Turning AI’s Random Answers Into Reliable Product Feedback
AI-driven features return unique outputs per user, breaking traditional feedback loops that assume consistent behavior. Gothelf proposes three instrumentable practices—track the next user action, capture context, and aggregate outcome distributions—to turn scattered interactions into actionable product insights. This lets teams evaluate AI value across the whole user base, not just isolated cases.