Inside Anthropic's Unprecedented AI Growth: Insights from Head of Growth

A lot of companies claim to be the fastest growing companies of all time. Anthropic actually is. You guys were at

a billion ARR at the start of 2025. The last number I've seen is 19 billion ARR. That's 1 to19 billion in 14 months.

Historically, we were very much the smallest, least wellunded player in this space. We didn't have the free cash flow

or the distribution of a Meta or Google. We didn't have the first mover advantage of an OpenAI. It's a complete miracle

that we've gotten to the stage that we have. give us just a glimpse of what it's like to be leading growth inside of

Anthropic. >> This is the hardest job I've had in my life. To come into anthropic, you need

to understand that 50 60 70% of how you operate in the past, just throw it out the door.

>> One of the cleverest growth moves you all made was this idea of importing memory from chat GPT. Activation is a

really big challenge in AI. We are starting to look at how do we automate growth. Our growth platform team is

driving this effort called cash which is claude accelerate sustainable hyperrowth. How can we use claude to

automate growth experimentation and it's delivering results. You're basically living in the future. We always talk

about the exponential. The product value that we will deliver in 2 years time is probably like a,000x what it is today.

The funniest thing is I've noticed internally linear charts are just not cool. Everything is log linear. Just

show me at log linear scale. Today my guest is Amole Evasari. Amole is head of growth at Anthropic which is

on the most unprecedented growth run in history. In the past 14 months, they grew from 1 billion to over 19 billion

in annual recurring revenue. Just in the past few months, their revenue doubled. They've been growing 10x year-over-year.

This is unheard of at this scale. By the time this episode comes out, their revenue will be even higher. To put this

scale in perspective, companies like Atlassian and Palunteer and Snowflake, which have been around for 15 to 20

years, each do something like 4 1/2 to 6 billion in ARR. Anthropic is adding this much ARR every few months. And if that

isn't interesting enough to you, Amole who leads growth at Anthropic is an incredible human. He previously led

growth at Mercury and Masterclass. Before that, he was a founder and an investment banker. And most

interestingly, something that most people don't know about him is that Amole suffered a severe brain injury. He

had to spend 9 months relearning how to walk and work and just not be nauseous all the time. He shared this story in a

guest post in my newsletter a number of years ago. We actually chat about this during the conversation. These are my

favorite kind of conversations because Amole and his team are living in the future and he's come to tell us where

things are heading and what's going to change. And in this episode, AMOLE shares an unprecedented look at how a

company like Anthropic operates and grows, including how they think about growth, what parts of the job they've

automated, the future of the product and growth roles, how Mole got the job in the first place by cold emailing my

Kreger, and so much more. A mole is wonderful, and just try to count the number of times that he blew my mind

during this conversation. Before we get into it, don't forget to check out Lenny's productass.com for an incredible

set of deals available exclusively to Lenny's newsletter subscribers. With that, I bring you Amole Avisari.

Amole, thank you so much for being here and welcome to the podcast. Pleasure to be here. Head of growth at Anthropic. No

big deal. I've had a lot of people come on this podcast from companies that claim to be the fastest growing

companies of all time. And Anthropic actually is. is if you look at the trajectory, I just have some of the

numbers here just so people understand how absurd this is. So you guys were at a billion ARR at the start of 2025, then

hit something like 4 billion mid2025, then 9 billion ARR at the end of 2025. And the last number I've seen is you

guys are at 19 billion ARR, which uh just to put a couple pieces of context here. One is that's from1 to$19

billion in 14 months. Um I have so many questions. First of all, the story of how you

actually landed this role is really interesting. Talk about how you how you got this role.

>> Yeah, it's a little unorthodox. So, it was funny when I when I did my onboarding, they they walk through what

percentage of the cohort came through referrals, what percentage came through applying on the website, what percentage

came through uh sourcing. And I was on none of those. And I was like, okay, this is interesting. And basically the

the way that I I got to was that I was actually a user of Claude and I was using a lot. I was like, man, these guys

like great product, great company, but they they really like obviously don't have a growth team. And uh what I did

was I just sent Mike Creger a cold email. He was the chief product officer. I sent him a cold email saying like,

"Hey, love what you guys do. Love the product. I think you guys badly need a growth team. Want to chat?" And uh I

didn't expect he would respond. And uh you know, he responds and says, "Hey, yeah, I'm interested. Let's let's talk."

And it's funny, I didn't know. I mean, I wouldn't have known. They were not hiring for a growth team. There were no

growth GM roles listed, but they were just at that time starting to think about hiring a growth team. So, it was

very good timing. But yeah, one one spoke to spoke to Mike and and one thing led to another. He said, "I'm the only

PM that he's hired from from cold email and I I feel very lucky that he decided to respond to my email."

>> I did not know the story. That is that is another uh absurd fact. Uh clearly you're good at cold email. What did you

do in this cold email to get his attention? I would say like I've basically perfected cold email over the

years. So I was a when I was a founder, I I had to get really really good at this. So I I sent a lot of cold emails

out and just honed the the the subject line, the message and and the tone and and so basically I've in the subject

line the first thing is like from a conversion standpoint, someone sees the email, they need to click on it. And so

I have a copy that I've tested that is like very very high uh open rate. And so >> wait, what is this copy or is this a

secret? >> It's a secret I think. >> Okay, we'll keep it we'll kind of keep

secret. Um so that's one getting them to open. I think the second is then the tactics of you need to understand like

where are people getting outreach and if you if everyone's getting outreach in one area and then uh you reach out to

them there then then you're not going to get as high of a response rate. So you think about like LinkedIn, if you think

about like work email, these are things that everyone is emailing. So there's there's ways to get people's personal

emails out there. And so like that's one thing that I did. And so, okay, I've got his personal email. I know the copy that

works. And then it's just keeping it very short on here's who I am. Here's why I'd be a good fit and and we should

chat. And and these things typically don't work. And then you you should always follow up a few times. I think my

rule of thumb is like if I really care about it, I should just keep keep reaching out to them and until they tell

me like, "Please stop." And so I would have I would have kept doing that, but he responded the first time. It makes

sense that a talented growth person would be very good at cold email and getting people's attention. So that's

almost like an interview step as just did I want to read this email. This episode is brought to you by our

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to make your app enterprise ready today. Okay. So, give us just like a glimpse of what it's like to be leading growth

inside of anthropic right now, the most by far fastest growing company in history. Just what is it like?

>> Yeah, I'd say I'd say it's very much a companywide effort, right? So, like yes, we we are the growth team. We have done

great. I think we've driven a lot of impact but honestly man we can't claim too much credit for the success of the

company like we we as Anthropic are really a model company and an intelligence company first and and

foremost and so the the lion share of of like what has driven our success is our research team we have I think the best

research team in the world we have great teams on inference and compute and then there's many other teams like claude

code go to market etc who I think deserve much more credit than us I think Just zooming out going to some of what

you said earlier that the growth trajectory has just been insane that that 10x year revenue growth trend has

been there since the beginning. I think 2023 was 0 to 100 mil. 2024 was 100 to one. Uh last year was one to to roughly

10. And like I I look back to when I joined in 2024 revenue was in the the hundreds of millions. and just that

trajectory. So, the end of 2024 and 2025, like week two of when I joined, we're going into 2025 revenue planning

and we have these like base case and aggressive case scenarios. And Daria is pushing the aggressive case scenario and

people are freaking out being like, how the hell are we going to hit that? And Dar's like, I think we can actually go

much higher than that. And I'm I'm coming in like this this place is crazy. Like, there's there's absolutely no way.

Um, and and and that happened, right? and and and then you you get to the end of 2025 and it's like okay law of large

numbers there's going to be a pretty big slowdown here based on you know your baseline rate of of 10 billion how are

you going to keep growing at this rate and like it just like has not slowed down and and you know those numbers are

public the the 19 billion number you you quoted is from the end of Feb so that is also out of date um and it's a look it's

absolutely insane like the the funniest thing is something that I've noticed internally is like linear charts are

just like not Cool. Like no one cares about linear charts. Everything is log linear. Show me at log linear scale and

that's that's kind of scale we think. And I think overall we're just you know really hanging on by the seat of our

pants. So we're trying to manage the growth and um do do the best that we can for our users. I was talking to somebody

at Anthropic about you and they said that basically anytime they want something to grow they ask you to help

and it works. So you talked about just like things are magical and amazing and like like Claude and all the tools you

all build are amazing innately and that's a big part of the reason they grow. I think many people listening to

this will be like what do you even do a mole with like a magical micro god that just can do anything for you? Why do we

need a growth person? What do you even do? Talk about just the stuff that you focus on and maybe like a couple of the

wins that your team has shipped that has helped accelerate growth. >> I would say like they're not fully

wrong, right? like we're we're very very lucky to have the best models in the world. We're very lucky to have products

like Claude Code and and Co-work. It it it certainly makes life a lot easier. Um having said that, I would say this is

like the hardest job I've had in my life and that's uh you know, having been a founder, having been an investment

banker and other things like that. Uh it's it's it's tough. And if I if I look at what do we do as a growth team here,

I think it's it's it's ultimately it's the same categories of things that you would think about at a normal company.

So we care about acquisition, how are we getting more more people in the door, the the intent of the people coming

through the door. We care about activation, the the signup flow, funneling people to the right products,

making them them successful, you know, we care about things like monetization, free or paid conversion, pricing and

packaging, all all of that stuff. The categories of work is the same. I think then the the probably the big

differences is I would say that like roughly 70% of what I I spend my time on is is what we internally refer to as

success disasters and that is where like things have gone so well that other things are breaking now and and I think

anyone who's worked at companies that have gone through rapid growth uh you think like Facebook or or Uber or Door

Dash early on like they understand this viscerally where scaling this much just brings a lot of challenges. So if you

think about each of those categories on acquisition, on activation, on monetization, there's just a ton of

firefighting jumping from like one urgent thing to another. And it's often like extremely painful and and like it's

funny because you look at all the charts, all the charts are like green, like fully up into the ride and

everyone's just like it's it can be quite tough emotionally still. And so you need to sort of step back and just

realize like we're very lucky to have these problems. But that's sort of 70% of my time I'd say is just these like

firefighting of success disasters. And I think the 30% remaining is just much more standard bread and and butter

growth work where it's like more proactive. So you think about okay if we have limited resources which which are

the products we have many different products. Which are the products we want to put some juice behind? What is our

long-term pricing and packaging look like? Especially given that the technology is changing a lot and and

behavior and engagement trends are shifting. And then you know things like we have a lot of new products coming up

like okay you you ship co-work now what like when is the right time that we should lean in as a growth team to start

optimizing the core adoption funnel for for co-work so it's probably yeah 70% just crazy firefighting 30% more more

breadandbut stuff. >> Okay I'm going to dig into a lot of that stuff. One of the cleverest growth uh

moves you all made recently was this idea of importing memory from chat GBT where you just made it really easy and

kind of jumped on this trend of people getting really excited about anthropic. Is there anything you could share about

this the behind thes scenes story of that feature? We're always thinking about what can we do to improve the the

cold start problem and improve the new user experience? I think that activation is a really big challenge in in AI. And

so, you know, that's like one one example of something that that we shipped that was very um you know,

specific to a moment in time. But ultimately that you zoom out, it's like, okay, how do you really how do you

really make it easier for people who are signing up to have Claude understand who they are and understand how Claude can

help them and get them to to the right place? >> I want to follow that thread activation.

This is something that comes up a ton when I talk to people leading driving growth on AI products. It's just like

like there are so much stuff trying to get your attention these days for people to get to a place where they okay wow

this is really going to be something I I want to keep using it. It proves to be really hard and it's also just

unreliable sometimes it's not going to be magical. It's AI. It's non-deterministic. I guess one is just

like uh how important is focusing on activation getting people to that aha moment with AI products? and two, what

are some things you've learned about how to do that well with with cloud and AI in general?

>> Yeah, it's a good question. I I think that activation it's it's critical, right? And and and defining that as like

early activation, call it day zero, day one product experience. I think that historically anyone who's who's been in

growth or been in product understands that that's that's usually one of the highest levers that you have to actually

even increase like longer term retention. And I think that that the importance of that has just gotten

exponentially higher. Now zooming out, I feel like one of the biggest problems in the industry is capability overhang

where the the models are just getting better so quickly and and it the the real challenge is on the product side of

how do we start to um diffuse those benefits to to to people where even internally like there's there's new

models coming internally and you're sitting there you're so busy and and when it when you when a new model's

available you you need to like really carve out time to be like what what can this do? how do I need to update my

priors? And and if you think about more broadly for most people, you may have a model that is like you may have AGI or

some, you know, model that can do all sorts of crazy things, but if if people's instinct is to come there and

be like, hey, what's the weather in SF? Then, you know, they're not going to get the the most out of of of the product.

And and so I think that it's it's it's tough because the model capabilities are rising so much. So like if I if I think

about okay back when we had I don't know say like opus 4 at that there's there's a series of things the model can do at

that point and and opus 4.5 unlocked a whole bunch of new things. you think about, okay, we sit there, we've got

this new model, Opus 4, the the time to then go and run a bunch of tests, figure out, okay, there's the capabilities from

this new model. What are the right on-ramps to to guide people to those features? You know, you run you run

tests, you get the learnings, you then ship a new flow. By then, you may already have the next model which

unlocks newer capabilities that makes all these learnings irrelevant, right? So, like it's actually just like a

really difficult problem to to stay on top of. I think that many of the same things, same old trends in in in growth

and activation remain I think accurate where to me it's like ultimately the some of the highest leverage is from

finding the right product or the right feature for the right user and uh I think that one learning you've seen this

time and time again across companies actually like the right friction helps and and adding more friction usually

works if you do it the right way. I think that's something I've consistently seen that we we've seen here as well. Uh

so to me, I think it's really un being able to identify which what are the characteristics of a user that allows

you to then recommend them to the right feature or product and not being shy about adding friction to to do that I

think is probably like the single biggest thing that that's important here. When I asked uh Ben Mann, one of

the co-founders, former podcast guest, what to ask you about, and this is what he highlighted is your experience,

especially at Mercury redoing onboarding and making it magical. And basically, he's in the same uh place as you of just

how important it is for people to understand what the AI tools capable of to help people decide to use it and

stick with it. Is there an example of something you changed in onboarding that helped significantly improve activation?

Yeah, it's a great great question and and I I like that he brings up Mercury. I I talk about their their product a

lot. So, worked on the growth team at Mercury. I think it's a fantastic product. It's something many people use

and the reason they use it is because it's a better banking experience than >> Yeah, I'm a I'm a very happy customer

just to put it out there. I love it. >> Great product. Highly recommend it. They have personal banking. Everyone should

go go and use it. >> Right. They just launched that. >> I I I and and and so I think that the

interesting thing about Mercury is like the core value is that it's a better experience, right? that that's the

reason you use it. You're not getting like better other things. It's just it's a better product experience. And so the

that ethos is very very deeply held within the company. It comes from uh a number of the founders. And um I think

that we we had a big push one quarter when I was there on on the onboarding flow. So onboarding flows for for

banking institutions and regulated entities are extremely complex. like the the the amount of time I've spent on the

difference between like a registered agent address and a legal address and a physical address like these things are

very very complex and we we basically looked at the onboarding flow and we were like okay we we've invested so much

in quality in the rest of the product but we haven't really done it here and this is the first experience that people

have and and so we said forget metrics forget growth forget everything else as the growth team on conversion we're

going to spend a whole quarter fixing quality in in this flow. And so that's all we did. Like forget the metrics.

We're just going to make this as good of an experience as we can and fix all these like you go back from one field to

the other field and adding in your beneficial ownership details. And it actually ended being like and probably

until I joined here like the the single most impactful quarter that I've ever had as a growth PM in terms of the

impact that it had. And so we saw a significant uplift from uh on basically our like onboarding started to to

completion from from just focusing on quality. And so that that to me is like a broader learning around quality drives

growth that I think I I've tried to to to bring to anthropic. I think for us at Enthropic um you know some of the things

that we've done in the onboarding flow uh is is basically like we we ask users questions around who who they are what

their interest areas are and we we then use that to recommend different products and features and like number of people

look at the flow and they're like you have so much friction it's such a long flow and like we have the data we're

kind of happy you with how that's performing. What is your kind of a philosophy on friction good friction

versus bad friction? I've just seen time and time again at every job I've been in in growth that adding friction and

adding the right steps uh leads to higher conversion and and higher funnel completion. So you want to get rid of an

I think especially if you have high volume you should test the majority of this and just learn and and see like

does this apply to your business as well. But you you want to you want to get rid of annoying friction that

doesn't add value. But the the like I think the most simple understanding people have is like just get just just

just solve time to value. Cut all the steps and just get them into the product and and like that doesn't work most

times. I think if you if you're if you've really thoroughly tested your flows, I look at the companies I've been

at masterass. If you go through masterclass's purchase flow right now, you'll go through all these steps in

this this quiz when you land on when you're trying to buy and it's like you're like, I came here to buy and it's

taking me through all these questions. What are you here for, etc. I think it's easy to look at that and be like, why

why do they have this? This is like a terrible thing. Just cut it all. And it's like no, like that's been

thoroughly tested and and actually there's like a significant revenue driver uh because it helps users feel

that the product is for them by understanding what their interests are and then recommending the content and

and classes there. One of the the growth PMs on our team left to to join Karm.com the meditation app. If you go to K's uh

you know their landing page and you go through their purchase flow, their login flow, you'll see a quiz. It's like not

not a not a a coincidence. But at Mercury, we also tested I think um I think you might posted on Twitter like

we broke out some steps in onboarding and just having one screen if you have like five or six different form inputs

and you you often break that into two screens and reduce the cognitive load to people that that is something that that

performs well. We added steps into the flow there that that actually performed well. Same at at anthropics. So I think

that the takeaway to me is like cut friction when it doesn't add to the experience of helping a user understand

why the product is for them. But if you can help users understand a product, why a product is for them and like how to

use it and and what's what's most relevant to them and it's going to add friction, uh don't shy away from it.

Test it, confirm that it works for you. But I I think this is like a something that like most growth practitioners

deeply understand >> and the for them is really important there. What you described is adding

friction to better understand who they are so that you know how to recommend the right thing for them.

>> Correct. Yes. And like that that like done right that just it just flows through right. So it helps you with

activation but then it helps you with life cycle. you know more about those users and why they're here and and like

you know most sophisticated businesses you can then even if someone drops off you can do like lookalike targeting and

you can get you can get them at the ad layer as well. So that that initial piece of how you understand the who the

user is is just like it's a juice that just keeps on giving if you if you then use it right further down funnel.

>> Everyone's about to go do a bunch of tearowns of Claude's on boarding, masterclass on boarding, Mercury on

boarding. Uh kind of as a tangent, I was at this PM dinner recently and I was asking all the PMs, how is your role as

a PM changed most with AI? Like where is AI most impacted what you do? And one of the PMs answered that is actually doing

competitive analysis doing a bunch of like tear downs of what other people are doing for pricing pages and onboarding.

So it's easy to do now. Just hey co-work would co-work for this or cloud. What would you use for that? Okay, this is

good. Help people pick which tool to use. If you want to go do a bunch of tear downs of other competitors

onboarding flows, what would you use? You can use you can use co-work for this, right? Um so you have co-work with

the Chrome extension. So if you task co-work with a Chrome extension, go and look for these these flows and uh show

me give me a view of what's working, what's not, that's definitely something that that co-work can do.

>> Cool. I think I imagine that's one of the challenges is like you have all these tools now just which one's for me.

Um by the way, the Chrome extension, I use it all the time. It's amazing. I want to drill a little bit further into

the growth org. >> There was this whole meme on Twitter the other day of just like you have one

growth marketer driving all growth at Enthropic and it's like okay that's crazy. What's like how many growth

people are there? What's kind of the rough org structure of the growth team? >> We're roughly maybe 40 people now. And

so we are I think structured very much like a traditional growth team in that we have sort of horizontals of of growth

platform and monetization who think about the the the the sphere of growth across the the entirety of our products.

And then we we have more sort of audience focused growth pods. You can think about like B2B growth. You can

think about cord code growth, knowledge worker growth, API growth. So, so really like these audiences to to keep a narrow

focus, which is the thing you have to do when you have so many different products. Uh, and then these these

horizontals that that sort of think about things um across across the board. >> And is it a cross uh a team of

engineers, designers, PMs? What's kind of like the functions within this growth or? Yeah, it's it's engineers,

designers, PMs, data. Um, I think that overall the shape of the org is quite similar to I'd say a traditional um

growth team. Probably the things that are maybe different is that we I think that we index a lot more towards larger

swings as opposed to smaller optimizations. Like if I think about a traditional growth team, I would have

probably done maybe 60 70% of my time on small to medium bets, 20 to 30 um% on on larger swings. And I think that for us,

we we we we flip it a lot like we we do much more the other way where it's sort of 7030 or more like 50/50 um rather

than than than indexing towards smaller bets. That's probably like one of the the biggest changes. I I think just to

highlight that what's interesting there is at the scale you guys are at like a 1% win is massive in the scheme of

things. So it's interesting that even at the scale you're at you're not focusing on these micro optimizations. It is easy

like you could easily focus on these small optimizations and then you tally them up at the end of the quarter and be

like look how much impact we made and like you could do that >> another billion no big deal.

>> Yeah. But but the the thing is like we're we're we've been tracking a 10x year on year and we we we you know

that's like the the thing that we we sort of keep in mind and I think it like ultimately comes down to our fix

fixation at this company about the exponential. I think if you look at anyone is talking about talking from

anthropic about basically anything we always talk about the exponential like it's is effectively as model

capabilities continue to grow on an exponential um and and the tools around them enable a better job of of diffusing

that into into uh useful use cases. You basically just keep unlocking new markets that where where the value of

those markets significantly dwarfs what the value of of the previous markets were. And like aentic coding is a great

example like it didn't exist you know a year a year and a half ago and then now just the value of agentic coding is is

bigger than the like previous market of of AI coding use and and so I think that is like the core thing here where just

that the future product value is an order of magnitude higher than it is today and I think about I don't know

like a a normal business like number of companies that I maybe mentioned or like you think about like a a trading app or

like a grocery delivery product like they're all many of the like the leading companies they're great businesses but

if I think about what is the product value that the a company like a standard like call it a grocery delivery app like

what is the product value you get as an end user today versus two years from now I I I look at it as like okay in two

years from now even if you're you're shipping all these new products as an end user the value you get from that

product maybe goes up like 30 to 50% if the company's done a really good job of of shipping new features. It's not

exponential though. And and and and so if I think about okay, you're here today, in 2 years you're going to have

30 to 50% more product value, then as a growth team, the like relative differential of the product value 2

years from now relative to today, I can actually capture like a decent percentage of that with the small to

medium optimizations that typically have higher conviction as opposed to like larger bets. But for anthropic it it's

not really that way where where the because of the exponential and and our products being like very very very the

the product value coming from AI the um the the product value that we will deliver in two years time is probably

like a thousandx 100 to a,000x what it is today and so if I think about that and it's like there's so much value on

offer you need to shift more towards okay we need to take larger bets and we need to not not sort of miss the the

forest for the trees and and so that's why we we do we still do all the smaller optimizations. It really matters and

like no one else is going to do some of these things and so we we need to do it. The compounding value is not immaterial

but we we do take on much larger core producty type of swings as well. So you mentioned it the chrome extension like

that is now the thing that underpins a number of use cases on co-work and and uh and cloud code as well and that's

something that the growth team built that's like a very like AI product that is like a very research heavy product

but we we were just bullish on it. We had an an engineer who was very bullish on it and we were just like hey no one

else is doing it we're going to do it and and so that's the sort of thing that I wouldn't have done at another company.

Oh wow, that's I did not know that. So the takeaway one takeaway here is like you know there's like stuff to extract

from your advice that is like only true at anthropic and then there's what can other companies learn from this

experience that you've had? So one is is your sense that if you're working in AI shift more of the pie

chart towards bigger bets because in the future the opportunity is so large you want to get find those as soon as

possible versus micropimize to be more specific there. It's I would say that it's if the primary value that

your product delivers is underpinned by AI as as a a central element of it then I think you should operate this way. So

I don't know companies like yeah lovable cursor you know all these like great businesses that are like it's as the

exponential rises their their value props are also going to continue to rise significantly like if if you're building

a product where it's it's an AI first product then I would definitely operate in this way. I think if you're building

a product where you're it's not necessarily an AI first product and you have some AI features that are on the

side but it's not the core of your value I don't know that I would operate this way. It would need to I would it would

depend on how is the rest of the product all staffed and how is the growth all staffed in relation to that.

>> Okay. Awesome. And then in terms of the way you're structured I thought that was really interesting. It's like a

combination of different sorts of things. So there's like uh the API growth, there's cloud code growth, but

then there's also like personas like a vertical of like knowledge workers and B2B. Is that intentional? Like some

specific bets and one just kind of like broad market opportunity. When you have like one product, it's easier to to have

a growth team that's more like purely on the funnel, right? It's like you have the conversion, you have activation, you

have monetization. But as you start to get into having multiple products, I think that's harder because if you do

that then, you know, if you just have like one activation team for example, but then you have cord code, you have

co-work, you have all the other things, they're very different audiences and and and they're very different sets of

crossunctional stakeholders internally. So, we're kind of looking at what what is the thing and all structures are like

not perfect and they're like right for a point in time, but we're looking for what is the structure that allows us to

have as much focus like focus is a really big thing and um on on audience and and uh and and problems and and uh

and also the tie-ins to cross functional partners is really really important like the the folks on our claude code growth

team like they work extremely closely with Kat and Boris and the others uh on that team and so that that tiein is is

is really important as well. >> So you've done growth at a lot of different companies, a lot of basically

let's call it traditional growth before anthropic. How else is growth as a function and as

a skill set changing with the rise of AI, AI products, AI startups? I think if your your your core product value is

very backed by AI then it is it is shifting where you're you're skewing more towards larger bets as opposed to

smaller medium experiments. I think in um other things maybe a big big thing related to this that I think will

accelerate this which I am really interested to see how it will play out is we are starting to look at how do we

automate growth which I think is like a really interesting area. So our growth platform team um we have a we're very

lucky we have like Alexe Kamisuroka teaches growth engineering at Reforge and he's just like the guy on the team

and and so he is driving this effort um that it's it's the name is it's a little cringey. I didn't come up with it but

it's like it's called cash which is Claude accelerates sustainable hyperrowth. I I did not come up with

that. Um >> but but but really it's an it's an effort to to to look at how can we use

claude to automate growth experimentation and it is still very very small. It's still very very early.

Uh we we we kicked it off only I think a couple of months ago. I think before Opus 4.5 it wasn't really possible. We

were just like not not seeing the results. And more recently with Opus 4.6 we're like okay this this is like headed

in the right direction. And so this I think is it will happen more and more across the the the industry where

basically if you think about okay I think this can happen all across product but grow growth teams in particular

because there's this whole body of work that is very small optimizations I think are just more inherently uh suited to to

like tackle this earlier. Uh I think if you think about like the the life cycle of shipping there's there's sort of four

parts to it. one is is um identifying opportunities like how good is Claude at actually identifying opportunities based

on different trends based on um previous trends that that Claude has seen in the past. Second is then building the actual

feature and and getting it ready to ship. Um third is is testing and ensuring that it meets your your your

quality bar and your brand bar. And then fourth is then once you've actually shipped the thing analyzing the data ga

gathering the learnings. If you think about that as like a the the the loop of okay these are four things that you can

eval and hill climber in each of these areas and understand how good is a model doing for you there and we we we we

basically think about it in that like the four four four ways and um and and we are scoring how good is Claude doing

in each of those areas and so we've been testing this at pretty small scale right now it's been a lot of copy changes and

some like very minor UI tweaks it's it's It's it's it's delivering results, right? Like and it's like you can push

it, press play with it, and it's like it it ultimately prints money where I'd say that the win rate is like I would expect

a senior PM to do better. Like I I would say like this is like a junior PM like 2 three years in. I would say this is like

the the win rate that I would expect from from like a junior PM. Um but it's not quite at the senior PM level.

Although I think like you look at the exponential, this wasn't available at all a couple of months ago. So it's it's

it's getting better, you know, rapidly and um I I think that the the it's going to change where you you'll be able to do

this for larger and larger types of experiments. Um but but then you know you think about the largest types of

experiments. I think that the the I mentioned the the four pieces around sort of identifying opportunities

building testing and shipping. The one I didn't mention there Lenny is crossunctional stakeholder management.

There's still a need for human brains. >> Yes, there is. >> And and like I think that that that one

is is going to mean that like in my eyes the work of PMs is like not going away actually anytime soon. And um that that

piece especially for larger projects you don't need to do as much of it for smaller stuff, right? You can you can

you can skip it. But for larger stuff uh that that piece is is not not not going away

>> until the the other stakeholders are their own little agents running around. >> I think that's right. I think that would

be the point where changes. It's funny. We had a we had like a difficult meeting a couple of weeks ago and me and my our

head of design, Joel, we were debriefing afterwards and he pings me. He's just like, "Amal, we will have AGI and it

will still be impossible to get six people in a room to to get to a line." And uh I'm like, "Yeah, I think that's I

can see that." That's a like what's the harder alignment problem? Oh, okay. This is so interesting and

this is exactly where I feel like things are going. So just to be clear what you shared here, there's basically this tool

that comes up with experiments to run to help grow Claude and all the tools. So it comes up with idea, somebody looks at

them, proves cool, let's do these things, builds it, ships it, tests the results, see how it's doing, and then

comes back like here's things that are working. Is that roughly right? >> It's roughly right. Right. And like we

right now we have human in the loop approving but like the amount of time I kind of think about scale in this way of

just like week on week are things getting better in each of the areas. Are people spending less time on each of the

areas? Are are the results getting better in each of the areas? And as long as like week on week that's getting

better then you're like okay this whole initiative is like scaling. Um and and so that that's roughly right but you can

think about it as >> I think a lot of this can be automated where human review is not needed. said

we care a lot about brand, right? So >> that is something that we we do look at right now. We don't want to be shipping

something that goes against the brand. >> Um but then >> you know you can have a skill that a

skill that that contains your your your brand guidelines and and very clear yet dos and don'ts on on brand and and and

so all of these types of like accompaniment I think are going to get better. The model is going to get better

at understanding how to use them. And so over time I I think that the need to like human review this really really

decreases significantly. >> Yeah. And you could always unhip it if it's like okay that was actually not a

great idea. And that's such a good point that we like we think we need people to do these things forever and it turns out

okay a skill could do this really well. Here's our brand guidelines. Here's our vision. Here's our mission. Here's our

goals. Here's what matters to us. Okay let's not ship that thing. So the reason I think this is so interesting, this is

like I've just been watching the expansion of AI doing more of the product development process. In this

case, the growth process of just okay, it went from helping you write code to like writing all your code to reviewing

your code. Now it it feels like what are the other ends of this the two ends around this? It's kind of going from the

middle out. The the top of that is coming up with what to do and then there's like the alignment stuff still

very hard and then on the other end it's uh reviewing the code and then shipping it. uh and then get distribution is

that's like a whole other thing I want to talk to you about. So, what I'm hearing here, and this is exactly what I

thought was going to start happening, is AI is now getting really good at telling us what to do. Not just taking our

orders and building it. And it feels like the growth version of this is where it starts because it's so much simpler.

Just like not that growth is easy, but just like it's data driven. There's this loop that you talk about. So, I think

this is such an interesting sign of things to come across just generally product.

>> Yeah, just putting that out there. >> Okay. So something that I'm constantly thinking about along these lines is just

the future of product PM engineering, how those roles shift over time based on the stuff we're talking about. How how

are you working together as a as a triad? And where do you see these roles going? What's most going to change, do

you think, across these three roles? This is like something that we talk about and think about frequently and the

the the picture changes rapidly. So sometimes when when things break you know execution like the bottlenecks

break historically in the past it's like okay now you need to hire more engineers you need to hire more designers etc and

it's more just like a a life cycle thing of like where is the life cycle of your team and that specific pod to identify

where the bottleneck is but now when when things break you need to still look at it of like okay is it like the actual

ratio or is there also underlying technological shifts that are that are also causing this to break and so that's

like a an interesting thing I think that smaller companies like if I'm at like a 15 or 20 person company I'm like the

only PM there working with some designers and engineers I I I think um I think in the smaller companies you'll

see probably like the biggest blend where like the PM will be doing all sorts of they'll be you know designing

shipping etc and I think you just have extreme bifocation you know larger organizations more scaled organizations

I think the jury is still very much out like you you speak to people even internally here and different people in

different teams have different views of like okay how much are these roles coming together versus how much are

these roles going going to be separate I I think that um it's not to say like I think even the PMs like a number of PMs

are shipping and and and themselves shipping and and and pushing PRs etc but I I if I if I look at okay across what

I'm seeing I think that it's it's clear that while PMs and designers are getting more leverage from AI engineering is

getting the most leverage Right now I I look at tools like claude code and like they the the amount of leverage

engineers are getting from them is higher than I think the amount of engine the leverage that designers and PMs are

getting from them today. Now that this like rapidly also changing but that that to me is like my view today and so um if

you think about okay a default team which is say five engineers one designer one PM with cord code that that that

five engineers is like two to 3xed right and and the PMs and designers have also increased but the that now they're

managing what is effectively a much larger group of of engineers and so even though like the headcount the org

structure hasn't changed. You're now you're now just dealing with a situation of maybe 15 to 20 engineers in the old

world, one and a half to two PMs and like maybe one and a half to to two designers. And so we're seeing that

that's putting like a lot of strain on on PM and and design. And it's it's not everywhere. Like I look at teams like

Claude Code and I think that or because that product is so technical like it's probably like just the the right thing

where you the the PMs are like all basically engineers themselves anyway. Um but but you know we had a product

like a PM lead on site the other week and we were all just like talking about this where across the board we're

feeling this where PM and design is just squeezed. It's just absolutely squeezed and we're like is it is the right thing

here? we just need to actually hire like a ton more more PMs and and that that could it could actually be where we we

we we land you know on growth how I think about it is like one we are hiring a number of growth PMs uh we we

desperately need people who are very very good and uh we are we are hiring so if you if you are excited by what we're

doing and and you know growth please please feel free to apply uh would love to love to chat and um maybe craft a

maybe craft an amazing cold email to you. >> Yeah. Yeah. Yeah. Feel feel free to cl

craft that email. Um so so that's one is I think we are going to be hiring a number of PMs. But then the second thing

that we do is we we we very much hire productminded engineers. I think this has always been the best thing to do in

growth. Like you always want to have the the engineers coming up with ideas etc. And so we especially especially people

who who can really like step in as mini PMs if if people uh if the PM is is absent. And so we're like basically more

formally leveraging that right now because we are so stretched. So the the frame that we have is that if a project

is less than is 2 weeks of engineering time or less then the the uh engineer is on the hook to effectively be the PM for

that. And so that means things like talking to security, talking to legal, talking to cross functional

stakeholders, and the engineer is very much driving that. The PM will get looped in and and they'll advise if

needed, and if something is like like wildly going off track, then they'll step in, but they're much more in an

advisory capacity versus execution. If a project is more than two engineering weeks, then the default is that the PM

should continue to to be on the hook for for making that go well. unless they still delegate more to ENGE, but they're

like squarely accountable. It's not like fully cleancut. It's like use your head like if this is a oneweek thing, but

it's extremely controversial like the PM should probably still drive it, but that that I think is like the the approach

that I expect more companies will start to do, which is just deputize the engineers to be mini PMs. Now, not

everyone can do it, right? So the the PMs the the the engineers who are more product minded suddenly their value goes

up significantly like like an order of magnitude and and then I think we will probably still be hiring a a lot of PMs.

There is so much interesting stuff I want to follow up on here. Okay. So one is this idea of two weeks just briefly.

I I always joke as a PM uh you can go on vacation and be away for like a couple weeks from your team and things are

going to be all right. like they'll, you know, there's like a momentum, there's a plan, people keep operating and it feels

like that's kind of the this rule of thumb you use of just like, okay, if it's two week project, you'll be all

right without a PM, you can handle it. Uh, I love that those two connect. Okay, the other here is so interesting. So,

you're saying here that because engineers are so accelerated and this all makes sense. PMs in design are kind

of just like, holy, there's like hard to keep up with the pace of engineering. And what you're saying is you need more

and more PMs to keep up. That's one route or it's engineers that can PM essentially which is so funny. It's just

like okay great news for product managers uh until more of the PME stuff can be done by AI but that's a really

interesting trend. I don't know is there anything else there just like oh wow we actually may need more PMs the ratio

more PMs to your engineers might be the future. Yeah, I I think this is like it it just like really depends on the

industry, the the size of company, like any company where you're building something that's like much more

developer focused, like you're going to rely on the engineers a lot more. Earlier companies, you don't have as

much of this like crossunctional coordination, stakeholder alignment nonsense that you need all these PMs

for. So you you you can like get by with less. But then as a company scales and like if I think about okay now you have

this ratio where maybe the the one PM became two PMs from like productivity that the like five engineers became like

20 engineers the one designer maybe became like three designers. If you think about like what is the best use of

time for that PM I think this is like a really interesting thing of like how much should PMs be actually shipping

things themselves versus everything else. I think like in the in in the world where you're like limited on

engineering, the PM should definitely be shipping things. I think in in today's world um it's a good way to like get an

understanding of the tools which is really important. So the PM should be shipping for that reason. But if I'm if

I'm one 1 p.m. or 2 PMs and there's 20 engineers. I think about what is the incremental

value I can add with with my time and is it actually shipping like the 21st PM feature or is it saying how am I getting

a little bit better at guiding the team on what the right opportunities are and and and so that's where I think like in

this world you may have all these engineers who are like mini PMs and the better that happens like that's like

where I would love to be doing more of but still like the if if you then get a really good PM who can come in and can

like improve that the the like why and the what and and the why and the what particularly by like 5%. That is like

such a high leverage. This is such an interesting insight you're making. It's like so counter to how a lot of people

are thinking PM is evolving. Like what I'm hearing here is because PMs are so behind because engineers are just

getting so much done. There's like many people here, okay, you need to be prototyping, you need to be shipping PRs

as a PM. what you're saying which I completely agree with is your time is much better spent helping

PM basically and helping the engineers uh become better PMs themselves and and the leverage there is a lot higher than

you spending time coding shipping PRs in most cases I think that's true in certain circumstances I think that as a

smaller company I don't know that that's the case in a smaller company where it's all hands- on deck I I think you you you

probably need to be shipping I think if you're in a company where like budgets are very tight and engineers are very

tight and you you know you're not able to just hire because money is unlimited then like you need to do what the what

is needed to to accelerate the the like the the impact your team's going to have right so there's going to be a number of

cases where like as a PM the right thing to do is to be like screw it I am shipping and like I am I am going it the

whole way but I'm talking here more about the like larger companies more scaled businesses

yeah if you have 20 p 20 engineers is is is is it the highest use leverage of your time to ship an extra feature or

figure out how do I uplevel everything that we're doing get the user insights better etc. Yeah, and I think there's

also an element of shipping to learn, building a prototype so that you can have a better opinion like a lot of

people talk about just going to try three things, see how it goes and that'll help inform the road map. This

is now the PRD is look at it instead of talking about it. So there's a lot of value there still. That's that's that's

very true. I think that's a great that's a great point. So like even for me now where we've got number of PMs, we've got

many engineers, there are certain times I'm like I want to articulate the idea I have in my head, it's just better for me

to prototype it and show it, right? So I think that that is really important. Um and then you know we we are very

scrappy. So like we're like a big big company by by name valuation, but we're like extremely scrappy and just the the

focus internally is just like minimize bureaucracy and just like just go. And so probably 70 70% maybe 60 70 80% of

what we what we ship does not have a P. I'm like averse to PDs. I think I just like I just like hate documentation. I'm

just like go just like cut cut the blockers. um 20 30% of stuff where it's like it's important it's really

important to get right like the documentation should be really good and like that people sp should spend a lot

of time on it but by and large I think PS are just out outdated at this point and and um you can just kick things off

with a good team without without needing to to do that sort of thing. >> Say more about that. What do you do to

help make sure because people can build so fast or spend a lot of time going in the wrong direction ship things that are

not what you're asking. How do you kick off a project and clarify here's what we're doing? Is it just a conversation

or is there anything beyond that? >> It really depends on the size of it. And this kind of goes back to like the two

week thing. So the why we have that two week thing, it's more like a how do I have some filter to say if we're

investing heavily into something we should apply more thinking behind it versus if it's a smaller set of

investments, just go for it. And as a growth team, again, you do have a decent amount of these smaller things that you

do. So for for very small changes, you're like, "Oh, there's a thing coming. We need to have an upsell for

it. What is it the thing we're doing?" Like this is just on Slack, right? This is just purely on Slack. It's just a a

messages back and forth and we'll I think it also depends on having a good caliber of engineer in there, but

engineers can can understand like, "Hey, I know you said this, but like what about that for the audience?" And so

like we're lucky we have good good product minded engineers in that sense. But all these smaller things are very

much just on on on Slack back and forth and and and that's what you you do for the larger things. I think I I very

firmly believe in like a proper kickoff. So we we still do you just there's so much going on at this place. No one's

got time. No one knows what's going on. And so doing a cross functional kickoff get legal, get safeguards, get everyone

in the room and just be like this is what we plan to do. what what do you care about? What do you care about? What

do you care about? Like that that 30 minute meeting um for larger things is just I think still so important to to

just streamline all the mess that may happen later if you don't do that work early on.

>> What's your approach to crafting that PRD in those cases? Is it like ramble into cloud? Is it do you have a

template? >> Even in those cases, there are times I don't craft a PD like cuz we're just

everything's moving so quickly, right? So there's still some of those cases where I just set up the meeting and then

like 5 minutes before I'll put it into quote work like here you know some of my thoughts what credit like here are the

things that I need to think about spin up like a a basic doc and and we use it to talk other times I won't even have a

doc but if if I am creating a prd um I have basically skill like a skill that that I I've you've created um and then

there's projects with all the previous PRDs in there uh and then I will each is pretty simple like I'll it has the

format down so I'll just say here are the things I care about here's the why here's the problem and flesh out the key

considerations flesh out the cross functional stakeholders those types of things but again my my my default is

like if I can avoid the dock and if we can just just jump to action then then that's what we should do and

increasingly just just jump to prototyping the thing >> yeah and that's that's where I think

it'll get so interesting once we can automate more of that just like your uh assistant talking to the legal assistant

just like ironing out all these little you know what's important to you what's important to the yes and it's coming and

I think the legal team has done like good enablement around this like we work you know versions of like how do you you

can think about like how can you um mimic what someone might say and like set up you know like a co-op right so

there's there's things like that that I think that we have now and then as plot gets more and more context and gets

better at passing long context I think These are things that quaude will just get better at knowing. One of the one of

the things Lenny is like a slight tangent but one of the I think most effective ways I use quad or most

interesting ways I use quad is this I see a number of people doing internally is to like help you identify

misalignment. Um this is like a I think something that's I found really really helpful. So with with coowork you have

this the Slack MCP and you and you can you can tell coowork you can tell co-work to say basically look across

Slack you know the projects that I'm working on these are the things that are top of mind go and find me areas of

potential misalignment right now and it does a really really good job so this is something that I've scheduled runs every

week's like looking at things and coming back to me with and saying like hey I think these things you should be aware

of and so you can think about in that in that shipping context text. It's a similar thing where Cord can basically

be looking at what's what's happening across the company and say, "You're thinking about shipping this thing.

Here's who you need to talk to. Here's what what you need to keep in mind." That is so cool. I am so excited to tell

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get $1,000 off Vanta. That's vanta.com/lenny. I feel like there's this like what are

the jobs of a product manager and then how are they slowly going to be uh supported slashdone by AI. So there's

this misalignment just like fine misalignment and then maybe one day it'll be like align people initially.

You talked about this uh cache automation for growing like how do I grow this product that's starting to

happen. Another that I I might use myself when I'm building stuff is just asking how do I make this product