The constraint on good product decisions was never talent or frameworks. It was research bandwidth. A PM at a Series B company gets maybe 10 hours a month for user research. After scheduling, conducting, and transcribing interviews, there's almost nothing left for actual synthesis. So most "insights" are vibes from 4 conversations. When you can load 50 transcripts into Claude, run per-participant analysis, cross-verify patterns, and audit the AI's reasoning in a single afternoon, you've 10x'd the sample size and cut the cycle from weeks to hours. The teams that operationalize this will look like they have superhuman product intuition. They'll just have better data, faster.