Shows how to inspect real application traces, define useful failure criteria and check automated evaluators against domain experts.
Why read Hamel Husain?
Husain gives you a way to get past a promising demo. His evaluation case study connects cheap assertions, human review and product experiments, using the same traces to find and explain failures. Start here when prompt changes keep fixing one problem and creating another.
His judge guide turns a domain expert’s pass/fail decisions and explanations into an evaluator you can test. The important part is the comparison with labeled examples and continued error analysis. He also coauthored Evals Skills with Shreya Shankar, providing reusable instructions for this work; the skills still need your product’s data and criteria.
Start with the original
Selected work
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Engineering case study ·
Your AI Product Needs Evals
How do you improve an AI product beyond its demo? Follow the real-estate assistant case study through assertions, readable traces, human/model review and product experiments. Each evaluation layer answers a different question.
Cite this selection
XFollowList, “Your AI Product Needs Evals” reading notes in the Hamel Husain profile. https://xfollowlist.com/people/hamel-husain#work-92f4e02bdc68
The linked work is the original source; this permalink identifies XFollowList’s reason to read it. Original work published .
Profile-source checking date and references · Dated reading map
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Evaluation guide ·
Using LLM-as-a-Judge For Evaluation: A Complete Guide
How can you trust an automated evaluator? Start with a domain expert’s labeled examples and critiques, then separate prompt development from a held-out test and measure errors in both classes. The page was updated September 1, 2026.
Cite this selection
XFollowList, “Using LLM-as-a-Judge For Evaluation: A Complete Guide” reading notes in the Hamel Husain profile. https://xfollowlist.com/people/hamel-husain#work-fcff45b396d9
The linked work is the original source; this permalink identifies XFollowList’s reason to read it. Original work published .
Profile-source checking date and references · Dated reading map
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Coauthored project guide ·
Evals Skills for Coding Agents
How do you make evaluation work repeatable with a coding agent? This guide, coauthored with Shreya Shankar, routes from trace review to error discovery, checks and evaluator validation. Tune the instructions to your own data.
Cite this selection
XFollowList, “Evals Skills for Coding Agents” reading notes in the Hamel Husain profile. https://xfollowlist.com/people/hamel-husain#work-b49b07e0e6b9
The linked work is the original source; this permalink identifies XFollowList’s reason to read it. Original work published .
Profile-source checking date and references · Dated reading map
Projects & roles
Evals Skills
Skills he published with Shreya Shankar for product-specific evaluation: trace review, error discovery, code checks and evaluator validation.
Community rating
Sources & further reading
Profile sources checked . This describes checking these references, separately from the publication dates of selected works.
- His current author site identifies him as a machine learning engineer, describes evaluation teaching and writing, and links @HamelHusain. Airbnb and GitHub are presented as previous work.
- The dated announcement names Hamel Husain and Shreya Shankar as authors and links the project repository.
- Current public X title identifies Hamel Husain and @HamelHusain, consistent with his author-site link.
Cite this profile’s source check
XFollowList, Hamel Husain profile sources. Sources checked 2026-10-11. https://xfollowlist.com/people/hamel-husain#sources-checked