Invest Like the Best with Patrick O'Shaughnessy
00:22:31 · Patrick O'Shaughnessy
[00:22:31] S0: can be rebuilt. Can we spend a few minutes on models? Dropped S1 came out this Obviously, a beautiful view into the business itself. But I'm actually more interested because the infrastructure stuff in what you think about just the state of these things today. I'm interested in all the debates, closed versus open, the public frontier versus the private frontier that the companies keep for themselves, movement of talent, opportunities, things that don't exist that should, whatever's on your mind about these things and how you see them evolving, I'm fascinated to hear.
00:23:01 · Martin Casado
[00:23:01] S1: So I think the biggest question is is what happens if and when the market slows down? Because I think we've got three years of data of what happens in the existing very big fast growing market. And like what happens there is being on the frontier means you've got tremendous pricing power. Even if you're just an epsilon better than the next guy, you got tremendous pricing power. There's no demand problem. You've got basically infinite demand and so these frontier models that are the best tend to get 80% plus of the market dollar weighted and that's happened for three years. But you could argue the reason that's happening is because we've not saturated the market at all and people always gonna want the smartest thing. And so then under that view, there's nothing structural that's gonna change as long as the market's growing. And you could argue this is gonna go on for quite a while because... And what is the penetration? Point 1% or something like that? They say 3% of the enterprise, but actually from budget wise, it's like 1% or less. Right? And so there's just a lot to grow given how useful the technology is. The more interesting question to me is what happens if the market starts to saturate in pockets? So if that happens, things shift to open source. Will you lose pricing power on the frontier? One thing that we don't really do a good job of accounting for when we model out the numbers for these companies is what happens if you invest in a model and then you don't get the next model out really quickly? Let's assume that Anthropic stumbles and they don't release a model for six months. What is the lifespan do you think of the previous model?
00:24:29 · Patrick O'Shaughnessy, Martin Casado
[00:24:29] S0: A very short period of time. It's very, [00:24:31] S1: very short, which is entirely different than we've ever had in software. In software, we've always assumed some long tail. But it turns out what happens if you put out the SOTA model and everybody loves it, then something internal happens. I don't know if it's regulatory, I don't know if it's technical, I don't know if it's a breach, whatever, and then you slip three months, right? It could be the case that you lose the entire market then. In my experience, and I see a lot of these model graphs for maps companies and from pitches, I would say that lifespan of a model is three to six months. So that means you you have to release the next model. So again, for this conversation, I think it's a very interesting conversation. We should tease it apart. What happens if the market continues to grow and doesn't saturate? I think we already know because you have three years of data and it just means the frontier wins and they do a great job and they create great models. Then what happens if either the use cases saturate, meaning you don't need more intelligence, or the market starts slowing down for another reason. Nobody knows the answer to that. I think there's a very real world where the value comes crashing back down into open source and we'll see a shift that we've never seen because software's always had a long tail of retention.
00:25:31 · Patrick O'Shaughnessy
[00:25:31] S0: On this trip, I've been asking a lot of people what percent of software coding tasks are already saturated and the typical answer is very very high percentage. That's been the biggest market and yet it still seems like people are spending like crazy on Frontier tokens to do coding which it seemed a little at odds. Like if I could do it with a six month old model or something that's vastly cheaper...
00:25:52 · Martin Casado
[00:25:52] S1: Well, are two different statements. This is a great thing to dig in on but we need to be very careful. So statement number one is, I am not using more tokens. I have enough tokens. I've automated 95% already so I can't automate anymore. And I think that we're getting pretty close to that. Comment number two is therefore I can use a cheaper model does not follow from comment number one. So if you and I are competing startups, we've got Martin startup, we've Patrick startup, right? So we've got competing startups and because we're in competitive equilibria, are you gonna choose a dumber model to compete with me? In competitive equilibria, you wouldn't, You would always pay 10 times more for the smartest Yeah. Yeah. Always. Always. Always. And so there's this very open question of will you saturate tasks so that you don't need a smarter model? And I think it's very hard to do that in a Darwinistic economic equilibrium when you're actually competing. And some of them may, but I think at the end of the day, it's about can you get software out faster? Can you make it better? And can you compete in the marketplace? And that will necessarily push you to the more intelligent thing. Now that said, clearly, things will slow down because you're actually not spending more tokens. And so either you have to increase prices or you're gonna have to go broad. But in my experience, the pricing is maintained for sure. And because of the competitive equilibrium, like, you'll always want the smartest thing. And then we're just seeing a broadening use of these outside of code. General knowledge work. I'm a huge Grok user. It's like my favorite thing ever. And so I think we're starting to see, yeah, take over more and more
00:27:23 · Patrick O'Shaughnessy, Martin Casado
[00:27:23] S0: of these. Say more about your personal experience with that. What you're doing with it, what you're learning from that experience. [00:27:28] S1: My new Grok, this is so funny. [00:27:30] S0: I mean, [00:27:30] S1: I've got a [00:27:31] S0: whole automation thing going on. [00:27:32] S1: Oh, I know it's so good. Like, I just feel like I've waited my entire life for power. This technology to show up. Right? Like, I want Star Trek. I want to go home and I want my house to greet me and I want to talk to it and I want to have the face show up on the monitor and I the whole thing. We've never been able to do it and now it's kind of trivial. So I use GrokBot for a lot of stuff. Use it for personal finances. My big hobby is modular synthesis. I like synthesizers like making music. Oh, girl. But with like the nineteen seventies like patching, tweaking type stuff, it helps me with a lot of that stuff. So I use it for a lot of like standard things but my new passion project is I want Grok Bot to embody itself. I say, I want you to be the living AI in my house. That's what I want and I want it to be just like Star Trek. Help me make this happen and it's literally Buy stuff. It's literally buying stuff so I was like, oh, let's try this. Yesterday I bought a few $100 worth of gear that's coming to the house and like, I'm gonna have it embody itself so [00:28:25] S0: that what gear is it buying? I don't even know.