Uncapped with Jack Altman
00:19:35 · Ev Randle, Jack Altman
[00:19:35] S1: And five to 18 to maybe 40 to 50 or something. [00:19:37] S0: It's like now, five to 18, it's like, I don't know if you can raise. I don't know if there's capital. [00:19:40] S1: Would you I don't know. Like, would you look at a five to 18 or what would it take for you [00:19:43] S0: to look at? Need in this in this environment, you would need to believe an 18 to 100 story for the next year, or you would just need to think that they were doing something that was so difficult and unique that it just had insane growth durability forever after that. But on the surface, that used to be enough where everybody would be super interested if all you heard was it's a software company going five to 18. Yep. Whereas now, if that's all you heard, you'd be like, well, why wasn't it five to 40? [00:20:10] S1: That's right. [00:20:10] S0: Which is insane. It's so insane. But it's all because of [00:20:13] S1: this code pull. That's right, 100%. A related topic that we've been talking about is that there are two archetypes, or there's almost like a continuum of how levered you are to the trend. And then do you have the old hallmarks of durability, enterprise stickiness? Some [00:20:37] S0: of
00:20:37 · Jack Altman, Ev Randle
[00:20:37] S0: of [00:20:37] S1: the things that we loved about the scions of the last era, like Datadog and CrowdStrike and even Databricks, even though they're not public. There seems to be some form of trade off between how levered you are to the AI, basically the cogen pull or just the AI trade in general, and some of the more traditional signs of durability and defensibility from an enterprise context, where it's like, oh, this is like three year long term contracts and all these things. What do you think about that trade off and if you're attracted to one or the other or anything that
00:21:19 · Jack Altman
[00:21:19] S0: you think about that? Well, might be wrong. But for me, I'm in a mindset right now where durability is really hard to call. Like, think in the last era, by, let's say, the late twenty teens, I think you had a good enough feel for cloud and enterprise at that point that you could not perfectly, but you could name it when you're like, that's durable or that's going to get competed. That's sticky. That's got a high switching cost. We got to a place where I think you could make those calls somewhat correctly because you had too many examples that looked like it, and you just knew how software worked. You also had situations where enterprises would look at software for years before they were buying and like, I know I'm going to buy Workday, but I'm not going to buy it yet. But when I do, I'm going to use it forever. You just had dynamics like that where right now, I don't know that durability is nearly as easy to identify. It's like even take like take application software. I don't know, six months ago, everybody was kind of like, it's dead. Yeah. At the moment, I think people are like, it's alive and it's good. And why should the labs do it? And there's all these edge cases to do, and they can actually be value add to the intelligence tokens. And there's all these reasons to put your data in there and blah, blah, blah. And you need a UI. And that's great. And six months from now, people might flip again and be like, never mind. Code got so good that that's all not true anymore and all these things. So calling the durability seems difficult to me. Yeah, I think. You know, I was thinking about like, what is it about the five to 18? I think if you are if you are trying to identify the next code, the next thing that's going to pull like crazy, I think that's probably the reason that people get really attracted. You know, like as an example, I think we all believe robotics will work. Yeah. We would all probably say it's not exactly working yet. We can't have a robot in here doing a bunch of things that a human could do. You can't really have one at home just yet. But I think we all believe we'll have one. You and I both love our Teslas. You, like, see the beginnings of it. And, you know, you go to these... You go to cool companies, like, if you visit, like, Pi or something like that, you're like, this... You know? You can see the future. Yeah.
00:23:35 · Jack Altman, Ev Randle
So it's gonna come. And so you can bet ahead on things like that. Bio is another one where it seems like the smartest people at the lab seem to be saying it's going to work. There seems to be early indications that target identification and other things are possible that didn't used to be. And so I think that, to me, is more the spirit of investing at the moment is either on the trend or you're calling the next one. And obviously, the returns are highest if you call the next one. [00:24:03] S1: 100%. Yeah, I feel like that is it's funny. As soon as you can put into chat for, obviously, the segment of what are all the derivative things, I went into chat. I'm like, well, we've seen these work. What other trends have worked? As soon as chat knows [00:24:21] S0: means it's the derivative trade everyone's talking about it. [00:24:23] S1: Everyone's talking about it, and the companies that you could invest in are probably already at a billion plus valuation or something like that. Yes. And you [00:24:30] S0: can still make that call because you can believe that the market will still somehow just not appreciate how far it will go. [00:24:35] S1: Yeah, 100%. 100%. [00:24:37] S0: And that's fine.
00:24:37 · Jack Altman, Ev Randle
[00:24:37] S0: And that's fine. [00:24:38] S1: It's super fine. I think on some of the... A final thing on difference or the comparison between even both categories that are growing and what is healthy growth versus riskier growth, I think there's two conflicting views. One is that, well, if you want to see a really healthy... A sign of health for the AI ecosystem would be money that is not in the system coming into the system. [00:25:08] S0: So this when it just circles around. [00:25:10] S1: Yeah. So... Well, I I think there's two arguments, but I think the argument here is, like, you know, okay. Circular revenue and just, like, you're... If the only people buying AI stuff are AI companies, that is like... You know, it's just... It's more and more leverage. Like, that's more and more leverage on the system because if it doesn't work out, then it all comes crashing down. Whereas, like, if large banks or large health care systems in, like, Ohio and New York and Florida are getting immense value in buying a ton of AI, that is really healthy because that's... That is like an independent, non AI oriented end market [00:25:41] S0: And it goes back to those are buyers of tokens. [00:25:43] S1: And those are buyers of tokens, [00:25:44] S0: which is what needs to happen here. Yes. You're spending a of money to make these tokens.
00:25:44 · Jack Altman, Ev Randle
[00:25:44] S0: which is what needs to happen here. Yes. You're spending a of money to make these tokens. [00:25:48] S1: Yes. They better be useful. They better be useful. And and, like, I think AI companies are much more willing to be risking their token spending or token buying relative to a big health care system with 8% profit margins. They're not going to blow up their P and L [00:26:02] S0: Well, again, if you are an AI application company buying tokens and then doing something to them and then giving them to somebody else, somebody still needs to make people's lives better. Like, at the end of the day, somebody needs to turn the token into a better life in a way that you couldn't have done without the token or at least not as well.