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Building AI Product Sense, Part 2

In part two of "Building AI Product Sense," Dr. Marily Nika, an experienced AI product manager from Google and Meta, outlines a weekly ritual for developing AI product sense—translating model behavior into trustworthy products. She explains why Meta now includes "Product Sense with AI" in PM interviews and introduces frameworks for uncovering hidden failure modes, defining Minimum Viable Quality (MVQ) with three thresholds, and assessing five strategic context factors that adjust quality standards. Nika also stresses early estimation of an AI feature's cost envelope, designing guardrails, and presents four common failure patterns that cover most real‑world cases.