An outer loop around AI coding harnesses gains 52%

Harness-of-Harness wraps existing AI coding harnesses in an outer loop and boosts task success 52.25% on average across three model pairs. For anyone already running Codex, OpenCode, or a similar setup, the gain sits entirely in the outer loop, so swapping in the new loop doesn't mean swapping out the harness underneath.

The paper tests three pairings, Codex with GPT-5.5, OpenCode with DeepSeek-V4-Pro, and Pi with MiniMax-M3, against three benchmarks: GameCraft-Bench, FrontierSWE and ProgramBench. The outer loop scopes work into small, verifiable increments and keeps the coding agent's own tests separate from an independent evaluation pass. After three iterations, the best pairing improved 82.86% over its standalone harness. The setup kept improving past 70 iterations in a multi-day run, not a one-off benchmark score.

For builders running a coding harness now, the practical move is adding the outer loop rather than replacing the inner one. The paper doesn't say whether the same gain holds on work outside these three benchmarks.