Airbnb's AI Eval Playbook: Read 100 Traces Before Writing Evaluators
samuelcolvin · x · 2026-08-07
Airbnb recently published its playbook for evaluating generative AI at scale, emphasizing the need to read roughly 100 outputs and traces before writing evaluators. Its three-layer evaluation framework includes:
- Programmatic checks: Using code to verify objective contracts and exact failures.
- LLM judges: Handling qualities that require interpretation, such as faithfulness.
- Human review: Establishing ground truth, resolving disputes, and calibrating LLM judges.
The Pydantic team demonstrates how to build this workflow end-to-end using Pydantic AI and Logfire, including evaluating a support agent, inspecting failures, calibrating judges, and using an optimizer to propose prompt improvements.
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