· David Senra, Alexandr Wang
[00:00:00] S0: Now you have the prototype, you have the buy-in, everybody knows, Mark's on board, and now you're doing the seven months of the difficult work of refining this product. [00:00:00] S1: Yes. There was kind of this specter, which was like, oh, personal agents, they came and went. And we always felt that it was because the experience wasn't perfect, it wasn't polished yet, all that kind of stuff. But we knew that that was something that we had to think about as we were developing this product. We focused our model development roadmap, the top focus, or one of the top focuses, was towards building on personal agents. And we had these long spreadsheets of hundreds or even thousands of different... not thousands, but more than a hundred specific behaviors and capabilities that we knew the model needed to have to be able to build the ideal personal agent. It was very, very meticulous. And then over time, we built evals for all of those. We figured out how to train the model to be really, really good at every single one of those things. And we have these reviews where we look at that spreadsheet, and we figure out the things that we're bad at and make sure that we're improving on them. We did this very meticulous process to slowly just keep improving and sanding out all the edges of the model so that it could power the product. [00:00:00] S0: Is that really the culture of Meta, too? This constant sanding of the products?
· David Senra, Alexandr Wang
[00:00:00] S0: Is that really the culture of Meta, too? This constant sanding of the products? [00:00:00] S1: Yeah, a lot of the culture of Meta is like, once you know what you're measuring, there's very talented people, and you can optimize for those things. You can sand out all the details. You can make those things amazing. I think in the sort of pre-AI consumer product era, a lot of this was around, how do you optimize your conversion? How do you optimize the referral rates? How do you optimize every part of the onboarding flow? How do you make all that stuff just perfect? And then I think the AI era, I think a lot of that, especially for Muse, has been in the form of sanding out every detail of the model to be perfect for the product.
· David Senra
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· David Senra
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· Alexandr Wang
[00:00:00] S1: Did you see this profile that's written on Zuck in "Colossus" written by Jeremy Stern? I saw it. If I'm being honest, it was too long, didn't read, but- It's 15,000 words. I just had Jeremy on the podcast. He's my favorite. Which I saw. I saw the- Yeah. I saw the- Yeah. I think he's writing the best profiles on entrepreneurs and investors in the world right now. I think he's literally the best in the world at what he does. But in that, Zuck says, he was talking about the advantage that he has relative to, I think, Elon and Sam Altman. And he's just like, "Listen, my skill set is very unsexy, but I'm really good at building teams and then just improving a product slowly over a long period of time." And relative to Elon and Sam Altman and others, he's like, "I'm not going to lose control of my company, and I don't need to raise any more money. And so I can just do this for an excessively long period of time." That section of the profile is popping in my mind when you're talking about this seven-month stretch of trying to refine and build Muse. I think that's exactly right. I think that it took immense patience. Seven months maybe doesn't sound like that long, but AI is fierce. Seven months in AI time. Seven months in AI time, which may be a decade in non-AI time. And I think for all of us, but I really give Mark a lot of credit for this, it took a lot of patience and restraint and a lot of trust in the process. And you can go back and look at what Mark said in earnings calls for this entire period from February through September, and he will allude to the fact that we were building personal agents. And we weren't really trying to hide it. We were building- Personal agents, and we were talking about it, but I think there's a lot of doubt in the company for that entire period. Like, people, obviously one of the dominant Wall Street narratives is like, "Oh my gosh, Meta's just burning all this money. Like, are they even going to pull anything off in AI?"
· David Senra
[00:00:00] S0: It's more than that. It's like, "Zuck cannot win AI." It's said over and over again for a long period of time. And again, going back to Jeremy Stern's profile on him, he then, off the record, starts talking to his competitors, including one former researcher that is now at a competitor that used to work with Zuck and is now at another lab. And he goes, "I don't want to have to compete with him because Mark is like the fucking..." I think the line is, "Mark is the fucking terminator." And it was like, he just will not stop. And then he talks about one of his superpowers is that he's never happy with the state of the product, so he always wants constant improvement, but he's not an asshole. Like, he's not a dict- he's definitely a dictator, but he's not rude and will destroy the chemistry of a team. He actually talks about in the piece that team cohesion is excessively important to him.