Hamel Husain's AI Evals FAQ: model benchmarks and product evals answer different questions
HamelHusain · x · 2026-09-24
Hamel Husain and Shreya Shankar published an FAQ on what AI evals actually are.
Key distinction:
- Model benchmarks: compare general-purpose models on shared tasks (GPQA Diamond, Terminal-Bench, MMLU), useful mainly for picking a starting model.
- Product evals: measure whether your specific AI product does what you want, covering the model, prompts, retrieval, tools, and application code—turning your judgment of a good experience into trackable metrics.
They frame evaluation as systematic quality measurement: each eval checks one behavior and returns a score or structured review; most products need multiple evals since they fail in different ways, and caught failures become data for improving the system.
Related event: Husain and Shankar Publish Deep Guide on AI Evals(4 posts)→
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