The Data Flywheel Assumption: When AI Features Compound and When They Just Accumulate Noise
· 9 min read
Every AI pitch deck includes a slide about the data flywheel. The story is appealing: users interact with your AI feature, that interaction generates data, the data trains a better model, the better model attracts more users, and the cycle repeats. Scale long enough and you have an insurmountable competitive moat.
The problem is that most teams shipping AI features don't have a flywheel. They have a log file. A very large, expensive-to-store log file that has never improved their model and never will—because the three preconditions for a real flywheel are missing and nobody has asked whether they're present.
