I Built a Chess Engine with 5 AI Agents — Here's What Surprised Me

I gave five AI coding agents a task: build a chess engine from scratch. One planned the architecture. Three built components in parallel. One supervised everything. No external chess libraries. No internet lookups. Just agents, a test suite, and a goal: beat Stockfish at 1200 ELO at least 50% of the time. The engine works. But what surprised me wasn't the output — it was what I learned about supervised AI agent execution along the way. The Setup The team looked like this: roles: - name: architect role_type: architect agent: claude instances: 1 talks_to: [manager] - name: manager role_type: manager agent: claude instances: 1 talks_to: [architect, engineer] - name: engineer role_type: engineer agent: claude instances: 3 use_worktrees: true talks_to: [manager] Five agents. One architect running Opus for planning. Three engineers running Sonnet for implementation. One manager routing work between them. Each engineer got its own git worktree — its own branch, its own directory, completely i