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HarnessDev: Can LLMs Create and Evolve Their Own Agent Harness?

236 upvotes · 1 SEP 2026 · Yuhao Wu, Jingyuan Zhang, Jiajun Shi et al.

This paper creates a benchmark (HarnessDev) to test whether large language models (LLMs) can design and improve their own execution infrastructure, called the agent harness, which affects their performance. Practitioners might care because it explores how models can adapt to changing environments and potentially improve efficiency.

continual learningagent developmentLLMsmodel-external executionbenchmarking