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Research questionHow can agents adapt as their tool, skill, and specialist-agent harness evolves without losing existing capabilities?Adding tools, reusable skills, or specialist agents can change what an agent observes and can do, disrupting tasks it previously solved. The agent must accommodate new capabilities while preserving useful prior behavior.
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Latest papersRecent research connected to this question, newest first.EVOHARNESSBENCH: Can Your Agents Keep Pace with an Evolving Harness?The evidence concerns controlled harness evolution across tools, skills, and agents, using 17 deterministic multi-stage streams and verifier-based tasks. It separately examines retention during harness expansion and self-evolving adaptation, finding inconsistent gains and a tension between the two.research paper · Sep 3, 2026
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How can agent harnesses adapt across tasks and models without manual redesign?How can LLM agents jointly adapt reasoning policies and hierarchical skill libraries during reinforcement learning?How can LLM agents reuse procedural skills across diverse long-horizon tasks without generic or instance-bound memory?How can LLM agents stay safe during multi-step execution when both policy and runtime harness shape behavior?
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