The distance between an impressive model demonstration and an AI system that creates lasting value is larger than it appears. Success depends not only on what the model can do, but on choosing the right use case, designing the surrounding system and building the trust required for people to use it. In this session we will explore what it takes to translate frontier model capabilities into dependable applications. We'll examine the decisions that shape successful deployments, from grounding and evaluation to workflow design, user adoption and continuous improvement. Leave with a clearer understanding of what separates a compelling prototype from an AI application that performs reliably, earns trust and delivers measurable value in the real world.