Joel Hron

And if you look at, like...

What we're doing in tax, it really brings together this concept of tools and code, I think, in a really interesting way where you think about a tax workflow.

Somebody starts with a bunch of like W-2s and 1099s and things like that.

And I need to use AI and LLMs in particular in this case.

To analyze these documents, resolve context between them.

I've got this invoice.

I've got this tax form.

Do these numbers match with each other?

Am I missing information?

Then it involves aspects of being able to take those numbers and

look at the tax law in some way and say, okay, like, how do I treat these numbers?

Like, should I deduct this or should I not deduct this?

And then how, once I've done that, how do I then map that to a tax engine that like calculates actually the tax and puts it into a filing form?

And that's like an end-to-end problem that involves like a ton of different tools and research and data extraction sort of things all in one.

And we've got a beta out there on Ready to Review that does this, at least in some of the simpler use cases.

But I'm really excited about those forms of agents because they do touch on so many different capabilities of the model to be able to do math things, call tools, do research all in one system.

And so I think if I were to extend deep research, that would be sort of where it's going next is like this broader context of operating.

Yeah.

Yeah.

Yeah, this is kind of what I was getting at when I said, like, solve the whole problem.