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Home - Creator Economy & Culture - AI Evaluations Crash Course in 50 Minutes (Actual Instance)
Creator Economy & Culture

AI Evaluations Crash Course in 50 Minutes (Actual Instance)

NextTechBy NextTechSeptember 29, 2025No Comments2 Mins Read
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AI Evaluations Crash Course in 50 Minutes (Actual Instance)
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Expensive subscribers,

Right now, I need to share a brand new episode with Hamel Husain.

Hamel has skilled 2,000+ PMs and engineers from firms like OpenAI, Anthropic, and Google on how you can run AI evals. In my new episode, he shares a free grasp class on how you can construct evals for an actual AI agent in simply 50 minutes utilizing a easy spreadsheet. I realized loads from Hamel and I feel you’ll too!

Watch now on YouTube, Apple, and Spotify.

In case you loved this tutorial, Hamel can also be providing $1,330 off his AI evaluations course to readers of this text. Join his final cohort of the yr by 10/6.

Hamel and I talked about:

  • (00:00) What essentially the most invaluable a part of evals is

  • (01:25) Stay walkthrough: Analyzing 100 actual manufacturing traces

  • (09:50) Creating the eval standards utilizing a easy spreadsheet

  • (24:44) Why binary go/fail scores beat 1-5 scores each time

  • (28:52) The settlement metric lure that fools most PMs

  • (30:08) True optimistic and unfavourable charges defined

  • (36:00) Learn how to arrange steady evals in manufacturing

  1. Skip generic eval standards to judge particular product issues as an alternative. “Generic evals don’t measure a very powerful issues together with your AI product.” As an alternative of “helpfulness” or “correctness”, create evals for particular product points like “human handoff failure” or “tour scheduling concern.”

  2. Comply with Hamel’s 4-step eval course of.

    1. Begin by manually labeling 100+ AI conversations (traces):

      Paste your guide labels right into a spreadsheet and categorize them with AI
    2. Use knowledge evaluation to determine and depend the commonest points:

      https%3A%2F%2Fsubstack post media.s3.amazonaws.com%2Fpublic%2Fimages%2F190023c6 be74 4a54 a414
      Create a easy pivot desk to depend points by class
    3. Create LLM judges with binary go/fail labels. Validate judges utilizing true optimistic and true unfavourable charges as an alternative of solely alignment. Extra beneath.

    4. Deploy LLM judges to manufacturing and do guide knowledge labeling periodically.

    5. You are able to do all the above utilizing a easy spreadsheet. Right here’s a hyperlink to Hamel’s sheet to judge an actual AI agent utilizing the steps above:

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