Harness Engineering
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Harness Engineering for Physical AI: Robot Middleware Is the Harness Layer
arXiv:2606.09416v1 Announce Type: new Abstract: Robot middleware faces a new role in the era of Physical AI. Learned policies, planners, and vision-language-action (VLA) models now enter deployed robots as causal participants on the control path, but the layer that integrates them with timing, scheduling, and network has not been named. Recent language-agent work names this layer the harness, the external system that mediates tools, manages state, bounds resources, and records execution.
Harness engineering: Leveraging Codex in an agent-first world
Article URL: https://openai.com/index/harness-engineering/ Comments URL: https://news.ycombinator.com/item?id=48416264 Points: 204 # Comments: 129
VeRO: A Harness for Agents to Optimize Agents
arXiv:2602.22480v4 Announce Type: replace Abstract: An important emerging application of coding agents is agent harness optimization: the iterative improvement of a target agent by editing and evaluating its code. Despite its relevance, the community lacks a systematic understanding of coding agent performance on this task. Harness optimization differs from conventional software engineering: agent harnesses interleave deterministic code with stochastic LLM completions, requiring structured...
Self-Harness: Harnesses That Improve Themselves
arXiv:2606.09498v1 Announce Type: new Abstract: The performance of LLM-based agents is jointly shaped by their base models and the harnesses that mediate their interaction with the environment. Because different models exhibit distinct behaviors, effective harness design is inherently model-specific. Yet agent harnesses are still largely engineered by human experts, a paradigm that scales poorly as modern LLMs become increasingly diverse and rapidly evolving.
Show HN: Keybench – Scriptable, extensible performance tool for key value stores
guycipher/keybench Folders and files | Name | Name | Last commit date | || |---|---|---|---|---| Repository files navigation keybench ======== A scriptable, extensible performance tool for sorted key value stores.
Giant fire tornadoes could clean up oil spills faster with less pollution
Giant fire tornadoes could clean up oil spills faster with less pollution What if one of the best ways to fight an oil spill is with a controlled fire tornado? - Date: - June 5, 2026 - Source: - Texas A&M University - Summary: - Researchers have shown that controlled fire whirls can clean up oil spills faster and more cleanly than traditional burning methods.
HARBOR: A Harness Framework for Agentic Robot Reinforcement Learning
arXiv:2606.08610v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a powerful paradigm for robot learning, particularly in sim-to-real settings, but its broader adoption remains limited by the engineering pipeline surrounding the algorithms. Building tasks, shaping rewards, and tuning hyperparameters require substantial expert effort, making RL workflows costly and difficult to scale. We introduce HARBOR, an agentic framework that frames robot RL automation as a...
Autonomous heterogeneous catalyst discovery with a self-evolving multi-agent digital twin
arXiv:2606.05050v1 Announce Type: cross Abstract: Theoretical heterogeneous catalysis promises rapid catalyst discovery, yet computational and machine-learning predictions often deviate from experiment and stay confined to narrow material families, for want of a faithful, condition-aware catalytic simulator. We present CatDT (Catalysis Digital Twin), a self-evolving multi-agent system that builds an autonomous digital twin of a working catalyst, unifying gas-solid and liquid-solid modeling....
What Makes Interaction Trajectories Effective for Training Terminal Agents?
arXiv:2606.03461v1 Announce Type: new Abstract: Stronger code agents are commonly assumed to be superior teachers for post-training, yet this assumption remains poorly disentangled from task difficulty, harness design, and student capacity. We investigate this pedagogical link using Terminal-Lego, a scalable pipeline that transforms multi-domain real-world issues into environment-verified agentic tasks. Surprisingly, standalone performance does not dictate teaching efficacy: while Claude...
Autonomous heterogeneous catalyst discovery with a self-evolving multi-agent digital twin
arXiv:2606.05050v1 Announce Type: cross Abstract: Theoretical heterogeneous catalysis promises rapid catalyst discovery, yet computational and machine-learning predictions often deviate from experiment and stay confined to narrow material families, for want of a faithful, condition-aware catalytic simulator. We present CatDT (Catalysis Digital Twin), a self-evolving multi-agent system that builds an autonomous digital twin of a working catalyst, unifying gas-solid and liquid-solid modeling....