02:15:17 · Jordi Hays, John Coogan
[02:15:17] S0: Definitely not. Okay. Definitely not. [02:15:19] S1: Potentially For
02:15:20 · Jordi Hays
[02:15:20] S0: another time. For another time. For another time. Are you, yeah, how are you it's interesting. The like, I I I still have some wariness around this like Rebel Alliance style plays because of the first generation of companies that were leveraging GPT models. They grew like crazy. And then it just was a matter of like building an interface and an interface is is straightforward. How are you like, you clearly are overcoming that fear and are willing are investing a lot against it. Part of it is like, I just feel like this dynamic now where hiring an agent is like quite different than hire, you know, just sign you know, using software and like you just assume that agents are gonna get better. And one of the challenges is it's like an agent that is generally intelligent. Just like a human, you can kind of plug into an organization and it can start just doing things. You don't really care that much how it how it does things. And so I just feel like the the process of like hiring agents for companies is gonna be like quite a bit different than like the last generation of software where you had to build out this massive sales force and you know, you're going to conferences and it's like, it's it's just a very different motion and I think that like, the growth of of Claude codes specifically is like proof that like software has changed to some degree and you can get adoption of something at a speed that is entirely unprecedented. So I'm curious how you're thinking about how just like the procurement and sales is going to change because again, we have companies on every single day that have grown revenue incredibly rapidly. They clearly are solving customer problems. You know, we had a healthcare agent company on today, started in 2023. It's a billion dollar company now. But yeah, the question is like, are are you still betting against when you invest in these companies, are you just betting against general purpose agent progress?
02:17:41 · Nick Grossman, Eliot Pence
[02:17:41] S7: Yeah. That's a really good question. And I think one important idea here is we're not just talking about will there be other agents that compete with Claude or ChadJPT. Like, will people build sort of, like, personified agents, and how will those get to market? I think that's one version of what agents look like. Another version of what agents look like is, like, cloud infrastructure, where every, you know, company that's building any system is gonna have agents and the orchestration of hundreds or thousands of agents built into their underlying, you know, platform, whether that's an app or whether that's an enterprise or or anything else. And so if you I think part of the Rebel Alliance thesis for us is agents are moving from sort of people you like, personified people you hire to cloud infrastructure. [02:18:30] S11: Yeah.
02:18:30 · Nick Grossman
[02:18:30] S7: And and it and when we look at how agents are getting deployed and orchestrated today, it's not just I'm hiring an agent and it's showing up in my Slack. It's like I'm programmatically spawning, you know, 50 agents, you know, to go sort of be part of whatever system I'm building. So if you think of agents as infrastructure as opposed to agents as employees, I think that's where a lot of these forces come into play where every every company, every enterprise who's building in an agentic style is going to need model routing, model choice, orchestration, know, memory, you know, some sort of harness, and there's there's different options at each of these as you're building up agentic systems. So so that's like really a big driver of this is the move from agents as people to agentic systems that have all of these layers in place and have more of like corporate's the wrong word, but like a more of a production vibe to them where they're gonna get built by professionals who wanna have control and who are gonna wanna lay them out in increasingly sophisticated ways. And so so I feel deeply, like like, very, very strong that that's happening. I see it everywhere. And I think a big like, a lot of the stuff that we're looking at right now in the agentic stack is, like, kind of low level, like, networking and identity and payments and all these, like, pieces you need in order to compose and orchestrate agents. We're moving from, like, agent as employee to agent as infrastructure, and and I think that also is, like, a big driver of how why we believe so much in the Rebel Alliance thesis.
02:20:01 · John Coogan, Nick Grossman, Jordi Hays
[02:20:01] S1: Last question. Can you take me through the financials, what they might look like at a Rebel Alliance company versus a non Rebel Alliance company? When I think about a lab, they might spend $1,000,000,000 on a training run, amortize it over months, and there might be all these GPU commits, they're spending money like an industrial company sometimes. If you're building a rebel alliance company, does it look different? Is it all talent? Are you subsidizing tokens at some point? Is it cost of customer acquisition? What are you pattern matching to in terms of like the shape of the business? Are we doing twelve- to eighteen month runway here? Like how are you thinking about deploying capital and watching that capital flow through the business at the early mid stage of a company? [02:20:49] S7: Yeah. It's good that you brought up, like, capital intensity. Right? So I think because I think an idea here is there's this category of hyper capital intensive AI companies Yeah. Which is the big labs. [02:20:59] S0: Yeah.
02:20:59 · Jordi Hays, Nick Grossman
[02:20:59] S0: Yeah. [02:21:00] S7: And then there's kind of everything else maybe that's like less capital intensive. Yeah. You know, we have a portfolio company called Pluralis Research that does model training, but in a decentralized network using, you know, compute that's scattered around the Internet. So you can still do training in a capital light way. I think that's possible. I don't wanna make it seem like the all the models must be capital intensive in the form of a single company, but I think generally speaking, you're looking for things that are more capital light. A lot of the things in the middle, like harnesses and memory and, you know, identity and payments, I think a lot of that looks like kind of regular tech companies. And then anything that sits at the sort of user level that's passing through token spend, you know, there's a category of margin profile there that's that's new in the AI era. Right? You're either taking a loss on on token spend pass through to the big labs, or you're, like, eking out margin by swapping out models. And so I do think there's, like, actually it's almost like this barbell of capital intensity where at the at the model layer, there's a lot of capital required. And at application the layer, there can be if you're subsidizing a lot of token spend, certainly on a free tier or or something like that. But there's a lot in the middle that I think has more of a traditional capital