Kevin Weil

Maybe it'll write some code for a little while as it thinks, and then go do some more.

And so it's this sort of iterative... I mean, it's what you would do if someone made you write a very complex research report.

You wouldn't

You go do some research.

Yeah.

And so to your question, that was something that some folks were like, okay, this is coming together.

but it's not clear exactly when it will come together.

And so there was a small team of researchers that just believed in this and were working to make this real.

And for a while, it wasn't good enough, it wasn't good enough.

And then there was some advances and all of a sudden you're like, okay, this is getting good enough.

And somewhere in that timeframe, we put also a product and engineering team working on it with them.

And then you have the thing that I think really is the magical part of OpenAI.

When you get a research team and a product and engineering team just in the same room, all bringing their unique skills to bear, and you understand the problem you're trying to solve.

And so you're bringing back use cases.

creating evals and benchmarks for how you measure whether you're successful against those use cases.

The research teams are taking that and using that to improve the model itself.

And you get this tight loop of the model improving towards a particular product.

And it's, you know, I think our best products are the ones that we build that way and deep research is a good example.

I think it's a completely different way of building products.

It's certainly different than anything I've ever, I've ever done in my career.