Alpin Yukseloglu

AI well.

For example, you can look at something like prediction markets, where there are markets where if you trade them to perfection, the most amount of money you can make is maybe $50 to $100.

And it's not worth it for Jane Street to put a quant on those markets because it's too expensive for them.

And it's bound by the cost of intelligence and the cost of attention.

But if you can trade those markets near perfectly for 10 cents of inference, then you'll do it.

And in aggregate, maybe that long tail is pretty valuable.

So right now, we're in a world where the long tail is sheltered by the fact that it's small.

And as AI gets better in all of these different domains, we should just be assuming that all of that's going to get collected by people who are able to use these tools.

Is that right?

Yeah, it's...

It's a benchmark and also an agent harness.

So we maybe had two releases in conjunction.

The first evaluates the ability of an agent to exploit smart contracts.

And then the second one is sort of an agent harness that is like, you know...

similar to an auditing agent.

So it can actually find the bugs.

And obviously the agent harness that we released is sort of not at the frontier of capabilities because we don't want it to be used for Blackhats.

But we have a UI that you can upload any smart contract into that will do sort of a baseline check for bugs.

Yeah, so the core idea is the model labs will release these LLMs, right?

So you'll have GPT 5.3, et cetera.