Oly Sourbut

You're going to look at some kind of summary and this kind of thing.

So yeah, moving along that agent access,

at least your first approximation, it's enabling more to get done between human kind of check-ins, but the exact trade-off there is that it's kind of reducing oversight potentially.

And I think there's a lot of design that can be done around enabling the really important pieces of information to be surfaced and also attempted to guarantee that like appropriate check-in happens at appropriate points as well, because kind of the more long running tasks, the more the agents kind of run into all kinds of small decisions maybe, but perhaps larger decisions as well.

I mean, at some stage, maybe you're imagining things like partially autonomous corporations where you've got various kinds of functions being fulfilled by AI systems.

They don't need to be agents as well.

I think people imagine, you know, drop in remote worker.

This is like a phrase that gets thrown around.

People imagine this kind of fully fledged self-contained agent, but it doesn't need to be.

It can be a kind of agentic workflow.

It can maintain context over time.

It can perhaps learn over time, but it doesn't need to have every single affordance under the sun.

And the oversight there can be entirely reasonable if it's well-designed.

And that's the big crux.

If it's well-designed, how do you know it's well-designed?

And there's all these kinds of questions.

So maybe have a few thoughts about that.

One is...

Yes, absolutely, we should get the guarantees that we need to get about the inclinations of the models we're putting into these systems to be thorough, to produce legible outputs, to not be biased in certain ways, to not have, you know,

blind spots and this kind of thing.