Jesse Zhang

There are things where there's not enough tooling and functionality on top of something for it to be really valuable and needed.

Then maybe it is easier to just leverage the models.

But most of the time, that's not the case.

And especially when you get into agents, an agent is not just a model, right?

You have to like design it.

You have to be able to put in guardrails.

You have to be able to teach how to do new things.

And that's where the software layer on top of the model is coming.

And if that's valuable, then it's just much harder for you to just like...

be made obsolete by a model update the other side of it is like okay well now the labs are quite interested in building applications so they're building a bunch of cloud coding applications and cloud code and so on and so those will end up being competitors with cognition or cursor and

And maybe for that reason, it is wise for the coding agents to start training stuff as well.

I think in our space, I would say for us right now, at least the sheer amount of functionality of the build, because it is a very top-down product, is quite large.

That has nothing to do with AI.

It's just stuff like, okay, how do you have observability into what the conversations are?

How do you alert the team if something spikes?

Yeah.

How are you able to QA and have unit tests for the conversation so that before you push it out to end users, you feel it's like, there's just all this like functionality that's there that doesn't really have anything to do with AI really.

And so it's just like a lot of stuff that needs to be built.

Yeah, we want people that are intellectually just at the leadership level, really curious and excited about technology.

You actually see a huge spectrum of that in the enterprise.