AI is changing how quickly product teams can collect, understand and act on customer feedback. But faster insight means little if it never makes its way into product decisions. In this keynote, Meg shares a founder-CPO perspective on using AI to turn qualitative signals into measurable success criteria, sharper priorities and meaningful product action. Drawing on her experience building Unfold as an AI-native, lean and user-led product, Meg explores how teams can close the loop between voice of customer, product metrics and continuous delivery. From clustering feedback at scale to building faster learning cycles around iterative releases, this session looks at what happens when the product itself and the way you build it becomes increasingly AI-driven. Attendee takeaways: - How AI can help product teams cluster and act on qualitative customer signals faster - Ways to translate raw customer feedback into measurable product success criteria - How to ensure insights influence roadmaps and strategic decisions, not just the backlog - How fast feedback loops can support more continuous, iterative product delivery - What product discovery and insight look like when the product itself is AI-driven - Lessons from building an AI-native product with a lean, inclusive and deeply user-led approach