As large language models and intelligent services become foundational to modern applications, architects and developers are rethinking their cloud-native patterns. In this session, we’ll explore what it means to build AI-first applications using Platform-as-a-Service (PaaS) on Microsoft Azure.

We’ll walk through practical architectures that embed Azure OpenAI, Cognitive Services, and event-driven workflows directly into your apps—without having to manage infrastructure. You’ll also see how the Model Control Plane (MCP) enables standardized model management, monitoring, and governance, ensuring consistent lifecycle control across environments.

You’ll discover how to combine services like Azure App Service, Functions, Cosmos DB, and API Management with MCP to deliver scalable, intelligent experiences at speed—while maintaining alignment with enterprise policies and compliance requirements.

Through two real-world inspired examples—an AI-powered customer support bot and a real-time feedback analyzer—you’ll learn how to operationalize LLMs, manage them via the MCP, choose the right Azure components, and apply best practices for security, cost optimization, and governance.

Whether you're modernizing legacy apps or building cloud-native platforms from scratch, this session will give you a solid blueprint to go from PaaS to the future with AI at the core, with MCP ensuring your models remain under control and enterprise-ready.