In this hands-on workshop, attendees will explore how to move from feature-based product development, where success is measured by releases to evidence-based product growth, where teams use customer behavior, experimentation, and AI-generated insights to make better product decisions. The workshop will also demonstrate how AI can accelerate customer-feedback analysis, surface behavioral patterns, generate testable hypotheses, and support faster prioritization without replacing product judgment. Topics explored include - Why feature velocity can create the illusion of progress without delivering measurable growth - Leverage AI to synthesize customer feedback, usage data, support trends, and market signals - Prioritize opportunities based on confidence, impact, and strength of evidence - Balancing AI-generated recommendations with human judgment and product strategy Participants will walk away with know-how to transform traditional feature request into a measurable growth hypothesis, identify the evidence needed to validate it, and design a rapid experimentation plan.