Tsinghua and Zhipu's HarnessPro lets agents rewrite their own harness to cut task costs
AIResearchers from Tsinghua, Zhipu and partner institutions released HarnessPro, a method that lets an AI agent improve its own harness for performance and lower cost. On Terminal-Bench 2 with GPT-5.5 and Codex, the Heavy variant raised pass rate from 76.3 percent to 80.8 percent while cutting cost per task from $1.09 to $0.72 compared with the RHO method.
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Original title: Tsinghua and Zhipu's HarnessPro Lets Agents Rewrite Their Own Harness, Cutting Task Costs 26%