The developer's first instinct for AI is the cloud: it offers scalability and security. But what happens when you need rapid prototyping, offline development, enhanced data privacy, or the flexibility to experiment with the vast ecosystem of open-source models? This is where running AI workloads locally provides an undeniable advantage.

This session cuts through the noise, providing a deep, technical comparison of the practical trade-offs between the cloud-based Foundry and Foundry Local. We will explore the critical differences in cost, privacy, and performance, and directly contrast the curated model catalog with open-source alternatives. Through live demonstrations of switching environments and utilizing AI agents, you will see exactly how to structure your applications. This equips you with a straightforward, robust architectural strategy for moving seamlessly between cloud and local execution, empowering you to make better-informed, high-stakes decisions for your Azure AI projects.