Alexander Embiricos: preference

Transcript context

…Before we get to Codex, is there a way that they've structured the org or, I don't know, the way that OpenAI operates that allows the team to move this quickly? Because everyone wants to move super fast. I imagine there's a structural approach to allowing this to happen. I mean, so one thing is just the technology that we're building with has just transformed so many things from both how we build, but also what kinds of things we can enable for users. And we spend most of our time talking about the sort of improvements within the foundation models, but I believe that even if we had no more progress today with models, which is absolutely not the case, but even if we had no more progress, we are way behind on product. There's so much more product to build. So I think just the moment is ripe, if that makes sense. But I think there's a lot of counterintuitive things that surprised me when I arrived as far as how things are structured. One example that comes to mind is when I was working on my startup and before that, when I was at Dropbox, it was very important, especially as a PM to always rally the ship and it was like make sure you're pointed in the right direction and then you can accelerate in that direction. But here, I think because we don't exactly know what capabilities will even come up soon and we don't know what's going to work technically, and then we also don't know what's going to land even if it works technically, it's much more important for us to be very humble and learn a lot more empirically and just try things quickly. And the org is set up in that way to be incredibly bottoms up. This is, again, one of those things that, as you were saying, everyone wants to move fast. I think everyone likes to say that they're bottoms up, or at least a lot of people do, but OpenAI is truly, truly bottoms up. And that's been a learning experience for me that now it'll be interesting if I ever work at... I don't think it'll even make sense to work at a non-AI company in the future. I don't even know what that means. But if I were to imagine it or go back in time, I think I would run things totally new. What I'm hearing is this ready, fire, aim is the approach more than ready, aim, fire. And there's something, and as you process that, because that may not come across well, but I actually have heard this a lot at AI companies is because you don't know, and Nick Turley shared I think the same sentiment, because you don't know how people will use it it doesn't make sense to spend a lot of time making it perfect. It's better to just get it out there in a primordial way, see how people use it, and then go big on that use case.…

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