Uncapped with Jack Altman
00:05:24 · Jack Altman, Ev Randle
[00:05:24] S0: Made Has it all work. [00:05:26] S1: It's made it all absolutely work. And I don't think it I think there was a lot of contention around the quality of the Frontier lab business model that partially answered by the numbers in the s one. Like, you cannot say that, like, Anthropic's business model isn't working on, like, a per unit basis or an aggregate basis. Like, they had 8% operate... Like, GAAP operating margins in q two twenty twenty six, so it's clearly working. I don't necessarily think that means that it's going to be a slam dunk out of the gates in terms of how public investors in the public markets value it and if there's a ton of share price appreciation right out of the IPO. There's two reasons for that. The first is that there's still some battleground topics that people have uncertainty over that I think are somewhat fair. So the first is, you know, Anthropic in q two grew massively. They grew 145 quarter over quarter. So it's like insane sequential growth, but then they didn't grow as much in q three. And there's a lot of pretty good reasons for this, but they grew 45% quarter over quarter, which is still So pretty insane. [00:06:30] S0: Nuts. But, you know, it's like the deceleration from
00:06:30 · Jack Altman, Ev Randle
[00:06:30] S0: Nuts. But, you know, it's like the deceleration from [00:06:32] S1: a 145% growth quarter over quarter to 45% growth. People are like, wait a minute. This doesn't... With SaaS, you go look at the net new per quarter of CrowdStrike or Datadog, it's just consistent upward trajectory. There's very little volatility to the growth rate, and then 80% of the revenue is consumption based. And so there's there's there's not like these... You know, if you had, like, you know, Snowflake or, you know, Databricks or one of these... It's like... A lot of that revenue is, like, multiyear long term contracts. I mean You have more, like, fixed visibility into the future growth. [00:07:03] S0: One of the things that's been surprising to me, which I wouldn't have been... I would not have guessed it, at least at this point, because it's like the last generation of model is pretty good now. But it still just seems that so much turns on who has the very best model at any given point in time. And the leading edge, even if it's by a little bit and even if the last model could do most of the tasks, it just seems like it's worth a crazy amount of momentum. And we saw this go back and forth between the labs all year. And we saw it again in the last month, and then you saw it over the summer. That part is surprising to me, that people will always seem to go for the highest intelligence even with some price and sensitivity. I think it probably is, is there's just so much surplus. And what
00:07:03 · Jack Altman, Ev Randle
[00:07:03] S0: One of the things that's been surprising to me, which I wouldn't have been... I would not have guessed it, at least at this point, because it's like the last generation of model is pretty good now. But it still just seems that so much turns on who has the very best model at any given point in time. And the leading edge, even if it's by a little bit and even if the last model could do most of the tasks, it just seems like it's worth a crazy amount of momentum. And we saw this go back and forth between the labs all year. And we saw it again in the last month, and then you saw it over the summer. That part is surprising to me, that people will always seem to go for the highest intelligence even with some price and sensitivity. I think it probably is, is there's just so much surplus. And what [00:07:50] S1: I mean by that is whether you're paying $0 or $200 for a Claude Max account or you're paying next to nothing with some free service, the value that you can get as an individual [00:08:04] S0: Right. [00:08:04] S1: Is probably in, like, at least in the thousands of dollars, if not tens of thousands of dollars. [00:08:07] S0: This is like a Keith Rabois in that there's, like, you know, two task types. There's the ones where it, like, just needs to be completed and it needs to be right. [00:08:15] S1: Yeah.
00:08:15 · Ev Randle, Jack Altman
[00:08:15] S1: Yeah. [00:08:15] S0: You don't get any more bonus points for getting any better past a certain point. And that's often, in a company context, talked about with regard to what type of executive you should hire. Are you protecting downside? Are you looking for uncapped upside? And filing taxes, for example, you either did it right or you didn't. At some point, I just have to believe those types of tasks will get saturated. But then if you think about writing code or doing sales or discovering, you know, drugs and biology or robotics, it's probably the majority of tasks people understand it as unbounded upside. Yeah. And in an unbounded upside world, if that's the mindset, you're probably always going to buy the better thing. I mean, I do still think there's... It's obvious that the sellers of tokens are doing really well. I still think that I believe it'll get there. But I don't think that in all cases, the buyers of tokens are proving to be that much more productive in all cases. [00:09:14] S1: That's... Yeah. Like, there's still [00:09:15] S0: a lot of hope going on. Yeah. And, you know, obviously, code code got from... You know, it was actually a year ago, I think, was not being productive, people were buying a ton of it. Now I think it looks like it is totally productive. But I still think we have a way to go until Perdue Farms can buy AI, and we're sure that it's a better business now. And I don't know, like, how that's gonna be don't [00:09:36] S1: know about Perdue Farms. [00:09:36] S0: I don't know about Perdue Farms. I'm just I'm just guessing.
00:09:36 · Jack Altman, Ev Randle
[00:09:36] S0: I don't know about Perdue Farms. I'm just I'm just guessing. [00:09:38] S1: Chick fil A has an amazing engineering team. [00:09:40] S0: Yeah. And you think they're supercharged by AI? [00:09:41] S1: I bet they are. Everyone everyone loves the Chick-fil-A [00:09:44] S0: don't know about robotics might help them too. [00:09:46] S1: Yeah. But Yeah. [00:09:47] S0: So I think there's a little diffusion that needs to happen on the consumption of token side. [00:09:51] S1: It's 100% true. And I think... So then... So so you have, like, weirdness in growth is, I think, one reason why people will be cautious about the stock potentially. There's debates. I think this is a core debate, which is how much cogen and related TAM. So for cogen specifically, how long does the fusion take? And then how much just cogen TAM is left? And then what is the [00:10:13] S0: next thing? How do you think about the cogen Tam? Like, you know, the analogy could be something like in in ZERP, you know, time Yeah. When everybody went remote. Mhmm. It was like Zoom got this absurd pull forward. Yep. And it was basically like everybody who wanted a Zoom account got it. And so Zoom grew ridiculously. And then it had maybe not full saturation, but, like, roughly, it got saturated. And obviously, at least in our corner of the world, everybody who might want to use AI programming has been using AI programming for a while. [00:10:46] S1: Yeah.
00:10:46 · Ev Randle, Jack Altman
[00:10:46] S1: Yeah. [00:10:47] S0: And then you have market share trades, and you have those kinds of other things, but you don't get 10x year over year from that forever. Yeah. But then you probably have a lot of other places in the economy where it's not even close. Yeah. So I don't know how [00:10:58] S1: you think about, like, the the code TAM. It is... It's funny because I, like, I think of back to your saturation point of, like, things that are saturated with, like, a Zoom call. There's a You either have the call saturation point. That's right. Can I get on? Do my headphones correct correctly? [00:11:13] S0: But you could always have another coding agent. [00:11:15] S1: You could always have... It's like you you [00:11:17] S0: have, like, 30 agents going out once probably. Right? [00:11:19] S1: All the time. Yeah. All the time. [00:11:20] S0: Building stuff. [00:11:20] S1: Just building stuff. Yeah. Just just Just technical. Figuring out how to be mean to you in our in our partner meeting. In the chat. But with Zoom, it's like there's a very clear ceiling in asymptote. And I think the really interesting thing that we've seen with code is I think there probably is some asymptote, but the asymptote isn't like a crazy place. And what I mean by that is some of our newer companies, like, companies that have been started kind of post OPUS 4.5, I'd say, the way that they build software [00:11:48] S0: Yes. Looks almost nothing. It's like nothing. [00:11:51] S1: It's Nothing like how you built software in 2019.