# Stripe Data Reveals Record Startup Growth Amid AI Shift

**Podcast:** Y Combinator Startup Podcast
**Published:** 2026-08-03

## Transcript

Okay, Patrick, thanks so much for being here.
Welcome to Startup School.
Great to be here.
Harj and I first met 20 years ago, and we started a company together.
Sorry, am I giving away the introduction?
Yeah, I thought this was my interview, but keep going.
We started a company together many, many years ago, and I learned a huge amount from Harj.
So it's really fun to do this.
All right.
Well, actually, I mean, speaking of that, so when I think when I first met you 20-something-ish years ago, at the time, your most impressive achievement, I would argue, was Chroma, your dialect of Lisp.
Any Lisp programmers here?
Oh, wow.
Okay, that was, I think I heard one whoop, which is more than I expected.
But yeah, I really liked Lisp when I was in high school.
Yeah, so what I was going to ask is a prolific 16-year-old today could presumably just, like, prompt Claude to write their Lisp dialect.
Would you advise them to not do that and still do it?
Is there any value in such things?
I don't know.
I wonder a lot.
Yeah, like obviously on the one hand, it used to be really fun to write all this assembly and machine code and to optimize your instructions and layout and memory and everything.
And now we don't have to do that anymore.
Compilers do it for us.
We don't mourn it too much.
And so maybe in the same way, we shouldn't mourn source code.
We should just transcend the plane of...
instructions to Claudius at all, but emotionally I miss it.
How about, I think just as I've been hanging out here with these students, maybe the question behind it is many of them are just wondering what should they be learning at college?
What is in this AI world?
How much should they be trying to learn and derive from first principles and how much should they just outsource to the AI?
Right.
I mean, my model of this is cache, you know, the CH, not an SH, where Jeff Dean has this famous set of numbers that every programmer should know, bandwidths and latencies and just kind of relevant constants that you show the reason about as you build systems.
And obviously, when you're thinking of building any system or distributed system or whatever, like all lookups and all relevant bandwidths between different Components are very different, right?
And retrieving something from L1 cache is very different to retrieving from RAM is very different from retrieving across the network or whatever.
And I think it's like that with knowledge, where fine, yes, you can ask the agent or something to compute something for you or to look something up for you, whatever.
That's a hell of a lot slower than knowing it in cognitive L1 cache.
And you can have way more round trips in your brain than you can you know, muttering through, you know, Super Whisper or typing it out or whatever.
And so I think even granting the full capabilities of the models, I still think there's a pretty, like, I think for a long time to come, neuronal lookups will be much faster.
And then look, if you look in revealed preference at what companies themselves are doing, whether they're companies like Stripe or the Labs or what have you.
There still seems to be an enormous premium on cognitive ability.
And so I wouldn't, I think renouncing that before there's evidence that we've saturated those benefits would be premature.
I mean, are there specific things that maybe you personally, either personally or as CEO of Stripe, you still purposely choose to do yourself and retrieve from your own cache, even though the agents would probably do a reasonably good job?
I still write myself.
I both philosophically but also specifically, substantively, dislike the writing of the models.
I mean, it's very interesting, right?
Because these can prove the Jacobian conjecture, you know, whatever.
And so clearly they're capable of these monumental feats.
But somehow I still haven't read the LLM essay that I found super compelling.
Now, I think it's just very hard to like RL limit that domain because the utility function or something is kind of hard to define.
But yeah, I think writing is a pretty, interpersonal communication and writing I think are still very fundamental.
And so being able to reason sensibly in the multi-dimensional space of reality.
And in some kind of indescribable way, I feel like the model is still kind of deficient at that.
And so I've never, I've yet to send, you know, every tool is now trying to prompt me with, you know, pre-written suggestions, whether it's, you know, Gmail or apparently WhatsApp just rolled this out.
And I think I've still sent zero of those in my life.
How about, so if you talk about the Stripe?
story, the early days in particular, a little bit.
You were at MIT, then you left to start Stripe.
How did you think about that decision?
And obviously, we're in a stadium full of college students.
How should they think about it?
How do they know if it's the right decision for them to leave college early and go start a company versus stay?
Yeah, well, I think I have the slightly unusual distinction of having dropped out of college twice to start a company.
So maybe one thing to know is that it's not totally trapdoor.
You can drop out and, in fact, return.
So I dropped out after my freshman semester to start this company with Harge.
That was super fun.
And then after a couple years of that, went back, did another year at MIT, and then dropped out again to start Stripe.
And when I went to college, probably like a lot of people here, I had this vision of my life involving becoming an academic and I really liked physics and I thought, you know, I'll do all this physics stuff.
It's so cool.
I'd read all the Feynman books, all of this.
And I guess I am, well, growing up in Ireland, I hadn't realized, I hadn't thought much about the possibility of startups.
Hello to the other Irish folks here.
And...
And I mean, way back then in the sort of pre-Cambrian era, startups were definitely much less well-known even on campus and so forth.
When I was dropping out, people thought it was super weird.
I think overall, if you enjoy college, I would actually, I think there's no harm in finishing.
I felt this real sense of urgency, which I think in hindsight was a bit unnecessary.
But if you don't enjoy college, just, you know, whatever, it's not your thing.
It's not what captivates you.
You don't really want to learn all the physics things or whatever.
I think a lot of parents think that dropping out is very risky and will impugn your reputation for the rest of your life and so forth.
And as far as I can tell, nobody has ever cared.
So I both think you don't need to, but also the cost of doing so are de minimis.
But what was the urgency you were feeling?
The urgency?
Yeah, to go out and do something.
I don't know.
Life is short, right?
And I mean, it was a general kind of haste.
I think a lot of us, I'm sure many of the people here, you kind of get into this mode of speed running high school.
And then once you get to college, it's like, obviously, I want to speed run that as well and do all the things.
So it's a bit of that.
A bit of Mark Andreessen also talks about a version of this.
I thought that a bunch of the opportunities in startups in Silicon Valley and so forth were ephemeral and fleeting.
And if we didn't build it then, it wouldn't be possible to do it in three or four years.
And maybe all the opportunities will be gone.
In hindsight, I think that was a poor intuition.
It's been pretty robustly and reliably the case over many decades that Silicon Valley has a surfeit of opportunities.
Yeah, I think it was mainly those two things.
Do you think it's, I mean, this is a very common thing that we hear when we talk to students now is that they are part of the reason they want to drop out on mass, it seems at this point, is their worry that actually now is the moment that there's sort of, I think the meme going around is that if you don't sort of drop out and start a company and make lots of money, you're going to be trapped in the permanent underclass.
So is that, should everyone here be worried about being stuck in the permanent underclass, I guess is the question.
I think.
Humanity has always had an affinity for these millenarian models of how everything will soon come to an end and be this permanent transformation of society and so forth.
Actually, there's a great book, The Winged Gospel.
People thought that after the invention of aviation, that it was just like civilization was just entering and humanity as a species were entering a new era.
And nothing is going to be the same.
And obviously, aviation was a pretty big deal.
But I don't think it was quite the sociological rewriting that some of the excitable proponents at the time imagined.
So it's hard to predict anything, especially in the future.
But I would take the under on this being the last couple of years to create a company.
So going back to the Stripe story, Stripe ostensibly seems like a good idea.
Like even on day one, the Internet's a big deal, money's a big deal, like combine those two things.
Presumably, is that how it went when you went to tell people you wanted to start Stripe, but everyone just say, hey, this is obviously a good idea?
It was kind of funny.
It was something we learned from YC.
was the importance of focusing on very concrete, easy to explain customer problems.
Like it's very easy to hallucinate or to imagine some customer problem that's not actually something viscerally felt by a person who would pay money.
And so over the course of, in part, working on Locktomatic together, we sort of encountered this issue of it being really annoying to deal with the movement of money or payments or whatever on the internet.
And on the one hand, it seemed like an obviously good idea in the sense that nobody liked the existing ways of doing so.
And they were broadly extremely unpopular and kind of antiquated and legacy and yet to like fill out this paperwork and go to the bank in person and the paperwork was in Latin and just like it was all bad.
But then the flip side is it just seems kind of ridiculous that two kids would start a financial services business.
And FinTech didn't exist as a sector at the time.
The word literally didn't exist.
And so it's just kind of we felt like the proverbial squirrels in a trench coat trying to masquerade as a real business or as serious adults, but obviously knowing nothing coming in about the space.
And certainly a lot of people we met and pitched or banks or partners or whatever that we talked to, I mean, They didn't literally laugh us out of the room, but you kind of see them looking for the button to, like, call security under the desk and have them haul us out because it just seems so improbable.
So anyway, I'd say it both seemed like an obviously good idea in that people really wanted this, but also a bad idea in that nobody took us seriously.
But I think the fact that it was, ultimately, the fact that it was grounded in such a concrete, actual, real user problem saved us.
Speaking of that, in order to actually build the product, you had to get a banking partner and do things that a typical software company did not have to do.
As two young founders, how did you manage to convince a bank to trust you in the end?
Yeah.
Well, actually, this is not an answer to your question.
But just the thing that strikes me as I sit here is the reason we decided to start Stripe.
is because John and I were in college together.
He was in his freshman year.
And we went to startup school in 2009, which was held in Berkeley.
And we thought it was pretty cool.
And so we went and we got sushi afterwards in Potrero.
And we were walking back from sushi.
And we're like, we've kind of been kicking around this idea for a payments thing.
We've been thinking of the space.
And it was walking back that evening after startup school that we decided to start Stripe.
I remember literally where we were on the road.
And I remember what we said to each other, which was, yeah, we might as well, because it probably won't be that hard.
OK.
So moral of the story is go get sushi and potrero tonight.
You might start the next Stripe.
And yes, beware of sort of these ultimate yak shaves.
We thought we could do it on the side while in college.
It would take a couple of months.
That was almost 17 years ago.
At the time, I remember you were also unusual in that you took sort of longer to do a big public launch.
And especially within the YC world, the motto is very much sort of launch early, launch quickly, be out there and iterate.
Could you maybe talk us through a little bit about that?
Why did you do it that way?
Yeah, so we started working on Stripe kind of seriously.
Well, we started working...
the week after that startup school but um we're kind of in college wasn't full-time we started working full-time the summer of 2010 we launched publicly september 2011 so almost uh two years after like the first lines of code after the repo was started and yeah waiting two years to launch it seems i mean you know if we're going to yc meetings you know every every week i think we'd have been you know bludgeoned uh on the head um I think, and look, in many domains, that probably is the wrong thing to do.
In our domain, to come to your last question, because we had to do so much stuff around security and partners and money movement and infrastructure and reliability and all the things, we didn't feel like we could scale a really good self-serve experience without getting a lot of the preconditions and the infrastructure in place.
I think the thing that saved us and meant that it wasn't a total walk in the wilderness, is we had production users almost from the very beginning.
So first lines of code in fall of 09, we got our first live production user in January of 2010, so like two months into working or whatever.
It did very little.
Like, it was very larval and incomplete.
And our first production customer was Ross Boucher at a company called 280 North.
And all I could do was charge a card.
And so, you know, Ross would charge the card.
And, you know, then he would ask sort of a reasonable question, like, you know, how do I look at all my charges?
reasonable request.
And so let's put up a little dashboard here.
And then he'd be like, well, I want to refund a payment.
And all right, we'll build refund support.
And then after a couple of weeks, he was like, at some point, do I get my money?
And they're like, hmm, also a reasonable request.
So let's build that functionality.
So it was very kind of just-in-time development.
Anyway, so we had a production customer from very early.
And then we did increase.
It was in private beta.
We increased the number of customers every single month.
you know, all the way to that public launch.
And so every week we had actual customer feedback requests, new users coming in, we're learning things from reality as opposed to our own kind of hypothesized or extrapolated conception of it.
And I think if you have, you know, a significant stream like that of grounding, I think it's probably okay to not be like launch, launch.
I mean, you're an expert YC partner.
Do you agree?
That's a good question.
Yeah, I mean, it is.
The issue with advice in general is it's sort of so generalized and, like, especially in startups, the exception proves the rule, right?
So I think those are, yeah, certainly if, you know, the cost of failure is high, then it almost certainly you have to sort of take longer to, like, build.
Maybe a slight tangent, but something I'm curious about related to this, though, is with these coding agents, the ability to just build and produce software cheaply and quickly.
I wonder, should people be taking more of this path?
Should people be more ambitious in general with what the version one of the thing that they launch is?
Or is it still fundamentally good product design to start narrow and focus and then expand out once you know what people want?
Yeah.
It's a good question.
I think probably in the era of AI, I mean, I don't know.
And to some extent, YC will be, I think, the expert here.
But the whole kind of traditional lean startup doctrine of exactly what you say, like start out by buying the Google ads or something and identify this crevice or whatever and iteratively expand out from it.
I think you can certainly imagine that that becomes much more competitive and much more aggressively tilled.
And it's kind of hard to find those little niches.
The internet's a much bigger place than it was 20 years ago when some of those ideas emerged.
Whereas taking these really divergent starting points where nobody else is trying to...
occupy that territory is maybe a more, like, basically, maybe you have to more aggressively decorrelate in the era of AI.
And I think it is interesting to think about, you know, many of the companies that are most successful over the last 10 years, so many of them are very anti-lean startup, right?
Whether it's, you know, the labs themselves or Amduril or, you know, you can go down the list.
A lot of them have this characteristic.
So I, yeah, I think maybe a better way of saying it is, 20 years ago, the whole lean startup thing was almost the only thing to do because of capital available, and you didn't have AI that made spinning up an organization with many different potentialities and capabilities so much easier.
Whereas now, I think you can start these much more aggressive and ambitious things up front.
Within YC, and probably startup raw at this point, you're famous for the Paul Graham term schlep blindness, the stripe.
at least on the surface, involved a lot of schleps, things that presumably weren't the intellectually most interesting things to work on.
And I always found that especially interesting for you because you just mentioned you had academic interest in physics and I just think clearly, you're a deep intellectual and have very many things that you're interested in.
As Stripe has sort of grown in this big company, in what ways are there sort of like intellectual...
rewards that you've given up and which ones have you gained?
Yeah, I mean, look, in any company, there's a bunch of stuff that's not that rewarding or in and of itself all that interesting, like setting up payroll.
No one sort of starts a company so that you can set up payroll.
And certainly building business and financial services, there's all sorts of more arcane and extensive versions of that.
I think that...
I actually feel extremely lucky with Stripe in this respect.
And I think this is something, I don't know if you need to think about it that much up front, but I think once you think about it maybe before you raise a significant amount of money, you always worry naturally about possibility of failure and what will happen if you fail and how to mitigate and avoid failure and all those things.
I think you need to ask the converse of that, what if you succeed?
and you raise money and you have customers and you have employees and a whole thing, are you going to enjoy that?
Are you going to want to work on that for 10 years, for 17 years, for 30 years?
I mean, Larry Ellison at Oracle is going for, I guess it'll be a half century soon, right?
So what if you succeed?
And in the case of Stripe, I really love it because we're working with the world's most interesting and innovative companies.
25% of all Delaware corporations are started with Stripe via Atlas, and then we get to partner with them and work with them and hear from them and get their feedback and get the request and everything through the entirety of the journey up to being the Shopify's and the OpenAI's and all the standout successes.
Oh, and actually speaking of Atlas, We're giving free Atlas incorporation to everybody at Startup School.
So if you are struck by the urge to found something over dinner this evening, as we were, just email startupschoolatstripe.com and we will get you your link for free Atlas.
But yeah, I think PG latched onto something where, yeah, there are all these kind of menial tasks, but in the kind of totality of Stripe, I find it so...
Interesting.
Every business is a kind of applied theory on how some aspect of the world works or how some market works or how some...
If the new company with a new model, it's kind of a contrarian thesis on some counterfactual...
I've never met a Stripe customer and thought that's boring.
So it's actually...
The business as a whole has been the opposite of the Schlepp-blindness instinct.
You have a particularly unique perspective on this because you work with the big model providers, the big lab companies, and you work with all of the fast-growing AI startups on the ground.
Something that came up a lot here yesterday, honestly, it comes up within the batches too, is people are just worried about, is my idea going to get sort of trampled by the big lab providers?
And given your perspective, I'm just curious, how should people think about that?
Yeah.
Again, Predictions are hard, and certainly the labs are very competent, capable organizations.
And maybe if you separate a little bit, will rapidly improving AI capabilities do this, or will the labs specifically themselves do this?
I think in general, the track record of, like, no organization...
If we go back 20 years, there was some of the sense with Google.
When we were doing Octomatic, the question was always for our company and every other company, what if Google does this?
And Google seemed kind of omnipotent and had this immense number of incredibly talented people and essentially infinite access to capital and servers, all the things.
And just human organizations are complicated, and it's very hard to have to manage to aggressively...
prosecute 100 different priorities and to deal with all the issues and interference that arises among them and so forth.
And so Google has done incredibly well in a bunch of specific places, but it's not like Google has done all the things, even if in some kind of basic material sense, Google maybe had that ability.
So I'd say that the track record of that is checkered.
And in general, I think that fear has been overstated.
Now, I think there is a more specific thing of just like models themselves.
Forget the labs.
Even if the labs aren't particularly ambitious about expanding their scope, literally LLMs will obviate a bunch of, or agentic capabilities will obviate a bunch of specific verticals or tasks or something.
Hard to say, obviously contingent on one's forecast of the model capabilities themselves.
But in certain cases, I'm sure that will happen in certain domains.
It has already happened.
Looking at the Stripe data, one thing I will say that I think is germane to people here, there are many more businesses getting started now than there were a year ago, like as little as a year ago, way, way more than we're getting started five years ago.
And actually, the relative change between last year and this year is pretty much the largest relative change we've seen in any given year.
So for example, From 2019 to 2020, we saw a big jump, understandable, during COVID.
So February to April of 2020 or whatever, I think the growth rate inflected to maybe 50% or thereabouts year over year in terms of new businesses getting started.
As I speak, the number of new businesses starting on Stripe is up around, it's a bit under, but around 2x year over year.
which again is the largest relative jump we've seen.
And you might think, okay, fine, there's way more vibe-coded, lightweight, slop, whatever.
Fine, there's more things, but are they actually succeeding?
But actually the median business is doing better this year than a year ago.
And then if we stratify it and look at...
the probability that any given business will reach some revenue threshold, a million dollars, $5 million, $10 million, whatever.
Those all seem to be getting better.
Business are the time to revenue for new companies in corporate with Atlas is declining.
And so by all the kind of objective metrics we can look at, it seems to be a better time than ever to start a business.
Now, again, things can change.
I don't know what the world's going to look like in five years.
But speaking today on July 26th or whatever it is of 26.
I think the Stripe data would suggest there's never been a better time.
I mean, we see the exact same thing in the YC batches.
Companies are just able to grow faster than ever, certainly within the batch.
Back in, again, the old days when Arj and I were first starting out, getting to a million dollars of revenue, like run-rate revenue, was a big deal.
People would know about that company.
They'd be like, you know, I heard that X company got to a million dollars of revenue.
And now, I mean, that's...
Yeah, you should be by your first month, it feels like.
That's an exaggeration for everyone here.
But I mean, certainly within sort of like the YC part of the lifecycle, like day zero to 90.
It's really being driven by, I would say, enterprises willing to buy from startups, which is a new thing.
So you can sign these new contracts within the batch.
You have the data as the companies keep growing.
I'm curious, are there other factors that are driving these sort of inflected growth curves from like 1 to 10 and 10 to 100?
I think it's really the dynamic you just mentioned, which is businesses everywhere are more spring-loaded.
to adapt and to try new things.
And they have a real terror of being left behind with archaic and antiquated ways of operating.
And so in normal times, you're a new startup, you have some mechanism for doing whatever, and you pitch the CIO or the CTO or the whoever at some company, and they kind of...
don't want to talk to you because your thing is not validated.
Maybe you'll be around in two years.
All the kind of obvious objections.
But now people know that, well, the risk of the status quo is actually extremely high.
And so even if there's risk in doing all the new things, well, this path also looks pretty dangerous.
And so I really think there's never been a better time for startups to sell and to have their products get adopted at a pretty meaningful scale right out of the gate.
A lot of YC companies in recent times have demonstrated this.
I think it's a really pervasive dynamic.
And there's a bit of it, I think, also.
I mean, Stripe is not a consumer company, obviously, but, you know, I think there's some version of this on the consumer side where I think consumers, I mean, are also pretty, I mean, consumers have complicated views on AI, and maybe they don't want the data centers, but people are very intrigued by the product, and I think there is a kind of, they're kind of beguiled by them, and there's a predisposition and an openness to experimenting with the new.
Maybe just more broadly, something I'm curious about is, again, with the data you have at Stripe, has anything you've seen in that data changed a belief you have about AI broadly, say, over the last 12 months?
I mean, there's a fear that AI is going to be this hegemonic, centralizing, totalizing force where a small number of companies gobble up a very large share of the economy.
Many companies at the forefront of AI have done incredibly well and I think will continue to do incredibly well for sure.
But basically we can see at Stripe the hunger and the intensity with which other companies are either getting started taking advantage of these new capabilities or existing companies are retooling.
I don't worry about the centralization in the same way.
I think there are going to be many thousands of winners.
And again, we try not to offer any definitive prognostications because the future is not predetermined.
But based on the trend lines we can see, I think we are heading towards a more decentralized world and one with more broad-based prosperity.
Cool.
All right.
Well, I think that is all we have time for today.
So...
Thanks so much, Patrick.
Thank you for having me.
And it would be remiss of me not to say that Stripe would not exist without YC.
Cool.
All right.
Thank you so much.