Driving the Agent Quality Flywheel from Your Coding Agent- Google Developers Blog

This post introduces a "quality flywheel" for engineering AI agents, driven by a coding agent that automates the evaluation and refinement cycle. It details a five-stage process: Prepare Data, Run Inference, Grade, Analyze Failures, and Optimize & Iterate. Key components include adaptive AutoRaters for grading, Automatic Loss Analysis for clustering failures, and a decoupled optimizer/evaluator architecture. The post also highlights the development of custom metrics to isolate specific failure modes, such as mid-conversation changes in agent behavior, and provides concrete examples of how the system operates using the `_travel-concierge_` agent.