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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.
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
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