Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams
Summary
Adaptive Auto-Harness is a framework for sustained self-improvement of agentic systems deployed on open-ended task streams, outperforming baselines via a stateful multi-agent evolver, harness tree, and human-steering hooks.
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Paper page - Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams
Source: https://huggingface.co/papers/2606.01770
Abstract
Adaptive Auto-Harness framework addresses dynamic task streams by decomposing performance gaps into evolution and adaptation losses, utilizing a stateful multi-agent evolver and harness tree with solve-time routing for sustained performance improvement.
Auto-harness systemssuch as A-Evolve, GEPA, and Meta-Harness improveLLM agentsby optimizing prompts, skills, tools, memories, and supporting infrastructure from execution feedback, but they are typically evaluated on fixed offline benchmarks. Real deployments instead present open-ended task streams: histories grow without a fixed endpoint, heterogeneous tasks require different harnesses, and problem distributions shift over time. These challenges make a single repeatedly and densely updated harness brittle, causing performance degradation as accuracy peaks early and then declines. This motivates sustained harness construction with task-wise adaptation. We introduce Adaptive Auto-Harness, a framework and system for such streams. The framework decomposes the gap to an oracle harness intoevolution lossandadaptation loss. The system addresses these losses with astateful multi-agent evolver, aharness treewithsolve-time routing, andhuman-steering hooksfor cases where history lacks the needed signal. Across prediction-market, security-competition, and event-forecasting streams, Adaptive Auto-Harness outperforms five existing auto-harness baselines and ablations attribute gains to better construction, routing, or targeted human steering. Code is available in https://github.com/A-EVO-Lab/AdaptiveHarness .
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