Joel Hron

Like there are other parts of our application, for instance, where we do like, you know, more workflow centric stuff like drafting policies or drafting purchase and sale agreements and things like this.

Where maybe you don't want so much agency.

Like, you know, my company has a way that they do this.

They have like standard templates or standard forms.

And I don't want to just go draft some document from scratch every time.

And so like being able to turn this agency dial, I think is actually not like, it's not like it's not a cool use case.

I think it's a necessity of like different types of work that these systems need to do.

Yeah, absolutely.

I think I think beyond deep research, which is a really cool use case, like I'm really excited by some of the stuff we're doing in tax as well.

It's like quite different.

But I think it also speaks to some of the things like the models are good at.

So a year ago, everybody was talking about LLMs and like they were like, oh, it's not good at math.

Like it'll never do math things and stuff like this.

And now all of a sudden, like it knows how to use calculators and it knows how to like write its own code and like this kind of stuff.

Yeah, silver medals, gold medals, whatever it is.

So, like, guess what?

I don't need to train the model how to, like, do 2 plus 7.

Like, I just needed to know how to write a Python script that does, you know, x equals 2 and y equals 7.

Like, add them together.

So, I think that paradigm change is, like, really profound.