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AI Evals for Product Managers

Hosted by Anshumani Ruddra

425 students

In this video

What you'll learn

Own & Lead AI Evaluation as the PM

Understand why the PM is the ideal AI evaluation owner. Use empathy and product context to define performance criteria

Build a Robust Generalizable AI Evaluation Framework

Move from one user to diverse data, use a 'living' Golden Set for regression, and utilize metrics beyond just accuracy

Implement Continuous Evaluation and Avoid Pitfalls

Automate evaluation as a continuous process. Use LLMs for qualitative checks and avoid pitfalls

Why this topic matters

Most AI features fail not because of bad models, but because of bad evaluation. Production AI systems need systematic evaluation - and PMs need to understand how to spec it, measure it, and improve it. You'll learn the eval loop: define "good" -> build your Golden Set -> choose your eval type -> automate & iterate

You'll learn from

Anshumani Ruddra

Product Super IC at Google | 22+ years of crafting blockbuster products

I have spent the last 22+ years building and teaching: first as an author of children's books, then as a game designer on some of the world's largest social games, and then as an entrepreneur and product leader across various global consumer tech businesses.

I'm an OG course instructor on Maven, teaching product builders for a decade+, and I'm part of the PM Faculty at Google. I believe the future belongs to the "Super IC" - individuals who leverage AI to drastically increase their output and as a force multiplier for their expertise. My teaching style is highly hands-on and practical; we will vibe-code, experiment, break things, and build working systems together.

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Anshumani Ruddra
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