创业学校：帕特里克·科利森谈学习、写作与辍学

好的，帕特里克。非常感谢你来到这里。欢迎来到创业学校。

Okay, Patrick. Thanks so much for being here. Welcome to Startup School.

很高兴来到这里。我和哈吉 20 年前第一次见面，我们一起创办了一家公司。我本来想做个介绍的。

Great to be here. Harj and I first met 20 years ago and we started a company together. I was going to give away the introduction.

是啊，我以为这是我的采访，但你继续吧。你做得很好。

Yeah, I thought this was my interview, but keep going. You're doing a good job.

嗯，很多很多年前我们一起创办了一家公司，我从哈吉那里学到了很多。所以做这件事真的很有趣。

Well, 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.

好的，让我们……嗯，实际上，说到这个，当我 20 多年前第一次见到你时，你当时最令人印象深刻的成就，我认为是 Chroma，你的 Lisp 方言。

All right, let's... Well, actually, speaking of that, when I first met you 20-something years ago, at the time your most impressive achievement, I would argue, was Chroma, your dialect of Lisp.

这里有 Lisp 程序员吗？哦，哇。好吧，那是……我想我听到了一声欢呼，这比我预期的要多。但是，是的，我高中时真的很喜欢 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.

是的，所以我想问的是，今天一个多产的 16 岁少年大概可以直接让 Claude 写他们的 Lisp 方言。你会建议他们不要那样做，而是仍然自己写吗？这种事情还有价值吗？

Yeah, so what I was going to ask is, a prolific 16-year-old today could presumably just 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?

我不知道。我经常思考。是的，就像我说的，一方面，以前写所有这些汇编和机器代码、优化指令、在内存中做布局等等真的很有趣，现在我们不再需要那样做了。编译器替我们做了。我们不会太怀念它。所以也许同样地，我们不应该怀念源代码。我们应该完全超越向 Claude 下达指令的层面，但在情感上我怀念它。

I don't know. I wonder a lot. Yeah, like I was saying, on the one hand, it used to be really fun to write all this assembly and machine code and to optimize your instructions and make layout in 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 Claude at all, but emotionally I miss it.

那……我想，就像我一直和这些学生待在一起，他们非常……也许背后的问题是，他们中的许多人只是想知道在大学应该学什么？比如，在这个 AI 世界里，他们应该尝试从第一性原理学习和推导多少，又有多少应该直接外包给 AI？

How about... I think, just as I've been hanging out here with these students, they're so... maybe the question behind it is many of them are just wondering what should they be learning at college? Like, 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?

对。我对这个的模型是缓存。你知道，C-H，不是 S-H，杰夫·迪恩有一组著名的数字，每个程序员都应该知道——带宽和延迟，以及你在构建系统时应该用来推理的相关常量。显然，考虑构建任何系统或分布式系统或什么的，所有查找和不同组件之间的所有相关带宽都是非常不同的，对吧？从 L1 缓存检索与从 RAM 检索非常不同，与跨网络检索等也非常不同。我认为知识也是这样。好吧，是的，你可以让智能体或什么东西为你计算或查找某些东西。那比在认知 L1 缓存中知道它要慢得多。而且你大脑中的往返次数可以比你通过超级耳语或打字等方式多得多。所以，我认为，即使承认模型的全部能力，我仍然认为在很长一段时间内，神经元查找会快得多。然后，如果你从显示性偏好来看公司自己在做什么，无论是像 Stripe 这样的公司还是实验室之类的，似乎仍然对认知能力有巨大的溢价。所以，我不会……我认为在证据表明我们已经饱和了这些好处之前就放弃它，那还为时过早。

Right. My model of this is cache. You know, the C-H, not an S-H, where Jeff Dean has this famous set of numbers that every programmer should know—bandwidths and latencies and just kind of relevant constants you should have to reason about as you build systems. And obviously, thinking of building any system or distributed system or whatever, all lookups and all relevant bandwidths between different components are very different, right? Retrieving something from L1 cache is very different from retrieving from RAM, is very different from retrieving across the network or whatever. And I think it's like that with knowledge. Fine, yes, you can ask the agent or something to compute something for you or to look something up for you or 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 super whisper or typing it out or whatever. And so, I think, even granting the full capabilities of the models, I still think for a long time to come, neuronal lookups will be much faster. And then, 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.

有没有一些具体的事情，也许你个人，无论是个人还是作为 Stripe 的首席执行官，你仍然故意选择自己做，从你自己的缓存中检索，尽管智能体可能会做得相当好？

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?

我仍然自己写作。无论是从哲学上还是具体地、实质性地，我都不喜欢模型的写作。我的意思是，这很有趣，对吧？因为这些可以证明雅可比猜想之类的。所以显然它们有能力完成这些巨大的壮举。但不知何故，我仍然没有读到一篇我觉得非常有说服力的 LLM 文章。现在，也许只是很难在那个领域进行强化学习限制，因为效用函数之类的东西有点难以定义。但是，是的。我认为写作是一种……人际沟通和写作我认为非常基础，所以能够在现实的多维空间中明智地推理。在某种难以形容的方式上，我觉得模型在这方面仍然有所欠缺。所以我从来没有……还没有发送过，你知道，现在每个工具都试图用预先写好的建议提示我，无论是 Gmail 还是显然 WhatsApp 刚刚推出了这个。我想我这辈子还没有发送过任何一条这样的建议。

I still write myself. Both philosophically but also specifically, substantively, I 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, maybe it's just very hard to 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 so 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... yet to send, you know, every tool is now trying to prompt me with pre-written suggestions, whether it's Gmail or apparently WhatsApp just rolled this out. And I think I've still sent zero of those in my life.

那……如果你谈谈 Stripe 的故事，特别是早期。你在麻省理工学院，然后你离开去创办 Stripe。你是怎么考虑那个决定的？显然我们在一个满是大学生体育场里。他们应该怎么考虑？他们怎么知道提前离开大学去创办公司对他们来说是正确的决定，还是留下来？

How about... 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?

是的，嗯，我认为我有一个稍微不寻常的特点，就是两次从大学辍学去创办公司。所以也许要知道的一件事是，这不是完全不可逆的。你可以辍学，实际上还可以回来。所以我在大一学期后辍学，和哈吉一起创办了这家公司。那非常有趣。然后过了几年，我回去了，在麻省理工学院又读了一年，然后再次辍学去创办 Stripe。你知道，我上大学的时候，可能像这里的很多人一样，我对自己的生活有一个愿景，包括成为一名学者，我真的很喜欢物理，我想，你知道，我会做所有这些物理的事情。太酷了。我读了所有费曼的书，所有这些。我想……嗯，在爱尔兰长大，我没有意识到……我没有怎么想过创业的可能性。向这里其他爱尔兰人问好。我的意思是，在那个时候，在前寒武纪时代，创业即使在校园里也肯定不那么出名，等等。你知道，当我辍学时，人们觉得这非常奇怪。我认为，总的来说，如果你喜欢大学，我实际上会……我认为完成学业没有坏处。我当时感到一种真正的紧迫感，我认为事后看来这有点不必要。

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 Harj. That was super fun. And then after a couple of years of that, went back, did another year at MIT, and then dropped out again to start Stripe. And you know, 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... 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 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. You know, 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.

嗯，但如果你不喜欢大学，那就算了，你知道，这不是你的菜。它不是让你着迷的东西。你并不真的想学那些物理之类的东西。我觉得很多父母认为辍学风险很大，会损害你一辈子的名声等等。但据我所知，从来没人真正在意过。所以我认为你没必要辍学，但辍学的代价也确实微乎其微。

Um, 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 impugns 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 costs of doing so are de minimis.

你当时感受到的紧迫感是什么？

What was the urgency you were feeling?

紧迫感？

The urgency?

是啊，就是出去做点事情的那种紧迫感。

Yeah, to go out and do something.

我不知道。人生苦短，对吧？我的意思是，那是一种普遍的匆忙感。我觉得我们很多人——我相信在座很多人——都会进入那种速通高中的模式，然后一旦上了大学，就会想，显然我也想速通大学，做所有的事情。所以有一部分是那个原因。还有一部分是 Marc Andreessen 也提到过的一个版本。我当时觉得硅谷创业公司里的很多机会都是转瞬即逝的。如果我们当时不建，那么三四年后就不可能再做了。也许所有机会都会消失。事后看来，我觉得那是个糟糕的直觉。几十年来，硅谷一直有大量的机会，这一点相当稳健可靠。是的，我觉得主要是这两个原因。

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 a bit of that. A bit of Marc 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. 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.

我觉得——我的意思是，我们现在和学生交谈时经常听到这个，他们想集体辍学的原因之一，似乎是他们担心现在就是那个时刻，他们有点——我觉得流传的说法是，如果你不辍学去创业赚大钱，你就会被困在永久底层阶级。所以，在座各位是否都应该担心被困在永久底层阶级？我想这就是问题所在。

I think it's—I mean, this is a very common thing that we hear when we talk to students now, is that part of the reason they want to drop out en masse, it seems, at this point, is they're worried that actually now is the moment that they're 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, should everyone here be worried about being stuck in the permanent underclass? I guess is the question.

我认为人类一直对那种千禧年式的模型情有独钟，认为一切很快就会终结，社会将发生永久性的转变等等。实际上，有一本很棒的书叫《有翼的福音》。人们认为在航空发明之后，文明就进入了——人类作为一个物种进入了新时代，一切都将不同。我的意思是，显然航空是一件大事，但我认为它并没有像当时一些兴奋的支持者所想象的那样，带来社会学意义上的重写。所以，预测任何事情都很难，尤其是未来，但我认为这不会是创业的最后几年。

I think humanity has always had an affinity for these millenarian sorts of 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, civilization was just entering—humanity as a species were entering a new era and nothing was going to be the same. I mean, 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 the future, but I would take the under on this being the last couple of years to get a company going.

有道理。回到 Stripe 的故事——Stripe 表面上看起来是个好主意。比如在第一天，互联网很重要，钱很重要，把这两者结合起来。大概当你去告诉别人你想创办 Stripe 时，大家都会说，嘿，这是个很棒、显然很好的主意吧。

Fair enough. 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, combine those two things. Presumably that is how it went when you went to tell people you wanted to start Stripe, and everyone just said, hey, this is a great, obviously good idea.

这有点好笑。这是——我们从 YC 学到的一件事是，专注于非常具体、易于解释的客户问题的重要性。很容易凭空想象或虚构一个客户问题，但实际上并不是一个愿意付钱的人能切身感受到的。所以在某种程度上，在共同开发 Automatic 的过程中，我们遇到了这个问题，就是处理互联网上的资金流动或支付非常烦人。一方面，这似乎是一个明显的好主意，因为没有人喜欢现有的做法，而且这些做法普遍非常不受欢迎，有点过时和遗留，你必须填写所有文书工作，亲自去银行，文书还是拉丁文的，总之都很糟糕。但另一方面，两个小孩创办金融服务公司似乎有点荒谬，而且当时金融科技作为一个行业并不存在——这个词字面上都不存在。所以我们觉得自己就像谚语里穿着风衣的松鼠，试图伪装成真正的企业或严肃的成年人，但对这个领域显然一无所知。当然，我们遇到和推销过的很多人，或者我们谈过的银行、合作伙伴等等，我的意思是，他们没有真的把我们笑出房间，但你会看到他们在桌子底下找按钮叫保安把我们拖出去，因为这看起来太不可能了。所以，我想说，这既是一个明显的好主意，因为人们真的想要这个，但也是一个坏主意，因为没有人认真对待它。但我认为，最终它植根于如此具体、真实、实际的用户问题，这拯救了我们。

It was kind of funny. It was—so something we learned from YC was the importance of focusing on very concrete, easy-to-explain customer problems. It's very easy to hallucinate or 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 Automatic together, we had encountered this issue of it being really annoying to deal with movement of money or payments on the internet. 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 you had to fill out all this paperwork and go to the bank in person, and the paperwork was in Latin, and 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. So 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, you didn't literally laugh us out of the room, but you kind of see them looking for the button to call security under the desk to have them haul us out, because it just seemed 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 it seriously. But I think the fact that it was ultimately grounded in such a concrete, actual, real user problem saved us.

你实际上——说到这个——为了真正构建产品，你必须找到银行合作伙伴，做典型软件公司不必做的事情。作为两位年轻创始人，你最终是如何说服银行信任你的？

You actually—speaking of that—how did you, 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?

是的，嗯，实际上这不是对你问题的回答，但当我坐在这里时，有一件事让我印象深刻，那就是我们决定创办 Stripe 的原因。约翰和我在大学时在一起。他当时是大一新生，我们去了 2009 年在伯克利举办的 Startup School。我们觉得那很酷。所以之后我们去 Potrero 吃了寿司，然后我们走回来，我们想，你知道，我们一直在琢磨支付这个想法，或者我们一直在思考这个领域。就是在那个晚上，在 Startup School 之后走回来的路上，我们决定创办 Stripe。我清楚地记得我们在路上的确切位置，也记得我们彼此说的话，那就是：“是的，你知道，我们不妨试试，因为可能不会太难。”

Yeah, well, actually this is not an answer to your question, but just a thing that strikes me as I sit here is the reason we decided to start Stripe. 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. We thought it was pretty cool. So we went to get sushi afterwards in Potrero, and we were walking back from sushi, and we're like, you know, we'd kind of been kicking around this idea for a payment thing, or we've been thinking about the space. And it was walking back that evening after Startup School that we decided to start Stripe. I remember literally where we were in the road, and I remember what we said to each other, which was, "Yeah, you know, we might as well, because it probably won't be that hard."

好的。所以，这个故事的寓意是，今晚去 Potrero 吃寿司，你可能会创办下一个 Stripe。

Okay. So, moral of the story is go get sushi in Potrero tonight and you might start the next Stripe.

是的，要小心这些终极的“剃牦牛毛”式琐事。我们以为可以在大学期间顺便做做，你知道，花几个月时间，但那几乎是 17 年前的事了。

And yes, beware of these ultimate yak shaves. We thought we could do it on the side while in college, you know, take a couple months, and that was almost 17 years ago.

当时，我记得你也很不寻常，因为你花了更长的时间才进行大型公开发布。尤其是在 YC 的世界里，座右铭很大程度上是尽早发布、快速发布、走出去并迭代。

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.

你能稍微跟我们讲讲那件事吗？你为什么那样做？

Could you maybe just talk us through a little bit about that? So, why did you do it that way?

是的，我们在学校结束后的那一周开始认真做 Stripe，但因为大学不是全日制，我们在 2010 年夏天才开始全职投入。我们在 2011 年 9 月公开发布，距离写下第一行代码、创建仓库差不多两年。等两年才发布似乎——我的意思是，我听说过，如果我们每周去参加 YC 会议，肯定会被敲脑袋。我认为在很多领域，那可能是错误的做法。在我们的领域，回答你上一个问题，我们必须在安全、合作伙伴、资金流动、基础设施和可靠性等方面做大量工作。我们只是觉得，如果没有把这些前提条件和基础设施准备好，就无法扩展一个真正好的自助服务体验。拯救了我们、让我们没有完全在荒野中徘徊的是，我们几乎从一开始就有生产用户。所以，09 年秋天写下第一行代码，2010 年 1 月我们有了第一个真实生产用户，大约在开始工作两个月后。它功能很少——非常初级和不完整。我们的第一个生产客户是 Twilio North 公司的 Ross Boucher。它只能做一件事：刷卡收款。所以 Ross 会刷卡，然后问一个非常合理的问题，比如“我怎么能查看我所有的收款？”于是我们写了一个小仪表盘。然后他说“我想退款”，我们就构建退款支持。几周后，他问“我什么时候能拿到我的钱？”这也是合理要求，所以我们构建了那个功能。这非常像即时开发。我们从很早就有生产客户，在私测阶段，我们每个月都增加客户数量，一直到公开发布。每周我们都有真实的客户反馈、请求和新用户进来。我们从现实中学习，而不是从我们自己假设或外推的概念中学习。如果你有那样一条扎实的反馈流，可能不急着“发布、发布”也没关系。

Yeah, so we started working on Stripe seriously the week after our school ended, but since college wasn't full-time, we started working full-time in the summer of 2010. We launched publicly in September 2011, almost two years after the first lines of code were written and the repo was started. Waiting two years to launch seems—I mean, I've heard that if we'd been going to YC meetings every week, we'd have been bludgeoned on the head. I think in many domains, that probably is the wrong thing to do. In our domain, to answer your last question, we had to do so much around security, partners, money movement, infrastructure, and reliability—all those things. We just didn't feel like we could scale a really good self-serve experience without getting a lot of the preconditions and infrastructure in place. The thing that saved us and meant it wasn't a total walk in the wilderness was that 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, about two months into working on it. It did very little—it was very larval and incomplete. Our first production customer was Ross Boucher at a company called Twilio North. All it could do was charge a card. So Ross would charge the card, then ask a very reasonable question like, 'How can I look at all my charges?' So we'd code up a little dashboard. Then he'd say, 'I want to refund a payment,' so we'd build refund support. After a couple of weeks, he asked, 'At some point, do I get my money?' Also a reasonable request, so we built that functionality. It was very just-in-time development. We had a production customer from very early, and in private beta, we increased the number of customers every single month all the way to public launch. Every week, we had actual customer feedback, requests, and new users coming in. We were learning from reality rather than our own hypothesized or extrapolated conception. If you have a significant stream of grounding like that, it's probably okay not to be like, 'Launch, launch.'

你什么时候——我是说，你是 YC 的专家合伙人。你同意吗？

When do you—I mean, you're an expert YC partner. Do you agree?

这是个好问题。是的，我的意思是，这就是建议的通病——它太泛化了。尤其是在创业公司，例外证明规则，对吧？当然，如果失败的代价很高，那你几乎肯定需要花更长时间来构建。我能稍微跑题一下吗？我对此很好奇：我们刚才在讨论编码智能体，以及廉价快速构建和产出软件的能力。我想知道，人们是否应该更多地走这条路？一般来说，人们是否应该对自己发布的第一版产品更有野心？还是说，从狭窄和专注开始，然后一旦知道人们想要什么再扩展，这仍然是根本的好产品设计？

That's a good question. Yeah, I mean, this is the issue with advice in general—it's so generalized. Especially in startups, the exception proves the rule, right? Certainly, if the cost of failure is high, then you almost certainly have to take longer to build. May I go on a slight tangent? Something I'm curious about related to this: we were talking about coding agents and the ability to 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 they launch is? Or is it still fundamentally good product design to start narrow and focused, then expand once you know what people want?

是的，这是个好问题。我认为在 AI 时代，可能——我不知道，在某种程度上 YC 会是这里的专家——但有整个传统的精益创业教条，正是你所说的：从买 Google 广告之类开始，找到一个缝隙，然后从那里激进扩张。你当然可以想象那会变得更加竞争激烈、被更激进地耕耘，很难找到那些小利基。互联网比 20 年前那些想法出现时大得多。采取这些真正发散的起点，没有其他人试图占据那个领域，可能更——基本上，也许在 AI 时代你必须更积极地解相关。有趣的是，过去 10 年最成功的公司中有多少是非常反精益创业的，对吧？无论是实验室本身还是 Anduril——你可以列下去。很多都有这个特征。也许更好的说法是：20 年前，精益创业方法几乎是唯一可做的，因为资本可用性，也因为 AI 没有让组建一个具有许多潜力和能力的组织变得如此容易。现在，我认为你可以从一开始就启动这些更激进、更有雄心的东西。

Yeah, it's a good question. I think probably in the era of AI—I don't know, and to some extent YC will be the expert here—but there's the whole traditional lean startup doctrine of exactly what you say: start by buying Google Ads or something, identify a crevice, and aggressively expand from that. You can certainly imagine that becomes much more competitive and aggressively tilled, making it hard to find those little niches. The internet is a much bigger place than it was 20 years ago when some of those ideas emerged. Taking these really divergent starting points where nobody else is trying to occupy that territory might be more—basically, maybe you have to more aggressively decorrelate in the era of AI. It's interesting to think about how many of the most successful companies over the last 10 years are very anti-lean startup, right? Whether it's the labs themselves or Anduril—you can go down the list. A lot of them have this characteristic. Maybe a better way to say it is: 20 years ago, the lean startup approach was almost the only thing to do because of capital availability and because AI didn't make spinning up an organization with many potentialities and capabilities so much easier. Now, I think you can start these much more aggressive and ambitious things up front.

在 YC 内部，可能现在在创业界，你以项目中的“苦差事盲区”一词而闻名。Stripe，至少表面上，涉及很多苦差事——我猜那些不是你 intellectually 最感兴趣的工作。我总觉得这对你来说特别有趣，因为你刚才提到你对物理学有学术兴趣，而且你显然是一个深刻的知识分子，有很多兴趣。随着 Stripe 成长为这样一家大公司，你在哪些方面放弃了 intellectual 回报，又获得了哪些？

Within YC and probably the startup world at this point, you're famous for the term 'schlepp blindness' from the program. Stripe, at least on the surface, involved a lot of schleps—things I presume you weren't intellectually most interested in working on. I always found that especially interesting for you because you just mentioned you had academic interests in physics and you're clearly a deep intellectual with many interests. As Stripe has grown into this big company, in what ways have you given up intellectual rewards, and which ones have you gained?

是的，在任何公司都有很多本身并不那么有回报或有趣的事情。设置工资单——没有人创业是为了设置工资单。当然，构建商业金融服务有各种更晦涩和广泛的版本。我认为在这一点上，我实际上对 Stripe 感到非常幸运。

Yeah, in any company there's a bunch of stuff that's not that rewarding or interesting in itself. Setting up payroll—no one starts a company so they can set up payroll. Certainly, building business financial services has all sorts of more arcane and extensive versions of that. I think I actually feel extremely lucky with Stripe in this respect.

我认为这件事你不需要一开始就想太多，但一旦你开始想，也许在筹集大笔资金之前，你自然会担心失败的可能性，失败会发生什么，以及如何减轻和避免失败。我认为你需要问相反的问题：如果你成功了会怎样？你筹到了钱，有了客户和员工，还有一大堆事情。你会享受这些吗？你愿意为此工作 10 年、17 年、30 年吗？我的意思是，甲骨文的拉里·埃里森都快干半个世纪了，对吧？所以，如果你成功了会怎样？就 Stripe 而言，我真的很喜欢，因为我们与世界上最有意思、最具创新性的公司合作。比如，特拉华州 25% 的公司都是通过 Atlas 在 Stripe 上创立的。我们与他们合作，听取他们的反馈和请求，贯穿他们从起步到成为 Shopify、OpenAI 等杰出成功企业的整个旅程。哦，说到 Atlas，我们为 Startup School 的每个人提供免费的 Atlas 公司注册。所以，如果你们今晚晚餐时突然有了创业的冲动，只需发邮件到 startupschool@stripe.com，我们就会给你免费 Atlas 的链接。但话说回来，我认为 PG 抓住了某些东西，确实有很多琐碎的任务，但从 Stripe 的整体来看，我觉得它非常有趣。每家企业都是关于世界某个方面或某个市场如何运作的应用理论，或者一家拥有新模式的新公司如何成为对某种反事实的逆向论点。我从未遇到过让我觉得无聊的 Stripe 客户。所以，整个业务与“琐事盲区”的本能恰恰相反。

And I think this is something you don't need to think about that much up front, but once you think about it, maybe before you raise a significant amount of money, you always worry naturally about the possibility of failure, what will happen if you fail, and how to mitigate and avoid failure. I think you need to ask the converse of that: what if you succeed? You raise money, you have customers and 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, half a century soon, right? So, what if you succeed? In the case of Stripe, I really love it because we're working with the world's most interesting and innovative companies. Like, 25% of all Delaware corporations are started with Stripe via Atlas. And we get to partner with them, work with them, hear from them, get their feedback and requests, through the entirety of the journey up to being the Shopifys and the OpenAIs and all the standout successes. Oh, and 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, just email startupschool@stripe.com and we will get you your link for free Atlas. But yeah, I think PG latched onto something where there are all these kind of menial tasks, but in the 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 a new company with a new model is a contrarian thesis on some counterfactual. I've never met a Stripe customer and thought that's boring. So the business as a whole has been the opposite of the Schlep Blindness instinct.

你对此有特别独特的视角，因为你与大型模型提供商、大型实验室公司合作，也与所有快速增长的 AI 初创公司合作。昨天这里经常提到一件事，老实说在批次内部也经常出现，就是人们担心自己的想法会被大型实验室提供商碾压。我想听听你的看法，我很好奇人们应该如何看待这个问题？

And 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 the fast-growing AI startups on the ground. Something that came up a lot here yesterday, and honestly comes up within the batches too, is people are worried about whether their idea is going to get trampled by the big lab providers. I'm giving your perspective, I'm just curious how should people think about that?

是的。预测很难，当然实验室是非常有能力、有实力的组织。也许你应该稍微区分一下：是快速提升的 AI 能力会做到这一点，还是实验室本身会做到这一点？我认为总的来说，回顾 20 年，没有任何组织的记录是完美的，谷歌就有这种感觉。当我们做自动的时候，我们公司和所有其他公司总是问：如果谷歌做了这件事怎么办？谷歌似乎无所不能，拥有大量才华横溢的人才，基本上可以无限获取资本和服务器。但人类组织是复杂的，很难同时积极推行 100 个不同的优先事项，并处理它们之间出现的所有问题和干扰。谷歌在很多特定领域做得非常好，但并不是说谷歌做了所有事情，即使从某种基本物质意义上讲，谷歌也许有能力做到。所以这方面的记录是喜忧参半的。总的来说，我认为这种恐惧被夸大了。现在，有一个更具体的问题：就是模型本身。忘掉实验室。即使实验室不特别热衷于扩大范围，从长远来看，智能体能力也会消除很多特定的垂直领域或任务。很难说，显然取决于你对模型能力的预测，但在某些情况下，我确信这会发生。在某些领域，它已经发生了。看看 Stripe 的数据，我想说一件与在座各位相关的事情：现在创业的公司比一年前多得多，比 5 年前多得多。去年和今年之间的相对变化是我们所见过的任何一年中最大的相对变化。例如，从 2019 年到 2020 年，我们看到了很大的跳跃，在疫情期间可以理解。从 2020 年 2 月到 4 月，新创业公司的年增长率可能达到了 50% 左右。就在我说话的时候，在 Stripe 上创业的公司数量同比增长了大约 2 倍，这又是我们见过的最大相对跳跃。你可能会想，好吧，有更多“氛围编码”的轻量级垃圾。也许有更多东西，但它们真的成功了吗？实际上，中等规模的企业今年比一年前做得更好。如果我们分层来看，任何一家企业达到某个收入门槛（100 万美元、500 万美元、1000 万美元）的概率似乎都在提高。通过 Atlas 注册的新公司实现收入的时间在缩短。从我们能看到的客观指标来看，现在似乎是创业的最佳时机。话又说回来，事情可能会变。我不知道 5 年后的世界会是什么样子，但就今天，2026 年 7 月 26 日而言，Stripe 的数据表明，从来没有比现在更好的时机。

Yeah. Predictions are hard, and certainly the labs are very competent, capable organizations. And maybe you should 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 no organization, if we go back 20 years, there's some sense with Google. When we were doing automatic, the question was always for our company and every other company: what if Google does this? Google seemed omnipotent, with immense numbers of incredibly talented people and essentially infinite access to capital and servers. But human organizations are complicated, and it's very hard to aggressively prosecute 100 different priorities and deal with all the issues and interference that arise among them. 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 basic material sense, Google maybe had that ability. So the track record of that is checkered. In general, I think that fear has been overstated. Now, there is a more specific thing: just the models themselves. Forget the labs. Even if the labs aren't particularly ambitious about expanding their scope, literally at length, agentic capabilities will obviate a bunch of specific verticals or tasks. Hard to say, obviously contingent on one's forecast of model capabilities, but in certain cases, I'm sure that will happen. In certain domains, it has already happened. Looking at Stripe data, one thing I will say that is germane to people here: there are many more businesses getting started now than there were a year ago, way more than 5 years ago. The relative change between last year and this year is pretty much the largest relative change we've seen in any given year. For example, from 2019 to 2020, we saw a big jump, understandable during COVID. From February to April of 2020, the growth rate inflected to maybe 50% year-over-year in terms of new businesses getting started. As I speak, the number of new businesses starting on Stripe is up around 2x year-over-year, which again is the largest relative jump we've seen. You might think, okay, there's way more vibe-coded, lightweight slop. Maybe there are more things, but are they actually succeeding? Actually, the median business is doing better this year than a year ago. If we stratify and look at the probability that any given business will reach some revenue threshold—a million dollars, five million dollars, 10 million dollars—those all seem to be getting better. The time to revenue for new companies incorporated with Atlas is declining. By all the objective metrics we can look at, it seems to be a better time than ever to start a business. Then again, things can change. I don't know what the world will look like in 5 years, but speaking today on July 26th of '26, the Stripe data would suggest there's never been a better time.

在批次内部肯定如此。

Certainly within the batch.

我们在 YC 批次中看到了完全相同的情况。公司就是能比以往任何时候都增长得更快。过去，在我们刚开始创业的时候，达到 100 万美元的收入——比如经常性收入——是件大事。人们会知道那家公司。

We see the exact same thing in the YC batches. Companies are just able to grow faster than ever. It used to be, back in the old days when Arge and I were first starting out, getting to a million dollars of revenue—like running revenue—was a big deal. People would know about that company.

他们会说，你懂的，我听说某家公司营收达到了一百万美元。而现在，我的意思是，我不……

They'd be like, you know, I heard that X company got to a million dollars of revenue. And now, I mean I don't...

是的，实际上……你应该……嗯，第一个月感觉就像那样。

Yeah, that's actually... you should be... Well, your first month it feels like.

你应该……嗯，这对每个人来说都是夸张的说法。但我的意思是，在 YC 生命周期的那段，比如从第零天到第九十天，我认为真正驱动增长的是企业愿意从初创公司购买，这是新现象。所以，你可以在批次内签署这些新合同。随着公司不断成长，你掌握了数据。我很好奇，还有哪些因素在推动这种从 1 到 10、从 10 到 100 的拐点式增长曲线？

You should... um, that's an exaggeration for everyone here. Um, but I mean I certainly within sort of like the YC part of the life cycle, like day zero to 90, it's really being driven by, I would say, enterprises willing to buy from startups, which is the new thing. So, you can sign these new contracts within like the batch. Um, 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 one to 10 and 10 to 100?

我认为这正是你提到的动态，即各地的企业都更有弹性去适应和尝试新事物。他们非常害怕因过时和落伍的运营方式而被淘汰。所以，在正常情况下，你是一个新初创公司，你有某种机制来做各种事情，然后你向某家公司的 CIO 或 CTO 或其他人推销，他们不太想理你，因为，你知道，你的东西未经验证。也许你两年后就不在了。你知道，所有那些明显的反对理由。但现在，人们知道维持现状的风险其实极高。所以，即使做所有新事物有风险，这条路看起来也很危险。因此，我真的认为现在是初创公司销售产品并让产品一经推出就被大规模采用的最佳时机。最近很多 YC 公司已经证明了这一点，但我认为这是一个非常普遍的现象。而且我觉得还有一点，Stripe 显然不是一家面向消费者的公司，但你知道，我认为在消费者领域也有类似情况，消费者对 AI 的看法很复杂，也许他们不想要数据中心，但人们对产品非常着迷，我认为他们被这些产品迷住了，并且有一种尝试新事物的倾向和开放态度。

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 whoever at some company, and they kind of don't want to talk to you because, you know, your thing is not validated. Maybe you won't be around in 2 years. You know, all the kind of obvious objections. But now, people know that 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, you know, pretty meaningful scale right out of the gate. A lot of YC companies in recent times have demonstrated this, but 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 products 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.

嗯，也许更广泛地说，我好奇的是，凭借 Stripe 拥有的这些数据，在过去 12 个月里，你在数据流中看到的任何东西是否改变了你对 AI 的总体看法？

Um, maybe just more broadly something I'm curious about is again with this the data you have at Stripe, has anything you've seen in that data stream changed a belief you have about AI broadly say over the last 12 months?

我的意思是，有一种恐惧认为 AI 将成为一种霸权、集中化、总体化的力量，少数公司会吞噬经济的很大份额。许多 AI 前沿公司确实做得非常好，我认为它们会继续做得非常好，这是肯定的。但根据我们在 Stripe 看到的情况，其他公司要么在起步、利用这些新能力，要么现有公司在重新调整，这种渴望和强度让我不再以同样的方式担心集中化。我认为会有成千上万的赢家。再说一次，我们尽量不做任何明确的预测，因为未来不是注定的，但根据我们看到的趋势线，我认为我们正走向一个更加去中心化的世界，一个更广泛繁荣的世界。

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. And many companies at the forefront of AI have done incredibly well and I think we'll continue to do incredibly well, for sure. But based on what 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 cuz 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.

是的，酷。好了，我想今天的时间就到这里。非常感谢 Patrick 的参与。

Yeah, cool. All right, well, I think that is all we have time for today. So thanks so much Patrick for me.

谢谢你邀请我，嗯，如果我不说 Stripe 没有 YC 就不会存在，那就不对了。

Thank you for having me and um, it would be remiss of me not to say that Stripe would not exist without YC.

好的，酷。好的，非常感谢，再见。

All right, cool. All right, see you so much.