Google Developers Blog outlines a repeatable eval pipeline for AI agents

Google Developers Blog says a vibe check misses agent failures such as retry loops, extra tool calls, and wrong answers that still look plausible.

It recommends starting with critical user journeys, simulated users, and a frozen golden dataset, then layering unit tests, deterministic metrics, LLM-as-a-judge rubrics, and integration tests.

The post uses the open-source agent-eval toolkit and a LangGraph agent example.