Brief
AI Evals FAQ Draws a Line Between Model Benchmarks and Product Evals
A curated FAQ on AI evals collects common questions from teaching 700+ engineers and PMs, and distinguishes model benchmarks from product evals.
AI evals are tests that tell you whether an AI system is doing what you want, according to the FAQ. It splits evals into model benchmarks, which compare general-purpose models on shared tasks, and product evals, which measure whether your specific AI product does what you want. Product evals cover the model, prompts, retrieval, tools and application code. The FAQ warns its opinions are sharp and not universal truths.
Source details and supporting facts
Each line is stated by the page named above it.
Stated by hamel.dev
- AI evals are tests that tell you whether an AI system is doing what you want.
- Model benchmarks compare general-purpose models on shared tasks.
- Product evals measure whether your specific AI product does what you want it to do.
- Product evals encompass all components of your product, including the model, prompts, retrieval, tools, and application code.
- This document curates the most common questions Shreya and I received while teaching 700+ engineers & PMs AI Evals.
- These are sharp opinions about what works in most cases. They are not universal truths.
Sources
- Hamel HusainText stored 15 September 2026
How this story was checked. Written from the 1 page listed above, stored 15 September 2026; claims checked against that stored text on 15 September 2026.
What that means
- 6 of 6 reported statements were confirmed against the page that carries them; the rest were removed rather than published.
- Figures in the text were required to appear in the stored source text: yes. Identifiers: yes.
- The check reads stored text only: no claim rests on a fresh look that did not happen.
- Where the reporting was silent, the text says so instead of filling the gap.