Garry Tan

“And I think Varun from Windsurf, who we hosted some time ago, he said it himself, the early stages at the beginning, the only moat that startups have is really just speed. Once you pass that and build something people want, then you figure out and go deeper into these types of moats that we're going to discuss.”

“The incredible story about Cursor, when we hosted Michael Truell to come talk to the batch, he was sharing how his product development cycle for shipping features and sprint cycles were one day. At the beginning, during 2023, 2024, around era, they would start to, every day would restart the clock and try to ship things every day. I mean, that's like insane speed. There's no big company that could ship something at that speed.”

“I think these are interesting examples because for all these AI agents, you could build a version of Greenlight or Casca or Casetext, like a demo version, in like a weekend hackathon. And I think when college students are thinking about these AI agents, I think what they have in their mind is like the weekend hackathon version of the product. And they're like, I could build that in a week. Like, how could that be defensible? And like the reason is like the version you build in a hackathon isn't useful to anyone. It's like if Casca or Greenlight fail, like the banks will lose millions of dollars. This is like mission critical infrastructure.”

“One way where this is playing out in the counter-positioning is that almost all of these house incumbents, their pricing model is they charge per seat, i.e. per employee. And this is, I think, a very big Achilles heel that they have strategically, which is that if their AI agents do a good job and actually work, those companies will need fewer employees doing this work because the work will be automated by AI agents. And in a simplistic way, that will just actually reduce, the more successful they are, the more they will reduce their revenue.”

“I mean, something sort of emerging that's very interesting in a bunch of YC startups like Avoka, for instance, they're doing customer support software, kind of like Service Titan, but for HVAC. And I think Service Titan has something like 1% wallet share, 1% of the gross transaction value of a given HVAC company, which is very small, right? But the wild thing that Avoka discovered is that they can come in as software, but then over time, they're actually getting a bigger and bigger chunk of the wallet share because they can get the HVAC people to pay them actually for the customer support piece, which is not 1% of their spend, but 4% to 10% of their spend.”

“This space is moved so quickly that in every vertical, many verticals, there's early on emerged one company that's seen as the early winner in the space. Often it's actually like the second movers, at least in the YC context, we have seen over and over again that there's advantage to being the second we were in a space. Stripe came after Braintree and Authorize.Nen, a bunch of things and was able to like actually win by just building a better product. DoorDash came after Grubhub, Postmates, various other delivery services and eventually went on to win.”

“Like the thing that still stuns me is OpenAI, ChatGBT has more consumers using it per day than Google's Gemini. I think anyone who understands the models and uses them daily would say that Gemini Pro 2.5 and Gemini Flash 2.5 are like equivalent models. Google was already one of the biggest consumer brands on the planet. It was almost certainly the biggest consumer brand on the internet. And yet somebody else came along and built the brand as the consumer AI app, and Google is like playing catch up.”

“Or try to use it to pick between two different startup ideas because they're trying to forecast five years in the future, which one will have a greater moat. Which just isn't how it works. I mean, literally, you shouldn't do that. Like a moat is inherently a defensive thing, and you have to have something to defend. Otherwise, like... If you have nothing to defend, don't worry about your moat.”

“I mean, I think it's deeper than merely like, is it obvious or non-obvious? Non-obvious sounds like in your body might feel like, you know, neutral. But actually non-obvious feels dangerous and scary. Like I could devote my life to this, waste 10 years on this and have no outcome.”

“And they weren't wrong. I remember talking to the Lyft founders the week before they launched Lyft. And they were extremely worried that they would go to jail. And they decided to like roll the dice and launch this thing anyway. I think a big reason why other people didn't launch Lyft and Uber before was utterly that. It's like it was basically illegal to do that and they were worried that they would go to jail.”

“Coinbase to me feels a little bit less. I didn't feel like crypto was well understood enough for it to be clearly illegal. If you hung out with a lot of people who were really, really into Bitcoin in 2010, 2011, 2012, the majority of people you ran across were cipher punks who said, F the state, F the laws, and we're going to have this radical freedom through Bitcoin. That's what he's contrarian bet was. It was that it's worth doing all of this extra work for a time where it wasn't clear the market even wanted it.”

“DoorDash entered a very crowded space. DoorDash, I think, was a prime example of this, because when DoorDash started, there was actually another YC company, Spoon Rocket, doing food delivery, where they would actually cook the food in these kitchens that were spread around the city. But there was this period where we're seen as just building software is not ambitious enough, and the big opportunities are going to be in going full stack. And so in a way that like DoorDash is contrary in bet was actually say, we're just going to do delivery, we're just actually going to have like an app and a marketplace, and we're not going to try to be a full stack startup, which was obviously the right bet in hindsight.”

“So the other thing that's cool about Campfire that we're seeing in a lot of enterprise startups is with CodeGen, increasingly, you can actually bring the switching cost closer to zero. Even with the idea of a forward deployed engineer, before CodeGen, it'd be like six weeks of writing custom scripts to convert one data schema to another. If the demos are very good, that six months could be two weeks. And then if you can code gen and get very, very good at a suite of tools to convert data from the schema to yours, you could have time to value in less than a month when it used to take a year.”

“So the story of Flock Safety, I remember I was still at Initialized. We were looking at companies at Demo Day. And then, funny enough, that morning, all the cars on my street in Noe Valley were broken into. And, you know, it was a professional crew. They came in and broke into every car on our street. And the police basically said, sorry, you know, unless you have a license plate, we can't do anything. Flock Safety today solves 10% of all reported crime in the United States.”

“I mean, speaking as a VC, like maybe the best exhortation I can give to the people listening is like, do not use that. Like, you know, it's merely an indicator. The more rules you have about investing, the more ways you can basically talk yourself out of making a lot of money in venture. It would be the stupidest thing in the world to use that as your only criteria for whether or not you should work on a company.”