Hexodic

Games where playing is the training signal.

A short lineage: games whose players made the system behind them smarter — and the strategy game built on that idea.

Get it on the App Store The play-to-train pillar

Are there games where playing trains an AI?

Yes — it’s a small but real lineage. The famous ancestor is Foldit, the University of Washington’s protein-folding puzzle game, where players’ spatial intuition produced solutions that eluded automated methods — most famously helping resolve the structure of a monkey-virus protease that had resisted researchers for years, a result published with the players credited.

Foldit’s insight was that play itself can be a scientific instrument: aggregate enough human moves at a hard problem and the system behind the game gets materially better.

That insight mostly stayed in citizen science. Hexodic brings it to the game itself: the thing your play improves is your own next opponent.

How Hexodic turns wins into training signal

Hexodic’s learning bot, CL3O, improves through classical search and statistics — explicitly not a neural network training on your data:

  1. Players challenge CL3O in the arena; a daily learning run happens only after arena games.
  2. A seeded self-play search proposes new evaluation weights.
  3. The best candidate must pass a sequential probability ratio test against the served version.
  4. Every recorded human win against CL3O is replayed; a candidate that fixes fewer of them than the served version is rejected.
  5. A candidate that passes is served to every client; otherwise it is discarded.

The full checks are on the bot gauntlet and CL3O. Arena games are tied to a signed-in account so wins can be verified, as documented on how your games help.

Why this is different from “AI-powered” games

Most games that advertise AI ship a static model: it was trained once, somewhere else, on something else. In Hexodic the loop is live and adversarial — the specific games real players win against the current version are what its successor must answer. If you can reliably beat the top bot, you aren’t generating engagement metrics; you’re the selection pressure. And because the mechanism is a tournament of programs with a statistical promotion gate, it’s fully inspectable — no black box between your win and the next bot.

The long-term vision — labeled vision, because it hasn’t shipped — is national bots: country-level bots trained by their own player bases, playing for their players. The game this loop lives in is a deterministic, five-minute abstract strategy game — depth first, clever loop second. Get Hexodic.

Part of the Hexodic AI and research hub, which links CL3O, what playing records, and how every published number was measured.