Lenny's Podcast: Product | Career | Growth

Why AI evals are the hottest new skill for product builders | Hamel Husain & Shreya Shankar (creators of the #1 eval course)

1368 snips
Sep 25, 2025
Hamel Husain, an AI product educator and consultant, and Shreya Shankar, a researcher and product expert, share their insights on AI evals. They explain why evals are essential for AI product builders, delve into error analysis techniques, and discuss the balance between code-based evaluations and LLM judges. Listeners will learn about practical tips for implementing evals with minimal time investment and common pitfalls to avoid. The duo also highlights the importance of systematic measurement in enhancing AI product effectiveness.
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INSIGHT

Evals Are Product Analytics For LLMs

  • Evals are systematic measurements of an AI application's quality, like data analytics for LLM products.
  • They create metrics and feedback loops so teams can iterate with confidence.
ANECDOTE

Real Estate Assistant Example

  • Hamel used NurtureBoss, an AI assistant for property managers, as a real-world example to show traces and system prompts.
  • He walked through actual logs to demonstrate how evals uncover problems in production behavior.
ADVICE

Write Quick Open Notes First

  • Start error analysis by writing quick open notes on individual traces and capture the first upstream error you see.
  • Sample traces rather than trying to label everything to learn rapidly and keep the process manageable.
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