Turbo Harness: Instance-Adaptive Harness Optimization
Quick summary
arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations typically produce a single global harness that is applied uniformly across task instances. However, a harness that works well on average may not be optimal for every instance. We introduce Turbo Harness, a framework that can adapt a globally optimized harness to each instance by reusing information generated during the original optimization process. Specifically, Turbo Harness recycles artifacts pro
Key takeaways
- arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve.
- Existing harness optimizations typically produce a single global harness that is applied uniformly across task instances.
- However, a harness that works well on average may not be optimal for every instance.
Why it matters
“Turbo Harness: Instance-Adaptive Harness Optimization” illustrates how changes in the AI ecosystem can affect products, workflows and user expectations together. Its lasting significance depends on measurable adoption, cost and safety outcomes.
Member comments