Harness Evolution as Learning: Approximation, Generalization, and Optimization Limits of Self-Improving Personal Agents

arXiv:2609.36892 · cs.AI, cs.CL · Submitted 2026-09-29 · Read on arXiv

cs.AI, cs.CL

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/ZyGan1999/self-evolving-harness-as-learning

Terminology

• Trace — 25× in this paper · explained in 2 episodes
• Generalization — 19× in this paper · explained in 13 episodes
• Adaptation — 14× in this paper · explained in 1 episode
• Foundation Model — 13× in this paper · explained in 3 episodes
• Personalization — 13× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Agent Harness — 4× in this paper · explained in 2 episodes
• Verification — 4× in this paper · explained in 2 episodes
• Calibration — 3× in this paper · explained in 7 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Frozen model — 2× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Verifier — 2× in this paper · explained in 2 episodes
• Wasserstein Distance — 2× in this paper · explained in 4 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Agent Memory — 1× in this paper · explained in 1 episode
• Agentic Coding — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Approximation Bound — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Error Decomposition — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Information-Theoretic Framework — 1× in this paper · explained in 2 episodes
• Online Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Paper Review — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes

Sources

• Beyond the Black Box: A Survey on the Theory and Mechanism of Large Language Models
• Statistical Priors for Implicit Preferences: Decoupling Skill Selection as a Local Harness in Personal Agents
• AutoHarness: improving LLM agents by automatically synthesizing a code harness
• TTHE: Test-Time Harness Evolution
• M$^\star$: Every Task Deserves Its Own Memory Harness
• OpenClaw-RL: Train Any Agent Simply by Talking
• AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
• MemEvolve: Meta-Evolution of Agent Memory Systems
• TEPA: Revoking Stale Memories for Conflict-Robust Language Agents
• Getting Better at Working With You: Compiling User Corrections into Runtime Enforcement for Coding Agents

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