Shadow-Mode Validation
Tesla's perception loop applied to startups: stop asking customers what they would do. Run the new behavior in shadow and watch the divergence.
Tesla didn't solve "make a car drive itself." They solved one specific sub-problem: perception at scale in the real world, not in a simulator. The mechanism was shadow mode — every Tesla on the road runs the FSD model in parallel with the human driver. The model predicts what it would do, the human does what they actually do, and the delta is the learning signal.
The startup translation: stop asking customers what they would do. Run the new behavior in shadow alongside the current one and watch the divergence. A pricing change, a copy change, a feature removal — all of them can be A/B'd as shadow experiments without committing.
You're trying to predict revealed behavior from stated behavior. That's the wrong direction. Predict revealed behavior from revealed behavior, and only ship after the shadow has converged with what you'd build.