Infini-AI-Lab releases Hermit adapter framework
MarkTechPost: Infini-AI-Lab Releases Hermit, an Open-Source Harness Adapter Framework for AI Agents
Infini-AI-Lab has released Hermit, an open-source harness adapter framework for AI agents. Hermit is a framework from Infini-AI-Lab that trains an external ‘harness adapter’ while the agent’s model and harness stay frozen. The first release, v0.1.0, shipped on October 25, 2026. CMU postdoc Haizhong Zheng announced it on X on October 27. For developers, the pitch is simple: adapt Codex or Claude Code agents to new tasks without fine-tuning or forking the harness. TL;DR F
Get smart on it
Hermit is an open-source framework that trains an external adapter to improve how AI agents perform tasks, while keeping the agent's underlying model and harness unchanged. This approach matters because many existing harnesses are closed-source or carefully tuned, making it risky to modify them directly, and a trained adapter can be moved between compatible models and harnesses. The framework uses a training loop where an agent runs tasks, gets scored, and an evolution method proposes improvements to the adapter stored in a version-controlled system. In benchmark tests using one model, the best-performing adapter method achieved 0.795 accuracy on a database task compared to 0.580 for baseline performance, though the results are self-reported and mostly single runs.
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