Paul Graham On Startups, Ambition, and Great Founders

YC Visiting Partner Vivian Shen sits down with Paul Graham at the original YC office in Mountain View to talk about startups, AI, ambition, and what makes great founders.

• 0:00Speaker 00

  So we're here in Mountain View today with PG himself at the original offices doing your talk that you do for the YC batch. I looked it up. This is actually the 47th YC batch.

• 0:10Speaker 01

  You know, I've been trying to calculate that number and I wasn't sure exactly what it was. No wonder I'm not too worried about this talk. You've done it that many times.

• 0:19Speaker 00

  Yes.

• 0:20Speaker 01

  It changes a little bit.

• 0:21Speaker 00

  Yes, it's the 21st year also of YC.

• 0:24Speaker 01

  You know, the weird thing is I make the talk from scratch every time.

• 0:27Speaker 00

  Really?

• 0:27Speaker 01

  I probably say the same things over and over, but I always feel like I should like, I think, oh, my God. I, you know, you think a couple of hours beforehand, oops, I better, I'm just talking to YC. I better think in advance a little bit about what to say. And so I open up a text file and start typing things and that's how it always is.

• 0:43Speaker 00

  Any tidbits from today that are new from winter?

• 0:47Speaker 01

  No, most of the things, most of starting a startup here, this is an actually interesting point. Most of starting a startup is the same and most of starting a startup is always the same, right? In, you know, microprocessors or AI or like the internal combustion engine, it's always the same stuff.

• 1:03Speaker 00

  Good. Well, in that case, let's run through some questions.

• 1:06Speaker 01

  Okay.

• 1:06Speaker 00

  And so you recently posted that the startups YC funds now are much more serious than they were in the supposedly good old days.

• 1:13Speaker 01

  Yeah.

• 1:14Speaker 00

  What did you mean by that?

• 1:15Speaker 01

  Well, what I meant by supposedly good old days is people are always saying that YC has jumped the shark. You know, and like, I remember when people started saying this, which is in about like 2008, right? YC is always this thing that was great, but now it's not what it was, right? Cause they can't say it was always terrible. They have to admit it was once great. So if they want to attack it, they have to say it's fallen, right? It was good, but now it's not. It's always been, it's always not good anymore.

• 1:43Speaker 01

  And so that's what I meant by the supposedly good old days, because the old days are what people claim used to be good. But like in the old days, there was a lot of things like Reddit, right? Which valuable as it is, is not exactly intercontinental ballistic cargo, right? Which I did office hours with recently. How about that for an idea? Like, it's like an ICBM, except instead of exploding, it lands.

• 2:08Speaker 00

  It's ambitious.

• 2:08Speaker 01

  And drops stuff off. Yeah, that's, that's serious, right? You don't get much more serious than an, than intercontinental ballistic cargo.

• 2:16Speaker 00

  Yeah. What, what were some of the other serious ones?

• 2:18Speaker 01

  Well, curing cancer. There's a startup in this batch. I mean, and there's all sorts of different approaches to curing cancer. And I say, fund many of them because like any one working would be good. So like one way to approach curing cancer is vaccines. That's one end, right? The opposite end is therapies, right? And so there's a startup in this batch that is basically doing on-demand research for people with cancer, you know?

• 2:51Speaker 01

  And what I like about it is they're sort of inflicting on cancer the death of a thousand cuts, which may be the way to defeat it because, you know, it's notoriously, it's notoriously not the sort of thing where you just like come up with a cure for cancer. I mean, maybe you do if these vaccines work, maybe, maybe you do, right? But maybe, or maybe the way you fight it is the death of a thousand cuts.

• 3:12Speaker 00

  And they're actually really interesting because they helped another YC.

• 3:15Speaker 01

  Yeah, right. It's part of the whole YC community. In, they helped Sid from GitLab deal with his cancer, which he has done very successfully. I mean, he approached it like a startup, right? And these were essentially his co-founders in that de facto startup. And it's funny because I remember thinking after that, you know, I'm all, I always had this process going of what would be a good startup idea, right? And I remember after that saying, you know, somebody should start a startup to do for everyone what Sid did for himself. And now, not only is this startup happening, it's the people who actually did it for Sid. So it couldn't be better. I was so delighted when I realized that one was happening.

• 3:52Speaker 00

  Yeah. And I think his essay that I went founder mode on my cancer.

• 3:55Speaker 01

  Yeah, that's a very good way of describing what he did.

• 3:58Speaker 00

  Yeah, using another YC term to

• 4:00Speaker 01

  Yeah.

• 4:01Speaker 00

  attack his cancer. So along that vein, I was rereading the essay you wrote in 2012 where you coined the term frighteningly ambitious.

• 4:09Speaker 01

  Frighteningly ambitious ideas. A lot of those ideas have actually gotten done since then.

• 4:14Speaker 00

  Like which ones?

• 4:15Speaker 01

  Well, a new Google, that was one of them, right? And it turns out, look, the, I, I sort of predicted this, right? That the way you make a new Google is not by attacking them head on. You have to wait for things to change so much that their model is obsolete. And that's when you can do it. And that's what OpenAI is. Right? Like I realized very early on, like after using OpenAI, like, whoa, I don't use Google anymore. I don't use searches, that what I really wanted from searches was not webpages. I wanted information. Why not just ask the AI for the information, right? And I'm sure everyone's now had this experience.

• 4:52Speaker 00

  And it was incubated at YC.

• 4:54Speaker 01

  Yeah, yeah, yeah, yeah. One of Sam's many side projects.

• 4:58Speaker 00

  Yes. And so along the same veins of around ambitious as a term. I am curious, when you figured out why a founder needs to be not just unusually talented and technical ability or something else, but they actually have to be really ambitious as well.

• 5:13Speaker 01

  When did I figure out that founders had to be really ambitious? I think I already knew that before we started YC because when we started YC, we already had all this experience of doing a startup ourselves, right? And so we knew that it was grueling and you need, you need something to drive you through all those obstacles. And honestly, being dutiful is not enough. The obstacles are too fearsome for mere dutifulness to do it. So there's got to be something driving you and you, you call it ambition.

• 5:47Speaker 00

  And part of ambition, I assume, is wanting to be a billionaire someday.

• 5:51Speaker 01

  Yeah, you'd be surprised, actually.

• 5:53Speaker 00

  Tell me more.

• 5:54Speaker 01

  You know what actually motivates founders day to day? The fear of failure, even though they're doing this thing that if they succeed, they'll be super rich. That does motivate them, but the thing that motivates them at the, at any given moment is the fear of like disaster, looking like a fool, the server crashing, right? Like if you're running some online service and your server's crashing, you're not thinking, I gotta deal with this because if I deal with it, I'll become a billionaire. You're thinking, oh no, the server is crashing. It will be a disaster, you know? What my, the engine of my model train set is falling off the edge of the table. I need to go and save it, right? That's what you're thinking at any given time. You just don't want your model train set to break.

• 6:40Speaker 01

  You put your head down and work on the model train set for 10 years and then you lift your head up and like, holy shit. Like if I add up the value, the value of all my shares at the current, the last round valuation, I'm a billionaire. But it takes people by surprise when it happens.

• 6:54Speaker 00

  Yeah, that's great.

• 6:55Speaker 01

  Sometimes I'm the first to tell them, like I do the math. I'm like, wait, according to your last round, you're a billionaire. And like, oh yeah, I am.

• 7:02Speaker 00

  That's what we want. And I'm curious, can you tell me a story about a founder where when they started YC, they were maybe not ambitious enough and then they became very ambitious during the batch?

• 7:12Speaker 01

  Those stories are rare because most of this quality is inborn. And so like, you know, Sam Altman famously was extremely formidable the first time I met him, before we even accepted him. And that's more the rule than the exception. So the one case where you see founders, it's not that they lack ambition. It's more like they've been trained not to show it. Because when you're young, you're often in situations where you're supposed to be obedient. You're not supposed to like go off and do what you want. You're supposed to do what people tell you. Maybe you have pushy parents who tell you to do what they want, right? And so you've never, you've never let yourself go. That's the one case.

• 7:56Speaker 01

  But even then, I would argue that the person was ambitious. They'd just been trained not to show it.

• 8:01Speaker 00

  Yeah. Actually, that's a good point because I think nowadays a lot of people think about startups like another badge that they should collect along their resume.

• 8:10Speaker 01

  And only if it fails. If it works, it's like your life's work. You don't, you don't have any more badges, right? And so what kind of badge is a failed startup? Not much of a badge. I think if people think that, they're not thinking it through, right? Like honestly, we would get, it was quite early on in YC's history when people started applying to YC for the prestige, right? Like they would apply to Harvard, hoping they would get in. But the thing is, if you apply to Harvard and get in, you should do it because no matter how stupid you are, there's easy majors you can choose and sort of slide through. You'll get a Harvard degree and everybody will be impressed with you. With startups, there's no easy majors, so, right? It's like applying to Harvard and being forced to study theoretical physics.

• 8:55Speaker 01

  It's really rough if you're not very, very hardworking and clever and determined. And so these people trying to get YC, trying to do YC as a credential, they had no idea what they were asking for. They didn't realize like this is not, this is a really, really unsuitable credential.

• 9:13Speaker 00

  There are many easier ways to get credentials.

• 9:15Speaker 01

  Yeah. Yeah. If you want to seem cool, like starting a startup is just about the least efficient way to do it.

• 9:21Speaker 00

  Yeah.

• 9:22Speaker 01

  It's brutally hard.

• 9:23Speaker 00

  Yep.

• 9:24Speaker 01

  And you won't seem cool for years, of years of brutal hardness before anyone will think you're cool.

• 9:29Speaker 00

  Hundred percent. When you were describing some of the founders before you used the word formidable.

• 9:33Speaker 01

  Yeah.

• 9:33Speaker 00

  Can you tell us a little bit more about how that word came to be, what it means to you as well?

• 9:38Speaker 01

  Well, a lot of the language of Y Combinator is, is Maya and Jessica's private language, right? And so we already had this word before we started YC, like for a certain, a certain kind of person. And I described it in an essay. I said, I think that it's someone who can, who gets what they want. That's, that's the test, right? Do you get what you want? Because how formidable are you if you don't get what you want? Um. So it's someone who gets what they want in any situation. And so if you invest in them and you have stock in their company and they have stock in this company, your interests are aligned. If they get what they want, you get what you want. So that's why investors want people who are formidable.

• 10:19Speaker 00

  Pretty good.

• 10:20Speaker 01

  Yeah, because they get a part of what the founder gets.

• 10:23Speaker 00

  So changing tracks a little bit, at startup school, Patrick Collison recently said that lean startups may be dead.

• 10:30Speaker 01

  Did he?

• 10:31Speaker 00

  And part of that is because he says, you know, it's really easy to raise money these days. AI lets you work on many things in parallel. You could, you know, spin out a bunch of agents and work on a bunch of things. Do you agree with him or would you have a rebuttal?

• 10:45Speaker 01

  Um, I've never really been clear what what a lean startup is. I mean, we already had a kind of startup that we funded in Y C and maybe it has a lot of overlap with what was described in this book, The Lean Startup, but I haven't actually read it. And so, I mean, why would I, right? Tolkien didn't read all those other fantasy books people wrote. Um, and so I don't exactly know what a lean startup is, but if you tell me what qualities you might think might be obsolete, maybe I could answer that.

• 11:13Speaker 00

  Let's say, starting with just a little bit of money on a very focused area.

• 11:18Speaker 01

  You mean, it might be dead, starting with a little bit of money? I don't think so. I think there's a lot of things you can do for cheap. I mean, tokens are very expensive at the moment. But that's just because there's a shortage of GPUs. Token prices will certainly inference prices at any given, any given level of inference go down dramatically, like thirty X a year or something like that. So even token prices are somewhat misleading because they're you're getting higher quality tokens over time. So I think, no, everything, technology always gets cheaper. I don't think, I think you can still start a startup on not much money.

• 11:53Speaker 00

  Even if it's a rocket startup or any of these.

• 11:56Speaker 01

  It's hard, it's harder to start a rocket startup on no money. But even a rocket startup, you can start on not much money because what you do is you adjust for how much money you've got. Like, you can't build an actual rocket. What you can build is you can build a design for a rocket and show that to, and you can simulate it, right? Or show it to experts. If it's convincing enough, you can go to investors and get a bit of money to do the new, the next stage. You're always able to raise another round, right? So you just do what you can on the money you got. As long as you can get to some kind of milestone, then you can convince investors to give you more.

• 12:31Speaker 00

  Yeah, I think Philip from Star Cloud was saying that they basically just wrote a white paper and booked a launch and they raised the money for Star Cloud.

• 12:39Speaker 01

  That nothing as convincing as booking a launch, right? It's gotta happen if you booked a launch. But he's a huge famous expert in the stuff he works on, right? So he comes with automatic cred.

• 12:49Speaker 00

  Right.

• 12:50Speaker 01

  It's easier for him to do that than some kid who just graduated from college.

• 12:54Speaker 00

  So let's transition to talk a little bit about AI more broadly. I'm curious, what surprised you about AI?

• 13:01Speaker 01

  Well, I was studying AI back in the nineteen eighties, a very different kind of AI that would never have worked. I mean, it was a joke. So I've been thinking about this a lot and I had a lot, I spent a lot of time thinking about what AI would eventually be like. And the way we thought it was all going to play out was you start out with like a perfect fly, right? You know what? It doesn't do much. It's like a fly, like a fly's brain, right? It can only do what a fly does, but it does it as well as a fly, right? And then you work your way up from flies to mice, you know, to cats. And eventually you get monkeys and then humans, right? But at every point, you're, you're perfect. You're doing what they do well.

• 13:44Speaker 01

  And instead, what we got was basically a full on human, but full of shit, right? Like the first, the first AIs, the first versions of Chat G P T were like an undergrad trying to bullshit his way through a paper. Something plausible sounding, full human stuff, like not even this fly stuff, full human, but like terrible, right? And so you start, and so instead of starting with perfect and then working your way up to human, you start with human and then work your way towards perfect. So it's sort of the opposite, the opposite quality ended up, ended up being the one that got optimized. That, nobody expected that. Nobody expected when the first plausible AI turned out, turned up, it would be like a bullshitting undergraduate, right?

• 14:27Speaker 00

  Just a slot, slot machine.

• 14:28Speaker 01

  Yeah. And it's still, you could still has a lot of that flavor, doesn't it?

• 14:31Speaker 00

  Yes.

• 14:32Speaker 01

  I hear all these stories about how AI is solving famous open problems in math, and I can't even get it to answer questions about when restaurants are open.

• 14:40Speaker 00

  That's what's called the jagged frontier.

• 14:42Speaker 01

  Hmm. Yeah. They must know things I don't know, or they have research versions. Maybe they can find out when restaurants are open.

• 14:49Speaker 00

  The other thing, you are, you are famously very good at taking complex topics and making them sound very simple. So what is the official P G definition of A G I?

• 15:01Speaker 01

  Oh, well, honestly, I mean, could you do better than the Turing test? The Turing, I think Turing was pretty good, right? One of the reasons, one of the ways I knew we were getting close to A G I was I actually had to go and look up the definition of the Turing test. That in itself is a piece of evidence, like, what was the Turing test again? Are we there already? I think what's happened now is we thought back in the day that AI would be sort of like this finish line and we, A G I would be this finish line, we'd cross it, it would be very clear. But when you're standing on the finish line, you realize it has width. From back in the nineteen eighties, it looks like it's just a line going across the horizon. But here you realize, okay, some bits of AI are way across the finish line.

• 15:44Speaker 01

  Some bits are like maybe in the middle of it. Who knew the line had dimension? The finish line is actually the sort of smear. And I think the best answer you can give is like, we're on the smear. It turns out to be a smear and we're on it.

• 15:57Speaker 00

  And that's why you can't get your restaurant times.

• 15:59Speaker 01

  Yeah, because they're in a bad part of the smear. Whereas the Riemann hypothesis, maybe we're already there.

• 16:04Speaker 00

  Okay, changing back to talk about startups. So the other thing you've said is that the best predictor of success for a startup is the pace that they ship new stuff.

• 16:14Speaker 01

  Yeah.

• 16:15Speaker 00

  With AI, does that change? Do you think there's a new metric?

• 16:18Speaker 01

  No, no, there's, I mean, we have all this powerful AI tools and there's still a lot of startups in this batch that are not shipping fast enough.

• 16:27Speaker 01

  And so obviously there's variation in shipping speed. It's not just the rate at which you can breeze things. You have to think of these ideas first, right? Everyone always asks me, like, with all this AI, is anything still the same? And the answer is so far, almost everything is exactly the same. The only weird, the only weird new thing is that companies have these giant AI bills. It used to be startups' big bill, big cost was salaries. That was all that mattered, salaries, right? Everything else was cheap guy by comparison, because it was just laptops and people. And now suddenly you gotta pay for GPUs, you know, giant, giant. I mean, tens of thousands of dollars a day in tokens.

• 17:05Speaker 00

  I'm also curious, how does being in a batch like Y C give founders an advantage?

• 17:11Speaker 01

  There's a bunch of reasons. One is, starting a startup is normally a very lonely business. What, you know, you have all this upside, you have complete control over what you're doing. The downside is you don't have any colleagues. And so this is like working in an office with all these colleagues, except you're all working on your own startups. So there's that, you have colleagues. You can also learn from what the other startups are doing at the same time you are. So you have some technical problem, probably somebody in the batch had that problem. You can just ask them how they solved it, right? And another advantage is what we call the Y C G D P, which is you have some sort of product, you can sell it to the startups in your batch. No, almost no matter what it is, you can find some. And they're the exact kind of users you want. Early adopters who decide quickly, right?

• 17:56Speaker 01

  And they sort of have to at least listen to your pitch.

• 17:58Speaker 00

  How did you come up with the idea for Y C?

• 18:01Speaker 01

  Uh, gradually. Initially, the idea was just going to be, we were, we, we didn't have the batch idea at first. The part we had at first was to do, was to be an angel firm. Because at that point, there were V C firms who would do these giant late stage round. And there were angel investors who were individual people investing their own money. But there was no, there were no angel firms. That was the original idea, to be an angel firm, like a V C firm, but invest small amounts of money earlier and use standardized paperwork. And then, having decided that, we thought, all right, we need to learn how to be investors, since we don't know how to be investors. We'll just fund a whole bunch of startups all at once.

• 18:42Speaker 01

  And so we thought to ourselves, well, all these college students get summer jobs working at Microsoft. Wouldn't they like to start startups instead? We'll create this alternative to getting a summer job. That's why the batch takes place during the summer. It turns out to be the perfect length, but that was just an accident. And so we thought, we'll fund a whole bunch of startups, we'll replace summer jobs, it'll be for current undergrads. They won't, we, they won't mind if we don't, if we're not real investors, because they're not real founders, right? Just a bunch of college students. And it turned out, in the course of that, we became real investors and they became real founders very quickly. And this batch thing was so great. This thing that we just discovered by accident, we thought, all right, we're going to always do investing that way.

• 19:25Speaker 00

  How has Y C changed or not changed since it's grown?

• 19:29Speaker 01

  It's changed very little. It's basically, um, like the same thing, but more of it. You know, like the problems the startups have are pretty much the same. There's a lot more of them, but, uh, but they, you know, they live in small groups that are just like individual bits of Y C. So one of the things people saying, when people say Y C has jumped the shark, one of the things they always say is, oh, it's so big now. Well, people used to say that back when we had forty startups in the batch, right? They would say, oh, come on, the old days are gone. There's forty startups in the batch, right? People are always saying that. And if you, if you divide the Y C up into little bits, where each startup is part of a pot of seventy startups,

• 20:11Speaker 01

  then it's just like they were back in twenty twelve, when there were seventy startups.

• 20:15Speaker 00

  Where do you think the next trillion dollar company comes from? What are the founders of it like?

• 20:20Speaker 01

  The founders of it are formidable. In fact, that is the answer to your question. The answer to your question, where the next giant company comes from, is it comes from the right founders, right? It's not some particular idea. I mean, it probably is some idea rather than others. It's probably not dog walking, right? Maybe, who knows?

• 20:39Speaker 00

  Maybe.

• 20:39Speaker 01

  Maybe. I mean, startups' ideas are very immutable. But it, it comes from the next trillion dollar founders is where it comes from. And they probably have good ideas, right? Whatever they're working on is probably promising.

• 20:52Speaker 00

  Do you think the founders in the future are going to look very different from the ones in the past?

• 20:58Speaker 01

  They're going to be robots.

• 21:00Speaker 00

  I hope not.

• 21:00Speaker 01

  No, no, no. Founders, they still, I mean, we now have twenty years of data. They still look exactly like they used to twenty years ago. Why should they change twenty years from now?

• 21:11Speaker 00

  Great. Thank you so much.

• 21:13Speaker 01

  Thank you.