Harness2: Recursive Self-Improving Agent Harnesses Without Verifiers

This episode examines "Harness 2," a paper on recursive agent harnessing. Its premise is that the wrapper around a frozen model can be improved automatically on a stream of unlabeled tasks, with no ground-truth verifier. The "harness" here is eight editable files: prompts, guardrails, memory, skills, tools, scripts, subagents, and middleware. The discussion places the work against prior approaches. These include SWE-agent's interface findings, Meta-Harness's freeze-after-search approach, per-instance scaling, ReasoningBank, Reflexion, and the Darwin Gödel Machine. It then explains the two coupled loops. Task-level refinement edits the execution harness for the current task. Harnessing-level recursion folds the lessons into a separate improvement harness, made of a library of adopted harnesses plus an EXPERIENCE.md file, while each new task still starts from a common base. The episode begins a walkthrough of the Propose, Probe, Compose refinement step, using a JobBench case that rose from 43.1 to 77.8. Listeners interested in self-improving agents will find it useful for seeing why self-correction without external feedback is hard and how this design tries to work around that. Sources: 1. Harness^2: Recursive Agent Harnessing for an Open World — Ruiyao Xu, Yanfei Chen, Zhongying CuiZhu, Bhavana Dalvi Mishra, Yifei Ming, Han Yu, Rujun Han, Chen-Yu Lee, Tomas Pfister, 2026 http://arxiv.org/abs/2610.14224 2. Reflexion: Language Agents with Verbal Reinforcement Learning — Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, Shunyu Yao, 2023 https://scholar.google.com/scholar?q=Reflexion%3A+Language+Agents+with+Verbal+Reinforcement+Learning 3. Automated Design of Agentic Systems (ADAS) — Shengran Hu, Cong Lu, Jeff Clune, 2024 https://scholar.google.com/scholar?q=Automated+Design+of+Agentic+Systems+%28ADAS%29 4. Darwin Gödel Machine: Open-Ended Evolution of Self-Improving Agents — Jenny Zhang, Shengran Hu, Cong Lu, Robert Lange, Jeff Clune, 2025 https://scholar.google.com/scholar?q=Darwin+G%C3%B6del+Machine%3A+Open-Ended+Evolution+of+Self-Improving+Agents 5. ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory — Siru Ouyang et al. (Google Cloud AI Research and collaborators), 2025 https://scholar.google.com/scholar?q=ReasoningBank%3A+Scaling+Agent+Self-Evolving+with+Reasoning+Memory 6. Self-Refine: Iterative Refinement with Self-Feedback — Aman Madaan, Niket Tandon, Peter Clark, Yiming Yang, et al., 2023 https://scholar.google.com/scholar?q=Self-Refine%3A+Iterative+Refinement+with+Self-Feedback 7. Large Language Models Cannot Self-Correct Reasoning Yet — Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, Denny Zhou, 2023 https://scholar.google.com/scholar?q=Large+Language+Models+Cannot+Self-Correct+Reasoning+Yet 8. Large Language Models as Optimizers (OPRO) — Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen, 2023 https://scholar.google.com/scholar?q=Large+Language+Models+as+Optimizers+%28OPRO%29 9. Meta-Harness (Lee et al.) — Lee et al. (as cited in the Harness2 paper; full author list not verified), 2026 https://scholar.google.com/scholar?q=Meta-Harness+%28Lee+et+al.%29 10. SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering — John Yang, Carlos E. Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, Ofir Press, 2024 https://scholar.google.com/scholar?q=SWE-agent%3A+Agent-Computer+Interfaces+Enable+Automated+Software+Engineering 11. Meta-Harness: End-to-end optimization of model harnesses — Y. Lee, R. S. Nair, Q. Zhang, K. Lee, O. Khattab, C. Finn, 2026 https://scholar.google.com/scholar?q=Meta-Harness%3A+End-to-end+optimization+of+model+harnesses 12. Rethinking the evaluation of harness evolution for agents — Y. Wang, H. Zhu, Z. Hu, et al., 2026 https://scholar.google.com/scholar?q=Rethinking+the+evaluation+of+harness+evolution+for+agents 13. Recursive harness self-improvement; and TTHE: Test-time harness evolution — H. Lee, J. Xu, J. Seely, D. Lee, M. Zaharia, Y. Tang (2026a); J. Nie et al. (2026b), 2026 https://scholar.google.com/scholar?q=Recursive+harness+self-improvement%3B+and+TTHE%3A+Test-time+harness+evolution 14. Hyperagents; Darwin Gödel Machine; Self-taught Optimizer (STOP) — J. Zhang et al. (Hyperagents 2026, DGM 2026); E. Zelikman et al. (STOP 2024), 2024-2026 https://scholar.google.com/scholar?q=Hyperagents%3B+Darwin+G%C3%B6del+Machine%3B+Self-taught+Optimizer+%28STOP%29 15. Harness continual learning (HCL) and Hierarchical self-improvement (HSI) — B. Kang et al. (2026); T. Zhou (2026), 2026 https://scholar.google.com/scholar?q=Harness+continual+learning+%28HCL%29+and+Hierarchical+self-improvement+%28HSI%29 16. GEPA: Reflective prompt evolution can outperform reinforcement learning — L. A. Agrawal et al., 2026 https://scholar.google.com/scholar?q=GEPA%3A+Reflective+prompt+evolution+can+outperform+reinforcement+learning 17. Recursive Self-Aggregation Unlocks Deep Thinking in LLMs — S. Venkatraman et al., 2025 https://scholar.google.com/scholar?q=Recursive+Self-Aggregation+Unlocks+Deep+Thinking+in+LLMs 18. Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena; LLM Evaluators Recognize and Favor Their Own Generations — L. Zheng et al. (2023); A. Panickssery et al. (2024), 2023-2024 https://scholar.google.com/scholar?q=Judging+LLM-as-a-Judge+with+MT-Bench+and+Chatbot+Arena%3B+LLM+Evaluators+Recognize+and+Favor+Their+Own+Generations 19. Scaling Laws for Reward Model Overoptimization — L. Gao, J. Schulman, J. Hilton, 2023 https://scholar.google.com/scholar?q=Scaling+Laws+for+Reward+Model+Overoptimization 20. Reflexion: Language agents with verbal reinforcement learning; Self-Refine — N. Shinn et al. (2023); A. Madaan et al. (2023), 2023 https://scholar.google.com/scholar?q=Reflexion%3A+Language+agents+with+verbal+reinforcement+learning%3B+Self-Refine 21. Automated Design of Agentic Systems (ADAS); AFlow; DSPy — S. Hu, C. Lu, J. Clune (2025); J. Zhang et al. (2025); O. Khattab et al. (2024), 2024-2025 https://scholar.google.com/scholar?q=Automated+Design+of+Agentic+Systems+%28ADAS%29%3B+AFlow%3B+DSPy Interactive Visualization: Harness2: Recursive Self-Improving Agent Harnesses Without Verifiers