Most teams have adopted AI for code completion—but that’s only the first step. The real challenge is turning those early gains into consistent, production-grade improvements across the software delivery lifecycle. In this session, we’ll share what we’ve learned working across real projects as we moved from AI-assisted coding to emerging agent-native delivery models. We’ll walk through where AI helped, where it broke down, and what had to change across architecture, workflows, and engineering practices to make it reliable at scale. You’ll see how concepts like structured context, guardrails, and multi-step automation are reshaping how software is built—from requirements and design through testing and deployment. We’ll also cover how engineering roles are evolving, what new skills are becoming critical, and how teams can move beyond experimentation to measurable outcomes. If you’re using tools like Copilot today and wondering what comes next, this session provides a practical, experience-based view of where AI is delivering real value—and how to apply it in your own environment.