Google details hill-climbing agent quality loop with Agents CLI eval, from baseline to alerting
rseroter · x · 2026-10-31
- A Google Developers Blog walkthrough shows how to iteratively improve agents with Agents CLI v1.8.0's eval commands: write test cases, run, grade, change the agent, rerun — keep changes that raise the score, revert those that don't.
- The eval namespace includes eval generate (run agent on a dataset), eval grade (score traces), eval compare (diff two runs), eval analyze (cluster failures into themes), and eval optimize (automated hill-climbing pass on the prompt).
- The demo covers baseline setup, regression tracking, model-backend swap experiments, scheduled evals, and automated alerting, with a chart showing eval score climbing from a 2.7 regression low to 4.9 over eight iterations.
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