CTO ANALYSIS
Evaluation becomes useful when a result changes a release decision. Before optimizing a score, define which user outcomes must hold and what evidence would justify deploying a changed agent.
Recent context: Google Developers published the linked announcement on 2026-10-28. The discussion below is CTO Tech Times analysis, rather than a claim of hands-on testing.
Separate the task from the judge
Use representative scenarios with observable success conditions, including tool failures and ambiguous requests. Keep evaluation criteria stable while comparing candidate changes. Review a sample with people who understand the work so an apparently improved score cannot hide a worse user outcome.
Track important failures individually
Averages can conceal a small number of unacceptable actions. Maintain separate checks for permission boundaries, incorrect external actions, and inability to recover. Record task-level traces and the versions of prompts, tools, and models involved. This makes a regression actionable instead of leaving the team with an unexplained number.
Give the loop an owner
Decide who reviews failures, who can accept an exception, and which regressions block a release. Run a compact suite during development and a broader suite at a sensible cadence. The budget should include investigation and maintenance of the cases. An evaluation pipeline without that ownership is another dashboard waiting to be ignored.
Primary source: Google Developers: original announcement (2026-10-28). Sources checked November 3, 2026.