Google Paper Introduces Harness^2 for Self-Improving Agent Harnesses
The non-obvious finding is that recursive self-improvement can work without a verifier by letting candidate harness edits compete against each other, which sidesteps a common bottleneck in agent reliability. Builders of agent pipelines can test whether carrying evolved harnesses across tasks beats memory-based baselines like ReasoningBank in their own stacks. Readers can follow the linked arXiv paper and DAIR.AI's chat-with-paper tool to dig into the setup.
