If you’re a premium subscriber, add the private feed to your podcast app at add.lennysreads.com

Dr. Marily Nika, longtime AI PM at Google and Meta, shares a simple weekly ritual that rapidly builds AI product sense – the ability to translate probabilistic model behavior into products people can trust. In this episode, Marily walks through the framework for uncovering failure modes before users do.

Listen now: YouTube | Apple | Spotify

In this episode, you’ll learn

• Why Meta added “Product Sense with AI” to its PM interview loop

• The rituals that surface hidden failure modes

• Why generative models confidently invent structure when confronted with mess

• What minimum viable quality (MVQ) means and how to define three critical thresholds

• Five strategic context factors that raise or lower your quality bar

• Why you need to estimate your AI feature’s cost envelope early

• How to design guardrails that protect users from model shortcomings

• Four patterns that cover most real-world failure cases

Referenced

• AI PM Bootcamp & Certification

• AI Product Sense & AI PM Interview prep

• Dr. Marily Nika: https://www.linkedin.com/in/marilynika/

• How to build AI Product sense (Part 1)

• Marily’s AI Product Academy Newsletter

• Thriving as a senior IC PM in the AI era

About

Welcome to Lenny's Reads, where every week you’ll find a fresh audio version of my newsletter about building product, driving growth, and accelerating your career, read to you by the soothing voice of Lennybot.

To hear more, visit www.lennysnewsletter.com

Listen: Building AI product sense, part 2

Lenny's Reads (private feed for popufig@gmail.com)