Google EnvHarness: Reshaping Static Environments for Better Agent Learning
jiqizhixin · x · 2026-08-28
Google introduces EnvHarness, a framework designed to enhance agent learning through environment-side scaffolding. Similar to how agent harnesses add memory and skills around a frozen LLM, EnvHarness wraps a static environment and reshapes its responses to agent interactions without modifying the core. A four-step loop reads agent trajectories, identifies weaknesses, proposes environment modifications, and validates if they yield better training signals. The goal is a more informative environment, not just a harder or easier one. Results show that environment-side scaffolding can provide richer training signals than agent-side tweaks alone.
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