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Harness-of-Harness Extends Coding Agent Work Sessions Through Planning, Development, and Independent Testing Loops, but Its Core Implementation Is Not Yet Public
A team at the Shanghai AI Laboratory has introduced Harness-of-Harness, which adds a recurring control loop for planning, implementation, and verification around existing coding agents. Across three-round experiments, it delivered an average relative gain of 52.25%, but each condition used only a single generation, and the executable HoH-lite is still marked as coming soon.