AI Feature PMF Signals: Why Your Metrics Are Lying to You
· 9 min read
When your AI feature ships and the metrics light up — DAU spikes, NPS climbs, thumbs-up feedback floods in — you could be looking at genuine product-market fit. Or you could be watching the first act of a two-part story where the second act ends with a retention cliff nobody saw coming.
The problem is these signals are structurally broken for probabilistic AI features. They were designed for deterministic software where "activated" means something, where a five-star rating predicts future use, where the novelty fades in days rather than masking a six-month churn wave. AI features behave differently, and the standard PMF toolkit is calibrated for the wrong inputs.
