00 · start here
Start here: what OverGrid asks an AI to see.
A short guide to the game, its scoring, and why one three-piece turn can create a serious search problem.
OverGrid / AI Field Notes
Two ways to read the board.
Choose a behind-the-scenes account of the game AI, or a player-facing strategy story drawn from the same concrete problems.
4 notes for Compute.
Behind the AI
For game makers: engineering, evaluation, tooling, and failed experiments.
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01 · search foundation
A small board can still have an enormous turn.
Why OverGrid’s first AI problem was not “which move is best?” but “which legal moves deserve a fair look?”
03 · early autoresearch
Our first hillclimb had no finish line.
The original autoresearch loop found useful hypotheses—and then taught us why capped snapshots cannot crown a champion.
11 · responsive compute
The best move may be outside the search budget
Petra’s missed height tile exposed the real bounded-search problem: evaluating a move is useless if the candidate generator never offers it.