Cloud AI platforms move fast enough to make any book about them feel out of date by the time it ships. This one is built to survive that problem. Rather than chasing every API change, Jonathan Owens hands you a decision-making framework: how to pick the right tool for a task instead of defaulting to the biggest model, how to know when an AI agent earns its complexity and when it doesn't, and how to wrap every system you build in the same safety and governance discipline regardless of how simple it looks. Across eight chapters you'll go from Microsoft Foundry's current architecture to hands-on workspace setup, generative AI with Azure OpenAI's model catalog, the Vision/Speech/Language toolkit, retrieval-augmented search, multi-agent systems with Foundry Agent Service, responsible AI and enterprise governance, and four real-world case studies spanning retail, healthcare, finance, and manufacturing. Every chapter ends with exercises you can actually run, not just read. Written for beginners and intermediate developers who want depth without academic detachment, this is the guide for anyone who needs to ship reliable, secure, cost-aware AI features on Azure, not just demo them.
