00:22:04 · Elad Gil, Aditya Agarwal
[00:22:04] S0: Teams is such an interesting example of that. Right? [00:22:06] S1: Yeah. So... Yeah. But it's actually an interesting example of what you said. Yeah. [00:22:09] S0: Yeah. Teams, it's fascinating if you look at it. So the early days of a startup, the primary thing you're competing with is other startups. And then incumbents often used to have five to seven years to react, literally, because they could just cross sell to everybody. And so that's Slack and Zoom versus Teams. Right? They were both like this, and then they flattened out, and then Slack had to sell. And the reason is because Microsoft bundled it in Teams, gave it to everybody, and then cut off their growth, and they won. And so in the olden days, like last decade, you had five to seven years of fighting other startups, and then an incumbent would come in. And if you could escape that incumbent, you won. Now maybe, there's less time for the incumbent triad because you can iterate so quickly on code and the markets are open and everything else. But the incumbent can also build share way faster even if if they're getting in their own way. And so there's this interesting dynamic that that timeline should shorten on both sides. And if so, we'll see what happens there.
00:22:09 · Elad Gil, Aditya Agarwal
[00:22:09] S0: Yeah. Teams, it's fascinating if you look at it. So the early days of a startup, the primary thing you're competing with is other startups. And then incumbents often used to have five to seven years to react, literally, because they could just cross sell to everybody. And so that's Slack and Zoom versus Teams. Right? They were both like this, and then they flattened out, and then Slack had to sell. And the reason is because Microsoft bundled it in Teams, gave it to everybody, and then cut off their growth, and they won. And so in the olden days, like last decade, you had five to seven years of fighting other startups, and then an incumbent would come in. And if you could escape that incumbent, you won. Now maybe, there's less time for the incumbent triad because you can iterate so quickly on code and the markets are open and everything else. But the incumbent can also build share way faster even if if they're getting in their own way. And so there's this interesting dynamic that that timeline should shorten on both sides. And if so, we'll see what happens there. [00:23:04] S1: That's interesting. I mean, you could argue that whatever baseline speed you are starting off, a startup should be able to accelerate it at a far fast start exponent. So you should have technically an advantage in a world where you can crack out a lot of code. I I would argue it's probably still harder for Microsoft or Google to generate a bunch of... But you never know. I get it. They're fast moving. They're also a good company.
00:23:04 · Aditya Agarwal, Elad Gil
[00:23:04] S1: That's interesting. I mean, you could argue that whatever baseline speed you are starting off, a startup should be able to accelerate it at a far fast start exponent. So you should have technically an advantage in a world where you can crack out a lot of code. I I would argue it's probably still harder for Microsoft or Google to generate a bunch of... But you never know. I get it. They're fast moving. They're also a good company. [00:23:27] S0: Yeah. They're good companies, and they have that distribution. And, traditionally, they've been... You know, probably the biggest hectic for them is they end that five to seven years, and maybe they have two or three years. Right? But, there is time. [00:23:37] S1: There is time. Yeah. Yeah. What is the most common mistake that you see AI startups make in our legs? Or maybe even call it startups in... Like, is there a Blah. Is there a common failure mode that is emergent based on the environment that you're in right now?
00:23:52 · Elad Gil
[00:23:52] S0: You know, I think there's two types. There's three types of failure mode. I think one type of failure mode is your thing isn't working and you stick with it too long. And it's back to, like, you should eventually iterate into something really working. And if it's taking two years and nothing's working, you should you should rethink. In most cases, if not all. Again, there's counterexamples. The second thing is there's really bad advice given to things that are working that are working for people who've never had anything work. So what used to happen is you'd get advice from founders who'd seen product market fit to founders without it, and they say go hire a sales team and scale really fast and burn a lot of money into it, and that was terrible advice. But it goes the other way. If something's really working and people tell you to buy, stay as lean as possible. They'll hire executives. Don't scale. That is awful advice. And that's where a lot of companies break for a while and other people, competitors who are gonna scale come in. And it just... It's it's, a very common pattern for things that are working that founders don't actually build out their company as a product, and they don't really go for it in an aggressive enough manner. So I think that's a big failure mode. And another failure mode is spending money on stuff that just doesn't matter. You know, you start training a crazy model on something instead of just testing something sheer with an existing, like, soda lab and just seeing if people want it. You know?
00:25:09 · Aditya Agarwal, Elad Gil
[00:25:09] S1: Maybe for that last one, I'm curious. I mean, you're deploying large amounts of capital often to a pretty early stage companies. I guess, for a lot of companies that are raising 100, 200 pretty early on in their, I would say, life cycle, have you found that they actually know how to use it well? It's kind of hard. You know? Like, if you're like,. I mean, maybe you're training the models. Maybe it's all kind of, like, ultimately That's that's I [00:25:35] S0: actually have not funded many things like that. [00:25:37] S1: Okay. I mean, so I suspect that we have the same priors because I think it's quite hard to spend a 100... Like, you know, if you raise a $100,000,000 as a seed round, you can't really pay yourself a $100,000,000. You know? You know, as a founder, you have I mean, you could. Anybody who wants to [00:25:53] S0: see how he ran all his way to her face.
00:25:53 · Elad Gil, Aditya Agarwal
[00:25:53] S0: see how he ran all his way to her face. [00:25:56] S1: You gotta see it in the back. Don't see variation in the back. Some salary. Yeah. But it's it's quite hard because your range of what you can pay yourself is pretty bounded, I think, in terms of what is accepted in Silicon Valley. There's only a certain way in which you can hire and create people. It's not easy to hire well and quake. So often, if you raise, you know, a 100 at 500, I tell people that you can do it, but it requires everything to go right, like, for 12 to 18 months. And if you had any hiccups along the way, it's really hard to zig and zag the company, which is actually opposite of what you'd expect. As most people are like, boy, raised a bunch of money. Now I can, you know, afford to get it wrong. But I actually think you can... It's it's much harder to get things wrong. You might have the money, but you don't actually have room to face instead of my ding. Yeah.