LLM plays chess by intelligently directing real-time engine search
MikePFrank · x · 2026-09-09
The author shares an LLM chess agent setup: the model is explicitly forbidden from downloading or calling external chess resources—all knowledge comes from training, supplemented by real-time engine search.
The key trick is that the model intelligently picks what to search for and how deeply: e.g., forcing a queen capture when the opponent's queen looks cornered, or searching for an escape when its own queen is trapped, allocating extra search time when it senses an opportunity or threat.
Related event: LLM Chess Agent Chooses Its Own Search Strategy(2 posts)→
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