02:37:10 路 John Coogan, Markie Wagner, S10
[02:37:10] S1: Yeah. [02:37:11] S7: And I can write the best code now, but even if you have the most incredible piece of software, you still have to change how the business organizes around it. And so, the people who understand like business and can think about, hey, like, what is the best possible fraud process going to look like? And, you know, what how should we reorganize the business around this new kind of thing? Mhmm. And they understand AI are the ones that are just, like, totally crushing it. [02:37:34] S1: Yeah. That feels like an entirely new skill set, like, much more people driven, but also, like [02:37:38] S7: Yeah. [02:37:38] S1: Forward thinking in technology. I don't know. Mhmm. [02:37:41] S10: It's a [02:37:42] S1: it's a it's an interesting new
02:37:42 路 John Coogan, Jordi Hays
[02:37:42] S1: it's a it's an interesting new [02:37:43] S0: How has enterprise sentiment around just AI changed during the course of building the company? Right? Because like every, you know, it is I would say it's a roller coaster in some ways. It's like going up Yeah. Up into the right. Right? There's generally more excitement about the potential but at the same time there's these of like period troughs of disillusionment. And you guys are coming out of stealth at a time when again, I think companies are more excited than ever but at the same understand the overall shortcomings and and we had Karp on the show last week and you know, he was just saying like a lot of these deploy codes coming in, they're just trying to like they're they're they're trying to deploy their their goal is to deploy AI, but they don't fully understand all of this like business process under under the hood. And he makes some good points.
02:38:41 路 Markie Wagner, John Coogan, Trent Simonian
[02:38:41] S7: Yeah. I think sentiment has evolved quite a bit. You know, I think it was extremely exciting earlier in the year. And then, you know, around the board meeting times, more and more CEOs would come to me and say, hey, like, you know, how do I get ROI here? And and, you know, this is what your other customers are seeing in these domains. And so, I think now people have realized, like, you cannot just throw an agent at a problem and expect to see the result that you want. Right? For an agent to to do a useful bit of work, it needs to learn how to do that work and run it, like, quite accurately. And that knowledge transfer between how's the work done today and getting it written down enough to where AI can run it, it's just hard. And it requires, you know, we sort of jokingly call it the great migration internally. Like, you have to go and migrate these, like, tremendous amounts of rules into something that AI can touch and improve and involve. And if AI can't touch it, it's not going to be able to help it. Mhmm. And so, you know, I think deployment is really important because in yeah, until that transition happens, it's going to be hard to just throw tokens to to see better outcomes. [02:39:50] S1: Give us some backstory on what you were doing before, how you wound up here. [02:39:56] S7: Yeah. So I got my start. I got extremely into AI in middle school after reading too much sci fi, you know. A lot of Dune. A lot of mainly Dune. [02:40:07] S1: Is that the message in Dune? I thought Dune was the you [02:40:13] S12: know? [02:40:13] S1: I guess, yeah.
02:40:13 路 John Coogan, Markie Wagner, Jordi Hays, Vinod Khosla, S5
[02:40:13] S1: I guess, yeah. [02:40:15] S7: Yeah. You wanna avoid the Dune outcome. [02:40:16] S1: Well, I [02:40:16] S7: just felt like it was gonna be really important during my life, Yeah. You know, and you know, you read and you watch sci fi, you know, the biggest difference between the future and today, it's like mostly machines thinking. Like that is sort of the main a d sort of b c moment [02:40:31] S1: In hard sci In soft sci fi, it's like time travel and faster than light speed and like aliens. But I moon [02:40:41] S0: is made of cheese. [02:40:42] S1: That's the type of sci fi I'm trying to read. [02:40:45] S9: That's the [02:40:45] S1: white pill. So then walk me through the consulting work that you did and how this like evolved out of that. Was there like a clear moment where you're like I'm stopping that and starting a company or is this an evolution or a change of structure? [02:41:01] S7: Yeah. So I was initially got my start in research. So I was [02:41:04] S5: at I
02:41:04 路 S5, Markie Wagner, John Coogan
[02:41:04] S5: at I [02:41:04] S7: was at Stanford working in AI at like Waymo and Google. Yeah. And then, you know, one day I sort of realized that, you know, all the things I built like, you know, didn't didn't matter too much. And that was Friday and I ended up dropping out on Monday. And the idea was like, hey, you know, we've had software for decades. What are people still doing and and why? And I felt like I didn't really understand anything about how the world works. So Mhmm. To your point, started consulting and Yeah. The idea was like, let's just go into some of the oldest companies around and understand, like, what his software is still not touched and and what And happened when you do that, and you start doing some of the work yourself, and like going into, you know, I went to North Carolina, and you're people who've done this stuff for like decades, you realize that a huge amount of the work is really just operating procedures documents [02:41:52] S1: Mhmm.
02:41:52 路 John Coogan, Markie Wagner, Jordi Hays
[02:41:52] S1: Mhmm. [02:41:53] S7: And people are just following them. Mhmm. And that this class of work everywhere, and you know, whether it's underwriting and claims and insurance, or onboarding customers and fraud and banks, it's just still sort of done by by people and software hasn't been able to go there. The reason why is because the second you write all this code to do that process, something will change. Right? A button will move, a column will change, or maybe even the the process changes. You want yearly instead of monthly transactions. And when you, you know, automate and see that happen enough, you you realize like, hey, there's a missing kind of material here that can flex but still have guarantees. And I really just waited for the models to get better. I knew some of the researchers and said, the models of today are not it. Please let me know when they get good enough to get stuff. And I truly just waited. So [02:42:39] S1: That's great. Well, congratulations on the round. How much did you raise? I wanna hit the gong. [02:42:44] S7: Oh, yeah. So you raised $50,000,000. Congratulations. [02:42:50] S0: And thanks so much. Who besides FF is in? [02:42:54] S7: Yeah. Kleiner Perkins Kleiner Perkins. First Harmonic, Genius Ventures Cool. All all participated in the round. [02:43:01] S0: Round of applause for Genius. Love Greg and Ben and Adam. [02:43:05] S7: We love Genius. [02:43:06] S1: It's great news. Well, have a great rest of your day. So great rest