Embrace uncertainty, avoid false precision

There's tons of stuff you can't know ahead of time. So if you're getting a false precision at the beginner, that's a comfort blanket. That's just helping you feel like there isn't uncertainty. There's uncertainty everywhere all the time.

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.

Everywhere I've ever worked before this, you kind of know what technology you're building on, but that's not true at all with AI. Every two months, computers can do something they've never been able to do before and you need to completely think differently about what you're doing.

The further out you plan, the more you're making it up. We know this.

"That change" refers to rapid shifts in AI capabilities, and "capabilities drop" means when AI companies release new features like Anthropic's computer use capability.

You want to be resilient to that change. When capabilities drop, you want to be able to jump on it really quickly. So being agile, not being stuck with roadmaps, being able to just say, oh, we're just going to switch priorities right away, is going to be super important.