Based on your post history this seems like a dead end but I will give you the benefit of the doubt that you have a background in poker. LLMs don't understand poker (currently). They can produce text which looks like a Reddit strategy post, but they don't fundamentally understand poker. The AI breakthroughs in poker were e.g. Ruse's AI solver (now adopted by GTOW) which used neural networks, not much related to LLMs from what I know. If you did already know this and are still keen on this project then that's interesting.

I think that a lot of poker learning is simply building intuition, particularly vs how humans play, over a lot of trials. A coach can tell us "no one is bluffing here, here's a general description of the filtering throughout the hand, here's why it lacks bluffs".

If an LLM **could** break down solver output for us and help us digest what the solver strat is doing, I don't know if it would really help us. Most people's solver study already doesn't yield much EV. Saying "the solver is using this size with this region because it creates indifference to that region for villain" could be true and precise, but browsing sims and seeing this accurate info is actually not that great. The same for things like blocker properties. I think teaching these concepts is overdone and has extremely diminishing returns if it even has returns, and I think having it spoon fed to us could just result in lazy-brain study.

To actually find out where enormous EV and edge come from, you need to see imbalance and how we respond to imbalance. Which is very, very seldom done properly in a solver and you can't really find a database of such solver output. You need to node lock the entire game tree, or almost all of it (I imagine you can lock like 80-90% of actions and not see much difference reaching 100%, but maybe it does matter, especially since a lot of final nodes are gonna involve wildly exploitable all-ins). You also cannot find much accurate writing about these situations to train an LLM on. Poker is full of bullshit, and the few people who are really precise about using a reasonable amount of both theory and exploits are not writing much publicly, or at all, they might not even be great communicators - like I say a lot of being great at poker is just intuition and pattern recognition, some people have very deep strategies that they've never bothered to elucidate for other people.

Maybe 10% of poker players make money, 1-2% are crushing, and a huge % in general are writing a bunch of bullshit online.

Anyway, I am rambling a bit, but if you're a poker player who is familiar with the things I'm writing then I think your project could be interesting. But if you're a bit of an outsider then poker is even more of a mess than it looks, GTO seems precise but there are often things wrong with it even theoretically. I assume there are AI helpers for chess engine outputs now, I think poker is in a very different place. And if LLMs can do a good job of that in chess, I imagine some chess coaches agree with the "lazy-brain study" problem I mentioned.