a country like the US or any country in Europe if you combine

declining population with less immigration you the the remaining human workers are going to be at a premium not

at a discount um and so I think I think that combination of kind of faster productivity growth, faster economic

growth, and then slower population growth and less immigration. Um, actually means there's going to be much

less of this kind of dystopian, you know, no jobs thing. I I just think it's probably totally outpaced.

>> That is extremely interesting. So, what I'm hearing is you're not super worried about job loss. Is the key here that the

timing kind of just works out, this population decrease, you know, like all these kind of have to line up for there

not to be this massive job loss with AI? >> Yeah. Well, look, if we didn't have AI, we'd be in a panic right now about

what's going to happen to the economy. Right? Because what we what we'd be staring at is a future of depopulation

and like depopulation without new technology would just mean that the economy shrinks. Right? So so it would

mean that the economy kind of itself kind of shrinks over time. You know the opportunity diminishes. There are no new

there are no new jobs. There are no new fields. There's no new there's no new source of consumer demand for spending

on things. Um and so you you would you would you would be very worried about going into period of like severe decline

of stagnation. Um, and you know, you know, essentially you'd be looking at these like very dystopian scenarios of

like an economy kind of self- euthanizing itself uh over time. Um, and and so you'd be very worried about like

the opposite of what everybody, you know, thinks that they're worried about. The only reason we're not worried about

that is because we now know that we have the technology that can substitute for the lack of population growth and then,

you know, also for the for the lack of immigration that's likely. And so, you know, I would say the timing has worked

out miraculously well in the sense that we're going to have AI and robots precisely when we actually need them,

uh, to keep the economy from actually shrinking. Um, and and I just think like that that's just like a a fundamentally

a fundamentally good news story. Um, to get to the mass job loss thing that people are worried about, um, on the

other side of things, you know, you have to you'd have to look at like far far far higher rates of productivity growth.

you'd have to look at rates of productivity growth that are 10 20 30 50% a year, you know, something like

that, which are, you know, orders of magnitude higher than we've ever had in any in an economy in the history of the

planet. Um, you know, it's possible that we get that. I mean, look, I'm, you know, I I have my utopian kind of, you

know, kind of, you know, temptation along with everybody else. If if AI like radically transforms everything

overnight, then maybe you, you know, let's let's play out the kind of utopian scenario. Uh you get to a much higher

level of of of productivity growth. You get to a much higher level of technological change. corresponding to

that you'll have a massive economic boom. Uh you'll have a you know massive growth in the economy and then

corresponding with that you'll have a collapse in prices. Um and so the price of goods and services that are that are

that are sort of you know whatever you want to call it affected by or commoditized by AI the prices of those

goods and services will collapse right there'll be price deflation and then as a consequence of price deflation

everything that people are buying today gets a lot cheaper and that's the equivalent of a gigantic increase in

wealth right across the society right think it this way this is actually worth talking about because people I think get

get kind of sideways on on this issue so if AI is going to transform the economy as much as the you know whatever or

utopians or dystopians or whatever kind of think that it will. The necessary economic calculation of what happens is

massive massive productivity growth. The consequence of massive productivity growth, what that literally means

mechanically is more output requiring less input, right? So you get more economic output for less input, right?

So you're substituting in AI for human workers or whatever. And as a consequence, you get like this massive

boom in output which with much lower input costs. The result of that is you get lots of goods and services in all

those affected sectors. The result of those gluts is you get collapsing prices, right? The collapsing prices

mean that the thing today that cost you $100 now cost you $10 and now cost you $1. That's the equivalent of giving

everybody a giant raise, right? Because now they have all this additional spending power. That additional spending

power then translates to economic growth, right? The development of new fields. Everybody's like materially like

much better off very quickly. And then by the way, if you to the extent that you do have unemployment coming out the

other side of that, it's it's now much cheaper to provide the kind of social safety net to prevent people from being

emiserated, right? Because the prices of all the goods and services that like a welfare program has to pay from, they're

all collapsing, right? And so the price of healthcare collapses, the price of housing collapses, the price of

education collapses, the price of everything else collapses because this this this this incredible impact that AI

is having. And so in this kind of utopian dystopian scenario that people have, it's not there there's no scenario

in which like everybody's just poor. In fact, it's it's quite the opposite, which is everybody gets a lot richer

because prices collapse and then it's actually much easier to pay for the social safety net for the people who,

you know, for some reason can't find a job. And so, like like maybe we end up in that scenario. I mean, the the kind

of optimistic part of me says, yeah, maybe AI is that powerful and maybe the rest of the economy can actually change

to to accommodate that and maybe that'll happen. But the result of that is going to be a much better news story than

people think it's going to be. Um, and again, everything I've just described, by the way, is like just a very

straightforward extrapolation on very basic economics. I'm not making any like bold predictions of what I just said.

This is just like a straightforward mechanical process that that that plays itself out if you have higher rates of

productivity growth, which are necessarily the results of higher grade rates of technological growth. And so, I

think we're I think we're looking at, and to be clear, I think we're looking at a world that's not like radically

transformed the way that maybe the utopians think that it will be or the the dystopians think it will be. I think

it'll be more incremental for races we can discuss. But I think that incremental is overwhelmingly I think

that process is going to be a good news process. And then even if it's much faster, it's also going to be a good

news process. It'll just be a good news process in the other way that I described.

>> I love hearing optimism and good news. I will also add that you've been I was researching you ahead of this chat and

you've been right so many times about where the world is heading. That's why I'm especially excited to talk to you.

I'll give you a short list. I imagine there are many more things. Uh okay. Okay. So, one, you were right about the

web and web browsers becoming important. You were right about software eating the world. Check.

You uh in 2011, you said that in 10 years we're going to have 5 billion people using smartphones. And I believe

the actual number ended up being six billion. [laughter] You also you had this debate with Peter

Teal that I came across where you were debating whether technologies stop progressing or if new technology will

continue to emerge. and you were arguing there is progress. Progress will continue. And he he was like, "No, I

think we're done with cool technology." You were right. Uh imagine there are many more things you were right about.

So, so again, I'm just I I love hearing your predictions because I feel like they're actually going to turn out to be

correct. >> So, I should start by saying I've been wrong about tons of things, but you

know, I buried those out back behind the shed. [laughter] >> Delete them from the internet. No web

browser can discover them. >> Yes, I have them nuked out of the internet archives so they they're never

seen again. Um, so, uh, you know, I'm wrong plenty of times also. Um, but yeah, I mean, look, I think, yeah, some

some of those I got right. By, by by the way, I will say on the on the Peter one, I I have come I've come much more around

to Peter's point of view. >> Um, I would probably argue that one like quite a bit differently today than I

did, and I would give his view I think I think a lot more credit. Um, and and it actually goes to kind of the discussion

that the kind of conversation we just had, which is the the real form of what Peter was arguing was we have lots of

process in bit. We have lots of progress in bits, right? But we have we have very little progress in atoms, right? Um and

and that's the real core of what he was arguing. And I think I I I think I I was a little bit I don't know missing that

or kind of you know kind of glossing that over a little bit um because I was so focused on making sure people

understood no there actually is still progress happening in in bits. But I think you know a lot of his critiques

around the lack of progress in Adams is real and and again this goes back to this thing of like in the and he you

know he's talked about this for a long time. In the last 50 years there has just been very little technological

innovation in most of the economy. there's been very little technological innovation in particular anything

involving atoms that you know there's been very little real world technological change there just there

just hasn't been like the the the built world is just not that different today than it was 50 years ago and if you and

again if you contrast that you know if you if you compare and contrast 1870 to 1930 it was a dramatically different

world if you contrast 1930 to 1970 it was a dramatically different world if you contrast 1970 today it's not that

different right and look you just see that you could just like walk around and it's just like oh yeah there's a bunch

of buildings that were built built in like 1960, right? And there's a bridge that was built in like 1930 and there's

a dam that was built in like 1910 and there's a city that was founded in, you know, 1880 and like [laughter]

what have we done, right? Like where are new cities? Where are new dams? Where, you know, where's where's the California

highspeed rail? Like you know, you know, like what's going on here? And so like I think he is I I think he is right about

a lot of that. Um, again, this is also why I think that AI is not going to have as rapid an imp. It's not going to be

again this kind of utopian or dystopian view of like everything changes overnight. I think it just kind of can't

happen because of the reasons that Peter articulates which is there's just there's so much about how the world

works that's basically just like wrapped up in red tape like bureaucratic process, rules, restrictions. um you

know the the the politics um by the way you know unions cartels opolies there there's all these

structures in the world that are kind of economic or political or regulatory structures that basically prevent things

from changing and so I mean let's take let's take a great example like a AI's impact on the healthare system like by

rights AI is going to have a dramatic impact on the healthare system and in and in in very positive ways but you

know large parts of the medical system today are they are cartels, right? And so there's like a there's the doctors

are a cartel and like nurses are a cartel and like hospitals are a cartel and then there's this push to like

nationalize all the healthare systems and then you've got, you know, then you've got a government monopoly, right?

And it's like and and and guess what cartels of monopolies don't like is they don't like like rapid change, right? Um

and so, you know, you show up as a kid and you're like, "Wow, I've got like this new technology to do like AI

medicine." And they're like, "Oh, well, does it threaten Dr.'s jobs?" Well, in that case, we're going to we're going to

block it. So, and I think a lot of consumers, by the way, you know, I I I see this in my life and you you'll

probably see this in your life also, which is, you know, like Chet GPT is like almost certainly a better doctor

than your doctor today, but like Chad GPT can't get a license to practice medicine, right? So, it can't substitute

for a doctor. It can't prescribe medications, right? It can't, you know, perform procedures, right? And so there

there there are these any anyway so Peter Peter I think was very articulate and has been for a long time on like no

there are actually real structural impediments in the economy and in the political system that we have that

actually prevent any the rates of change that are anywhere near the rates of change that people had in the past. And

and you can maybe say optimistically you know maybe the presence of it of the new of the new magic technology of AI maybe

it causes us to revisit a lot of these assumpt assumptions for the first time in decades to really say okay is this

really the world we want to live in? Don't we actually want to get to the future faster? So maybe that would be

the optimistic view. >> It's time to build. Somebody famously said, I uh in my calendar, I actually

have that as my [snorts] when I start to work. It's time to build. That's my block in the morning of the day. Thank

you for that. >> Okay. I love I love the way you go from just like macro to just like end of one.

And I want to go to end of one. A lot of the listeners of this podcast are product managers. They're engineers.

They're designers. They're not a lot of There's a lot of founders, but there's also a lot of non-founders. There's a

lot of people building product that aren't founders and uh obviously a lot of people are worried about where their

career is going. Is one of these roles going to disappear? Is one of these roles going to do really well? How do I

stay up to date? You're close with a lot of teams, a lot of product teams. What's your sense of just the future of these

three very specific roles? Product manager, engineer, designer. >> This I think is a really funny question.

So these three roles in particular obviously are kind of the central roles for for building you know for tech

companies. So, the way I've been describing it is, you know, you know the concept of the Mexican standoff, right?

Which is the the movie scene where the, you know, the two guys have guns pointing at each other's heads.

>> Um, and then there's, if you watch like John Woo movies, he loves to have he does the three-way Mexican standoff

where you've got like a triangle, you know, people like, you know, and of course it's John Woo movie, they've got,

you know, guns in both hands. >> So, they're all each each is aiming at the other two.

>> Yeah. >> Um, and you got this kind of standoff situation. And so the way I've been

describing this is there's like a Mexican standoff happening between those three roles between product manager,

designer and coder. Specifically the following which is every coder now believes they can also be a product

manager and a designer right because they have AI. Every product manager thinks they can be a coder and a

designer. And then every designer knows they can be a product manager, right? And a and a coder, right? And so people

in each of those roles now, you know, know or believe that with AI they they don't need the other two roles anymore,

right? they they they can do that because they can have AI do that. And then of course and then of course

there's the real irony which is you know all the the all three of them are going to realize that AI can also be a better

manager, right? So they're going to they're going to end up a aiming the guns up the order chart. But that's

probably that's the next phase. And what I think is so fascinating about this Mexican staff is they're actually all

kind of correct I think right which is AI is actually a pretty good you know it's now it's actually now a really good

coder. it's actually now a really good designer and it's also a really good product manager, right? It's actually

good at doing all three of those things or at least doing a lot of the tasks involved in in in those three jobs. And

so again, this this goes back to the the the superower this kind of idea of the supermpowered individual. Uh where if if

I'm a coder like you know I mean step one is like I need to make sure that I really understand AI coding and like

what that means and what how coding is going to change in the future. you know that that I need to you know

specifically how to go from being a coder who writes code entirely by hand to being a coder who you know

orchestrates you know a dozen instances of of of you know coding bots you know you know there's there's a change in the

actual job of coding itself which is which is happening right now but the other part of it is okay how do I become

that superpowered individual how how do I become a coder that also then harnesses AI so that I can also be a

great product manager and I I can also be a great designer right and then the same thing for the product manager which

is how do I make sure that I can now use coding tools how do I make sure I can also, you know, do AI AI based design.

And the same thing for the designer, which is how do I use AI to be be also become a coder and also become a product

manager. And then what you get is maybe the maybe the those individual roles change like maybe those are not anymore

sort of stovepipe roles the way that you know they have been for the last 30 years or whatever. Uh but what happens

is the the talented people in any of those roles become superpowered and they become good at doing all three of those

things. Um and then and then those people become incredibly valuable because then those are people who can

actually like you know build and design right new products right from scratch which is like the you know which is

which is the most valuable thing. And so I I think I think that's I think I think that's the opportunity.

>> So I love this answer. So what I'm hearing is essentially uh if you're amazing at any of these three roles you

will do well. >> Number one if you're amazing at these roles that's great but also you part

part of being amazing these roles is also being being able to fully harness the new technology right. So if you're

if you're a master coder today and you you don't ever get to the point where you you figure out how to use AI to

leverage your coding skills, you and and do more, right? Like at some point you are going to hit an issue, right? Here's

another way economists talk about this, which is there's the concept of the job, but the job is not actually the atomic

unit of what happens in the workplace. The atomic unit of what happens in the workplace is the task. And so and and

then what what the way the economists think about it is a job is a bundle of tasks. And everybody wants to talk about

job loss, but really what you want to look at is is task task loss, right? Tasks changing. I mean the the the the

classic the classic example of task changing. Classic example of task changing was once upon a time executives

never used typewriters or personal computers themselves, right? You know, if you were a vice president of a

company in 1970 or whatever, you did not have like a typewriter or computer on your desk typing things. You had a

secretary who you dictated memos to, right? And then there and then there was this change where like emails started to

show up. And what would happen was the job of the secretary then went from, you know, it went from, you know, the the

job of the secretary changed from sending out letters with stamps on them to like sending or receiving emails with

the other admins. And then and then the secretary would print out the email and bring it into the executive's office.

And the executive office would read the email and paper, scroll scroll the reply um and and and give and give that

message back to the secretary who would go back and type it into the computer on on on his or her desk and send it as an

email. Fast forward to today, none of that happens. Now executives just do all their own email. They still have

secretaries or admins, but they're now doing different tasks. You know, they're travel planning and orchestrating events

and like doing all these other things, you know, that that you know that the great admins do. And then and then the

task the task set ironically of the executive has expanded to do actually more of the clerical work themselves

actually like sit there and like type their own memos, which again 50 years ago they never never would have done

that. And so the executive job still exists. the secretary job still exists u but the tasks have changed and and I

think that's like a great example of what's going to happen in coding the tasks are going to change is what's

product management the tasks are going to change designer tasks are going to change and so the the the job can p the

job persists longer than the individual tasks and then as the tasks change enough then that's when the jobs change

and so at the at the level of individual you kind of want to think of like okay I have this job the job is a bundle of

tasks I need to be really good at making sure that I can like swap the tasks out, right? I can I can really adapt, use the

new technology, you know, get really good at AI coding, for example. I can, you know, and then and then you want to

kind of add skills. I can also get really good at design. I can also get really good at product management

because I've got this new tool. So, you want to kind of pick up more and more scope as you do that. And then, you

know, 10 years from now, is your job title coder or coder designer, product manager, or is it just I build products

or is it just I tell the AI how to build products? It's like whatever that whatever that job is called, who even

knows what it's going to be, but it's going to be incredibly important because the people doing that job are going to

be orchestrating the AI. And so that that that's the track that the best people are going to be on. Um and and I

think that that's the thing to lean hard lean hard into. >> I think people aren't fully grasping

just specifically software engineering and how much that is changing. Like it's pretty clear we're going to be in a

world soon where engineers are not actually writing code, which I think a year ago we would not have thought. And

now it's just clearly this is where it's heading. It's like there's going to be this artisal experience of sitting there

writing code which is so crazy how much that job is going to change. >> Yeah. So again here I go back and again

pardon maybe the history lesson but like I go back like coding. So [laughter] the first you may know that do you know the

original definition of the of the term calculator. Do you know what that referred to?

>> No. >> It referred to people. Right. So back before there were like

electronic calculators or computers or any of these things um the way that you would actually do computing the way that

you would do calculating like the way an insurance company would calculate actuarial tables or the military would

like calculate you know I don't know whatever troop logistics you formulas or whatever it was the way that you would

do it is you would actually have a room full of people um and by the way these like big rooms you could have hundreds

or thousands or tens of thousands of people doing this and you would actually you would actually figure out you have

somebody at the head of the room who was like responsible for like whatever the mathematical equation was and then they

would parcel out the individual mathematical calculations to people sitting at desks who were doing them all

by hand, right? And and those that that job title was those people were calculators, right? Um and so we've gone

from a world in which you literally have people doing mathematical equations by hands by hand. Then we got the first

computers. The first computers of course didn't have programming languages, right? They they only had machine code,

right? So the first computers were programmed with ones and zeros. And so the task of the programmer became do the

ones and zeros and then that became punch cards and you can still you know there's still people you know kicking

you know today who you know whose job as a programmer was to like deal with the punch cards and then you got actually

this big breakthrough which was called assembly language which was basically the way to do machine code but like with

some level of like English kind of added to it and then the best programmers did assembly language and then you know when

I was coming up it was higher level languages like C that compiled into machine code and that's what programmers

did and then I still remember when when scripting you know when scripting languages you know we developed

JavaScript at Netscape and then you know Python took off and Pearl and these other scripting languages but scripting

languages you know took off in the in the in the in the in the 2000s there was this big fight in in the technical

community which is is scripting real programming or not right because it's it's like it's kind of cheating right

because real programmers write code that compiles to machine code and like real programmers like do like memory

management themselves and they do all you know this this this whole craft of writing writing uh you know writing

writing C code and you know these these JavaScript or Python programmers are is doing this kind of lightweight thing and

does it even really count as as coding and of course the answer is yes it very much counted and now most coding is done

with the scripting languages right um which have you see my point the scripting languages have abstracted away

like five layers of detail underneath that that people used to do by hand and they don't anymore and then and then

there's and then to your point like AI coding is the next layer on that AI coding actually abstracts away the

process of actually writing the scripting code right and so in one sense this is a really big deal for all the

obvious reasons but on the other hand it's like okay this is the next layer of the task redefinition under the job of

programmer right now what's the job of the programmer it's to your point it's not necessarily to write the code by

hand but what it is now is all right now you know if you talk to the world's best programmers today what they'll tell you

is oh my job is I'm sitting there and I'm orchestrating 10 code bots right coding bots that are running in parallel

right and and literally they sit there and they shift from browser you know browser to browser or terminal to

terminal and they're and they're they're watch their their day their day job now is kind of arguing with the AI bots

trying to get them to like write the right code, right? And then and then debug it and and fix the problems and

change change the spec and and do all these things. And so now now the job of the programmer is to argue with the

coding bots, but like if you don't know how to write the code yourself, you don't know how to evaluate what the

coding bots are giving you, right? And so, you know, you asked about the 10, you know, our 10-year-old is, you know,

super into computers and super into programming. And what I'm what I'm tell, you know, he's he's using claude and

chat GPD and co-pilot and all these things. What I'm telling him is like, look, and by the way, he lo coding. He's

on Replet all the time doing vibe coding, you know, doing g doing games, you know, he's sitting there, you know,

it's hysterical, right? Because he's sitting there, it's a 10-year-old basically who's, you know, spends two

hours at dinner arguing with an AI for fun, right? Um, right. But but what I'm telling him is, no, look, you need to

still fully understand and learn how to write and understand code because the coding bots are giving you code. If it

doesn't work or if it's not doing what you expect or it's not fast enough or whatever, like, you need to be able to

understand the results of what the AI is giving you, right? in in the same way that somebody who's writing scripting

language code does need to understand ultimately how the microprocessor works. Um, and so again, it's it's kind of this

upleveling of capability where you actually want the depth to be able to go down and be able to understand what the

thing is actually doing even if you're not spending your day actually doing that by hand. And again, I look at that

and I'm like, okay, now programmers are going to be 10 times or 100 times or a thousand times more productive than they

used to be, right? And and and that is overwhelmingly a good thing. The the the the tasks are definitely changing. The

nature of the job is changing. Um, but are human beings going to be involved in like in the coding process and

overseeing the the AI coding and all that? And and the answer is of course absolutely 100%. Like no question.

>> So you're in the camp of still learning to code, still a valuable skill. >> Oh yeah, totally. Well, again, if you

want to be one of these super Look, look, if you just want to put your like self on autopilot and like I can't be

bothered and I'm just going to have AI write the code and it's going to generate whatever it does and that's

fine and I'm going to be, you know, I'm going to be if if the goal is to be a mediocre coder, then just let the AI do

it. It's fine. The AI is going to be perfectly good at generating infinite amounts of mediocre code. No problem.

It's all good. If if if the goal is I want to be one of the best software people in the world and I want to build

new software products and technologies that like really matter then yeah you 100% want to still be you want to go all

the way down you want your skill set to go all the way down to the assembly to assembly and machine code you want to

understand every layer of the stack you want to deeply understand what's happening at the level of the chip right

and and and the network and so forth by the way you also really deeply want to understand how the AI itself works right

because you want to right because if people understand how the AI works are able to they're clearly able to get more

value out of it somebody doesn't understand how it works, right? I mean, you're always more productive if you

know how the machine works, right? When you use the machine and so yeah, the the supermpowered individual on the other

end of this that wants to do great things with the new technology, yes, you 100% want to understand this thing all

the way down the stack because you want to be able to understand what it's giving you, right? And and and when

something doesn't work or when something isn't right, you want to be able to really quickly understand why that is.

Um, by the way, again, this goes back to education. AI is your best friend at helping you learn all that, right?

because it's like, oh, I need to understand, I don't know, like this isn't fast enough. Um, I need to go I

need to figure out as a coder, I need to figure out how to do a different approach to memory management or

something. And you can be like, well, you know, like I, you know, I don't quite know how to do that. Okay,

AI, let's spend 10 minutes. Teach me how to do this, right? Teach me what this all means, right? So, all of a sudden,

you have this like incredibly synergistic relationship with the AI where it's also helping you get better

at the same time as doing a lot of work for you. >> By the way, I was going to say I was a

big Pearl uh programmer. I was an engineer for 10 years and that was my my language of choice.

>> You do you remember I don't know when you were doing it but do do you remember at the at least early on do you remember

did you ever did you ever hit this where like coders were like looking down their nose at you being like

>> for sure for sure it's like this is so slow it's not going to scale what are you what are you spending all your time

on this thing? Yeah, exactly. And of course, you know, and again, it was sort of this thing where, you know, they were

they were sort of correct, which is at the beginning it wasn't, you know, fast enough or whatever. By the end, they

were definitely wrong, right? Which is it got much better, much faster, and you know, it's it swept the world. U you

know, most coding today happens as scripting languages. And and then by the way, the people along along the way, the

people who really understood the scripting languages and the people who understood all the lower level systems,

they were the ones who were able to actually make the scripting languages actually work really well, right? And so

that that was that was a great example of this kind of adaptation. And then and then again the result of that was you

know a far higher number of people writing code with scripting languages than were ever writing code with lower

level languages. And I I think this will just kind of be a more dramatic version of that. I love that Pearl was designed

by a linguist. I don't know if you remember that part and that's what made it so nice to to code with.

>> Well that's funny because of course it was so notorious for being impossible to understand. So [laughter]

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Coming back to these this kind of triad, the other element that I hear more and more of is just as is the skill of taste

and design and user experience. It feels like that's a very hard skill to learn and to me tells me design is going to be

much more valuable in the future. >> Yeah, that's right. And again here this this is a great example. So the again

the task level the the the the task level of like design the perfect icon, right, is going to be like all right,

the A's going to do that all day long. is g give you a thousand icon designs. It's going to be great. Like it's going

to be fantastic. Like whatever, you know, and there will still, by the way, there will still be some level of human

icon design or whatever, but like AI is going to get really good at that. But like what are we trying to do? Like the,

you know, kind of capital D design of like, all right, what is this thing for? And how does this how is this going to

function in a world of human beings? And like, you know, what what's going to is this going to make people happy when

they use it? Is it's going to make people feel good about themselves? Um, is it going to fit into the rest of

their life? Is it going to you know I don't know challenge them in the right way? You know all these kinds of higher

level questions that the great designers have always thought about like that the the job of designer right will involve

much more of those higher level more important components and and then again with with AI doing a lot more of the

underlying tasks. And so, you know, one way to think about it is, you know, I don't know, you you think of like, I

don't know, the world's best designers, you know, Johnny Ibe or whatever, you could be like, "Wow, like if I'm a

designer today, if I'm a 25-year-old designer and I and I aspire to be, you know, Johnny Ibean in a decade, um, it's

it's all of a sudden I have a new path that I can use to kind of get to to get there, which is I, you know, because

Johnny I did everything he did without AI." Now, you know, a young designer can be like, "Wow, if I really harness AI in

a decade, I'm going to be like the best designer the world's ever seen because it's not just going to be me. it's going

to be me plus being so super empowered by this technology to be able to do so much more. Um, and then so much more of

my time and attention is going to be is going to be able to be focused on these higher level things that most most

designers never get to. And I think that that's going to be another great example of that.

>> So maybe what I'm hearing here is kind of this T-shaped strategy of be if you want to be successful in any three of

these roles, be very very very good at that specific role, product management, engineering, design, and then get good

enough at these other two roles. >> Well, so I think that's great. I think that's really really relevant. And then

you know the Scott you know Scott Adams unfortunately just passed away um you know which which is a real tragedy but

um I was always I I referred for years to actually Scott's Scott Adams he had this famous um he had this famous kind

of career advice he would give people which I I think makes a lot of sense which which doveetails with what you're

saying which is he he used to say he used to say it's like look he said um you know I I could he he said you know I

could have been a pretty good cartoonist um or I could have been like pretty good at business but the fact that I was a

cartoonist who understood business made me like spectacularly great at making Dilbert,

right? Because even the world's best cartoonist who didn't understand business could have never written

Dilbert. And then the world's best business people who didn't know how to do cartoons couldn't have done Dilbert.

It took somebody who actually had both of those skills to be able to make Dilbert, right? Which is one of the most

successful cartoons in history, right? And so so the the way Scott always described it was that that the from a

career development standpoint that the additive effect of being good at two things is like more than double, right?

um the additive effect of being good at three things is more than triple, right? Um because you you you be you become a

super relevant specialist in the combination of the domains. Um and and you you look you see this all I mean you

see this all over you know you see this all over the economy. Yeah. I mean you see this all over the economy but I'll

you know give you an example Hollywood you know just Hollywood as an example you know there are a lot of writers who

can't direct a movie and they can be very successful writers. There are a lot of directors who can't write a movie.

They can be very successful directors. But the superstars in the entertainment industry are the people who can write

and direct, right? And you know they they have a term for those. They call those auras, right? And that's you know

those are the people who are like the real creative forces that move the field. And so and so again and by the

way Hollywood actually it's really funny spend been spending a lot of time talking to Hollywood people about AI.

Hollywood has the same Mexican standoff going um right now that we that we described in tech except in Hollywood

for example for filmm it's the director it's the writer and the actor right because the director is now thinking wow

I don't need the writer anymore because the AI can write the script and I don't need the actor anymore because I can

have AI actors the writer is saying I don't need the director because [laughter] AI can direct the movie and

the AI can do the actors and the actor is saying I don't need either one of these guys I can have the AI direct the

thing I can have the AI write the thing and I'm just going to show up and do my performance right and so so it's it's

it's the same it's the same kind of tri triangular configuration. And again, what what's great about it is they're

all correct, right? Each person in each of those three fields is going to be able to expand laterally and pick up

those other those additional skills. And then as a consequence, you're going to have more people who can write and

direct or write and act or direct and act or do all three. And and I think, you know, to your point like your your

your T-shift thing, like I I think that's going to be true basically across the entire economy. And and and if you

think about the T is if you think about the T configuration, it's like yeah, the bre the breath the breath the top of the

tea is like how many individual domains are you familiar enough with to be able to use the AI tools to be able to do

really good work. And then the the this part of the tea is how deep can you go in at least one of those domains so that

you really really deeply know what you're doing. But like if you're like super deep on coding and you can use AI

to do design and you can use AI to do product management, right? That that's your T right there. and and you're a

triple threat at the top of the tea, but with this level of technical grounding underneath that. And I mean, at that

point, you're again, you're the superpowered individual, you're going to be able to just perform like feats of

magic, uh, for example, in terms of designing and building new products, you know, that people in my generation

couldn't have even dreamed of. And so I I I think I think that this is a universal kind of theory that I think

could can apply across the entire economy. >> I'm going to invent a new framework

right now. Okay, forget the T framework. Uh, I'm picturing an F sideways or an E where there's three two or three

I don't know, downward parts. And so what I'm hearing is get good at least two.

>> I think that's right. I think that's right. Yeah. The combination. Yeah. Um my my friend Larry Summers had a had a

different version of the Scott Adams thing which is he he used to tell people he said the key for career planning is

he said don't be funible, >> right? And you know that's he's an economist and so that was economics

speak and and what that means is what that means essentially is don't be replaceable. And so don't be a cog.

Right? So, and what that meant was don't just be one thing, right? So, if you're if you're if you're quote unquote, you

know, again, just a designer, it's just a product manager, just a coder, like then in theory, you can be swapped in or

out. But if if you have this if you have this Yeah. to if you have this E or F, you know, laying on it side kind of

thing. And if you have if you have this combination of things that's actually quite rare, then all of a sudden you're

not fungeible. Not not only you're not funible, like you're actually massively important because you're one of the only

people in the world who can actually do that combination of things. Um, and yeah, that that your ability now to

become one of those people is like just titanically enhanced uh with AI as compared to anything we've ever seen

before. >> This is so interesting because I've worked with people that are good at

these two skills and they were always called unicorns at the company. She can code and design. Oh my god. And what I'm

hearing here is this is what you need to become. You need to become really good at at least two things there. I think

you use the term smoke stack or something where it's like PM over here, engineer design. And what I'm hearing

here is you need to get good at at least two of these skills. the silos of these two roles are disappearing.

>> That's right. That's right. And again, I can't I can't overstress the following for for anybody listening to this. The

thing about AI that I think people are just like not getting enough benefit out of yet is just it will teach you.

[laughter] Like this is amazing. Like there's never been a technology before where you can

ask it like teach me how to do this thing, right? So it's I always feel like it's like it's like people spend too

much. It's one of these things where it's like so much focus on figuring out how to use like a large language model.

is like, okay, what am I going to try to get it to do for me? Right, which is of course very important, but the other

side of it is what can I get it to teach me how to do, [snorts] right? And it's it's just as good at that, right? Um,

and so again, this is this level this level of latent superpower like you know, people who really want to like

improve themselves and like develop their career should be spending every every spare hour in my view at this

point talking to an AI being like, "All right, train train me up like tell me tell supermpower me, tell me how to, you

know, train me train me how to be, you know, I'm a coder. Train me how to be a product manager." It will happily do

that. It's it knows exactly how to do that. You know, run me, you know, make me problems, you know, make me

assignments, then evaluate my results, right? And it will it will do that just as happily as it will do work quote

unquote for you. >> Two tricks I've heard along those lines. One is uh to watch the output. What the

agent is doing and thinking as it's doing the work. So, if you're not an engineer, is just sit there and watch it

think and make decisions. And it's almost become this like layer on top of learning to code is learning to see what

the agent is doing and thinking because that teaches you about architecture. And the other is uh a couple podcast guests

have mentioned this. When you get stuck and then you figure out how to unstuck yourself, you ask it, "What could I have

done differently? What could I have said that would have avoided this error in the first place?"

>> Yeah, that's right. That's right. Yeah. Look, on that first one, and this again, this is what I'm doing with my

10-year-old. Yeah. Look, if if if you ask an Yeah, this is this is a really good point. So, if you ask an AI, write

me this code, and then and then it doesn't and it comes back and it doesn't work right. Like if if all you know is

like single function I asked and it gave me back something that's not good like what do you like what do you even do

with that right like you don't understand why it gave you that result do you really understand even what do

you even understand what to tell it to try to get it to do something different but to your point like if you actually w

if you actually watch what it's doing um and and and then and then you you have the grounding you know kind of that leg

of the of your ear or your F um if you have that grounding then you can be like oh I see what it's doing I see where it

made the mistake I see where it went sideways and then you're all of a sudden able to intervene and able to say no no

that's not what I meant do this other thing right and so and again this is this this this is a big part of having

having the actual kind of you know synergistic relationship um is that you understand and by the way look I mean

this is like everything I'm saying is you know everything everything that we're saying right now also is the same

as if you're working with human beings right like you know if you and I are colleagues and I you know ask you to do

something you'd come back with something completely different like I I do need to understand what was happening in your

head right in order to in order to be able to get do need to give you give you feedback right if I just tell you oh

that's wrong it doesn't like nothing happens. I need to actually understand I need to have theory of mind, right? I

need to understand what you were thinking in order to really give you the right feedback. Um and so and and you

know and again the great thing with AI is AI will happily sit there and explain all day long why it's doing what it's

doing. It'll you know it'll happily critique itself. [laughter] You know, you can do this. By the way,

this has a very fun thing where you can have have one AI critique the other AI, right? Um, which is another thing, which

is like you have one AI write the code, you have another AI debug the code, [snorts] and so you can actually use you

can play the AIs off against each other and get them to argue with each other. Um, and yeah, the these are all these

are all the kinds of skills that are going to become, I think, incredibly valuable.

>> I think people call those LLM councils. Yes. >> They're talking to each other.

>> Yeah, that's right. That's right. >> I do feel like if I were like I'm I have no design background. I've always wanted

to design. I would I've always wanted to be a great designer. Uh, it feels like that's the hardest one to learn of all

these three by just watching and talking, right? Because there's a lot of exposure hours as as folks have used

this term just like how do you learn to be a great designer? That feels like that's going to be really hard and

valuable. >> So, my my true confession is I've always kind of wanted to be a cartoonist,

>> but I have no like art skills, but as we're talking, I'm like, it might be time. [laughter]

>> Their time has come, Arc. >> Yes. >> I want to pivot to founders, your maybe

your bread and butter. You spent a lot of time with the most cutting edge AI forward founders. I'm curious to what

you see them do, how you see them, some way they operate that's maybe blowing your mind about how the future of

starting a company looks, how the future of AI forward companies look. >> Yeah. So, this is a great very, you

know, topical topic that's all playing out in real time right now um on on the leading edge. So, I I think there's like

three layers of it and see see if this makes sense. I think there's like three layers of it. I think layer one is

they're thinking all right how how does AI redefine the products themselves right um and and this is kind of the

this is kind of the timehonored you know kind of thing that happens at technology transitions and this is kind of what you

know a lot of venture capital is based on which is um you know okay there's a new technology that comes out and you

know maybe it's the personal computer or the iPhone or the internet or now it's AI and it's like all right um is this a

new capability that gets added to existing products right so all of a sudden you've got I don't know an

existing you software business and now you got your you know PC version of it and now you got your iPhone version of

it and you just kind of keep on going and you know you kind of add the new technology kind of gets kind of added

into the mix um you know it's kind of another ingredient into an existing formula and and of course you know a lot

of new technologies are like that right um you know I don't know when I don't know when flash when flash storage came

out or something you know it didn't really you didn't really redefine the the software industry because people

just went from using you know hard disk using flash storage or something um uh but when the internet came out like

basically old school onrem software for the most part you know not not entirely but like a lot of it died and just got

replaced by like web software um right and so so sometimes you get the kind of it's additive to an existing thing

sometimes you get the actually it redefineses an entire product category redefineses an industry the actual you

know in many cases the companies themselves turn over and so so so you know so there's sort of this question

and like you know an example you just mentioned nano banana so like a great example is there you know there are

these businesses like you know just take Adobe like you know Photoshop is built a whatever a 40-year franchise in image

editing. Um, okay. Is AI a sort of a feature now that gets added to Photoshop to be able to do AI based image editing

or, you know, do you just like stop editing images entirely because you're using Nano Banana and your all images

are just being generated and it's just easier to just have AI generate a new image than it is to try to edit edit an

old one. So I think you know there's many areas of of tech in which that question is being asked and you know the

answers I think will vary by domain but u you know obviously as as a venture firm we're batting hard on many of these

categories being being totally reinventsted and a lot of the a lot of the best founders are trying to figure

out how to do that. So that so that's kind of AI you know changing the definition of the product. I think the

next layer is actually a lot of what we've already talked about which is AI changing the jobs. Um, and so it's, you

know, a lot of what we've already talked about, but like, okay, if I'm a founder of a company and I've got, you know, if

I have, you know, room in my budget for 100 coders, you know, how do I get those coders to be super empowered AI coders,

not, you know, not the kind of coders I used to have? And if they're super empowered AI coders, then does that

mean, you know, do I still need the hundred? Maybe now I only need 10. Or does that mean I still want 100, but now

they're doing 10 times more, right? And so that, you know, as you know, like a lot of the best founders are are working

on that right now. And then I think the third shoe to drop hasn't quite dropped yet, but it's it's you know it's kind of

the big one which is like all right like the the the the basic idea of having a company right you know does that change

and and again here you've got this concept of the superpowered individual which is like okay um you know can you

have entire companies where you have basically the founder does everything right because what the founder is doing

is like overseeing an army of AI bots and and there's sort of this you know there's kind of this holy grail in our

industry that's been running for a long time which is like can have the can you have like the one person billion dollar

outcome and you know we've had a few of those over the years Bitcoin is probably the most spectacular example you know

with Ethereum right behind it um you know which wasn't quite one person but you know a very small team you know you

had you know kind of Instagram and WhatsApp that had very big outcomes with very small teams you know every once in