From Code to Intelligence: The Rise of the Full-Stack AI Engineer

Most AI projects don’t fail because the model isn’t good enough—they fail because everything around the model isn’t built. In this session, we’ll break down what it actually takes to deliver enterprise AI systems that make it to production and create real value. Drawing on real-world implementations across government, finance, and education, we’ll show why AI success is an ecosystem problem—not a model, prompt, or framework problem. You’ll see how modern enterprise AI systems are built and explore how the Microsoft AI ecosystem (Foundry, Fabric, Copilot, and emerging “IQ” layers) is converging into a unified intelligence platform—and what that means for how developers design systems today. Along the way, we’ll unpack the most common failure patterns and more importantly, we’ll show what actually works: - how to move from pilots to platforms how to build an enterprise intelligence capability iteratively, and how to deliver measurable value early while laying the foundations for agent-driven systems. For developers, this talk introduces a fundamental shift in the role itself. You’re no longer just writing code - you’re orchestrating intelligence across low-code and pro-code agents, data platforms, copilots, and governed systems. This is the rise of the Full-Stack AI Engineer. If you want to move beyond demos and build AI systems that scale, ship, and survive real enterprise constraints—this session is for you.