#226 Garry Tan: Billion-Dollar Misfits — Inside Y Combinator’s Startup Formula

Y Combinator started because Paul Graham and Jessica Livingston are remarkable people. Paul was just trying to help people and follow his own interests. He knew how to make products and software that people could use. He created the first web browser-based program. He was so early on the web that it was a new idea to make software for the web that didn't require some desktop thing. He's always been an autodidact, a really great engineer, and a polymath. Paul Graham's essays became a shelling point for people who wanted to do this new thing. In 2005, he was able to get hundreds to thousands of really amazing applications from people who wanted to do what he did. The magic is it's only a 10-week program.

We spend a lot of time writing essays and putting out content on our YouTube channels, just trying to teach people how to actually do this stuff. There's a lot of mechanical knowledge about how do you incorporate or how do you raise money for the first time, and all of that is out there for free. Doing YC, being in the program, is a 10-week program. We make everyone come to San Francisco. At the end of it, it culminates in people raising about a million to a million and a half bucks for teams that are two or three people, just an idea starting at the beginning of Match.

We ourselves use software, but we also have 13 general partners who actually read applications and we watch the one minute video you post. The most important thing to me is that I want us to try the products. Sure, we can use the resume and people's careers and where they went to school. We're not going to throw that out. It's a factor in anything. But the most important thing to me is not necessarily the biography. It's actually what have you built? What can you build?

The best thing that we can do is actually brute force read. On average, a group partner will read something like 1,000 to 1,500 applications for that cycle that they're working. So the best thing we can do is humans trying to make decisions, which is maybe a little antithetical to the broader thing right now. And now it's, let's just use AI for everything. But I think that the human element is still very important.

The surprising thing that has worked over and over again is in those 10 minutes, either you learn a lot about both the founders and the market, or you don't. So we're looking for incredibly crisp communication. I want to know what is it and why are you working on it? A much better answer is, you know, well, I spent a year working on this and I've got all the way to the edge of what people know about this thing. It's like you're traveling the idea maze with the people you're talking to. At the end of those 10 minutes, you want to talk to people longer because that's what a great interview feels like.

One of the things I feel like I learned from Paul Graham, interviewing alongside him so many years, was that sometimes this person would come in, they had an incredible resume. They had the credentials of someone who I felt like should be able to do it. But then they had a mess of an interview. If in 10 minutes you cannot actually understand what's going on, it means the person on the other end doesn't actually understand what's going on and there isn't anything to understand, which is surprising.

Working with founders when they're just right at the beginning and just an idea is actually relatively low status work because it's very high status to work with a company that is worth 50 or $100 billion now. But guess what, that's 10 years from now or sometimes 15 or 20 years from now. It all starts out very low status and all the way in the weeds, like you're answering sort of relatively simple questions and you're giving relatively small amounts of money.

One of the myths of venture, maybe 10, 15 years ago, was that within nine months of funding a company, you will know whether or not that company was good or bad. About a quarter of those who raise the Series A, they do it in year five or later. That's a function of like we're funding 22 year olds, 19 year olds, 24 year olds. We're funding people who are so young that sometimes they've never shipped software before, sometimes they're fresh off of an internship. It takes three to five years to mature, to learn how to iterate on software, how to deliver really high quality software, how to manage people, how to manage people effectively give feedback.

Being around people who are really earnestly trying to build helps. The default startup scenario out there is not about signal, it's about the noise. Like you're playing for these other things, like how much money can I raise and from what high status investor. Some people sort of float off and they become seenesters. They're like oh let me try to get a lot of followers on Twitter. That's the most important thing. And then what we really try to do at YC is like when we spot that kind of stuff, it's like oh no, no, like maybe don't do that. Let's go back to product market actually building and then iterating on that, getting customers know, long term retention, all of those things are the fundamentals.

That's probably the biggest danger to people who want to be founders. It's certainly much better to find people who have a problem in the world that they feel like they can solve and they can use technology to solve. And that's like sort of a more earnest way to look at it. If you look at the histories of some of the things that are the biggest in the world, they actually start like that. There are lots of interviews with Steve Jobs and Steve Wozniak saying, you know, I never meant to start a company or ever wanted to make money. All I wanted to do was make a computer for me and my friends.

At YC, what we hope is that people actually come to San Francisco and we do strongly advocate that they stay, but it's no requirement. And then what we hope is that if they do leave, they end up bringing the networks and know how and culture and vibes, and they bring it back to all the other startup hubs in the world. One thing we spotted is that the teams that come to San Francisco and then stay in San Francisco or the Bay Area, they actually double their chance of becoming a unicorn.

The ideal founder is someone who has lived like 20 lifetimes and has the skills of 20 people. Probably the first conference that we had, the first mini conference we have when we welcome the batch in is the sales mini conference. Sales is about you having a hundred boxes in front of you and maybe five or six of those boxes has a gold nugget in them. Instead of being incredibly afraid of getting an F, just flip open all hundred boxes immediately and then you should aggressively try to get to a no, and you'd rather get a no so you can spend less time on that lead and you can get on to the next one.

When Paul and Jessica created YC, I went through the program myself in 2008, and I came out transformed. That's very explicitly what I want to happen for people who go through the batch today. It isn't just show up to a bunch of dinners and network with some people who happen to be. It's much deeper than that. I want people to come in maybe with the default worldview, and then I want them to come out with a very radically different worldview. I want someone who is much more earnest, someone who is not necessarily trying to hack the hack. They're trying to create something of great value. Did you with your hands assemble people and capital and you create something that solve some real problem, put people together, Is there real enterprise value?

The number one thing that I want that comes to mind for me is earnest. So what does earnest mean? Incredibly sincere. I think basically what you see is what you get. Like you're not trying to be something else. It's like authentic, but even humble in that respect. I'm trying to do this thing. Brian Armstrong is an incredibly earnest founder who literally read the Satoshi Nakamoto white paper and said, this is going to be the future. And let me work backwards from that future. He said, here's a thing that is broken in the world that he saw personally, and he said, this is a technology that solves real problems that I have seen hurt people and I know that this technology can solve it.

The biggest thing that is increasingly true, and we're seeing a lot of examples of it in the last year, is blitz scaling for AI might not be a thing. We are seeing incredible revenue growth with way fewer people. We have companies basically going from zero to $6 million in revenue in six months. We have companies going from zero to $12 million a year in revenue in 12 months, with under a dozen people, usually five or six people. This is the result of large language models and intelligence on tap. We are seeing companies that in the next year or two will get to 50, $100 million a year in revenue, really with under maybe 10 people, maybe 15 people tops.