Google says agent behavior comes from prompts, evals, iteration, and feedback loops
AI Engineer · youtube · 2026-07-25
Google engineers describe how prompts, evals, iteration, and feedback jointly shape agent behavior, arguing that prompt writing alone is not enough to make systems stable.
The talk focuses on a seed-asset agent that turns messy advertising creatives into clean reusable assets for downstream generative AI tools. Key lessons include:
- prompting alone did not produce reliable behavior;
- evals worked better as feedback signals than as static scorecards;
- agent trace logs helped explain why failures happened;
- iteration had to avoid regressing previously fixed issues.
The speakers are Chris Souza, Preetika Bhateja, and Daniel Bump from Google.
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