Kevin Weil

Yeah, I think part of this is about making sure that, like we talked about earlier, that the user is in control here.

So you should be able to at some point be like, hey, you know what?

You've checked enough.

Like, you're good.

And the other interesting thing in all of this is the technology is evolving so quickly, like much more quickly than I think we're used to with technology.

We're used to things taking like decades to deploy and to really achieve scale.

One of the phenomenons you see with AI technology is there'll be some benchmark, some eval that AI just can't crack.

And people are like, oh, AI just can't do that.

And then one day, somebody ships a model that gets like 5% on that eval.

Still mostly can't do the job, but just like begins to get it.

And then what you inevitably find is like two months later, there's a model that's at 30 on that eval.

And then four months later, there's a model that's at 60.

And then, you know, within six months, it's completely saturated and like models are great at that new skill and will forever be.

And so you go very quickly from like proof of existence to like, oh yeah, of course AI models can do that.

That like rate of development is still, I think, something that we're not totally used to.

Yeah, it's a really good question.

And actually, coding is this vertical that kind of hits all of these things.

For one, it's really important to us because if we can speed up coding, if we can make every engineer more effective, we also make ourselves more effective.

And so we can build even faster and we can bring AGI to the world faster.

So it's interesting to us from that perspective.