Nick Heiner

Like when you add all that stuff in, you know, that's where the models tend to fall apart.

Yeah, so I will admit that, you know, I work at a company that produces aerial environments.

So if you're asking me, you know, I'm going to have a certain perspective here.

But I think my perspective is also correct.

And now I will share it.

So, you know, I think it really comes down to...

what the factory, your previous guest, the factory CTO, I think, was saying.

Eno, yeah.

Eno, yeah, yeah.

Where he was saying that making the code base agent-ready has a huge impact.

And that absolutely matches what we've seen in our own research.

And so I don't think companies want to be building their own RL environments because there's a lot of work and infrastructure that goes into that that is not really part of the core competency.

what they should be doing is making their entire business agent ready.

And so that basically means that like,

you get it ready to plug into an Arnold environment so that you can train, you know, even if you're not training a model per se, but like you're evaluating an agent, whatever AI solution you're using, you're evaluating it in this environment.

So yeah, that could be things like making certain data sets available in an agent friendly way.

It could be thinking about what are existing workflows where we can separate out parts that are good for agents and parts that are good for humans.

I could also be just thinking, what is work?

that was never economically viable to do before.

But now that agents exist, it is valuable to do.