Textbook in PDF format Companies are now moving Generative AI projects out of the lab and into production environments. To support these increasingly sophisticated applications, they’re turning to advanced practices such as multi-agent architectures and complex code-based frameworks. This practical handbook shows you how to leverage cutting-edge techniques using Microsoft’s powerful ecosystem of tools to deploy trustworthy AI systems tailored to your organization’s needs. Written for and by AI professionals, Generative AI on Microsoft Azure goes beyond the technical core aspects, examining underlying principles, tools, and practices in depth, from the art of prompt engineering to strategies for fine-tuning models to advanced techniques like retrieval-augmented generation (RAG) and agentic AI. Through real-world case studies and insights from top experts, you’ll learn how to harness AI’s full potential on Azure, paving the way for groundbreaking solutions and sustainable success in today’s AI-driven landscape. Generative AI (GenAI) is evolving at a pace few technologies have ever matched. What began as fascination with increasingly powerful models has quickly matured into something far more complex and consequential: platforms, architectures, governance frameworks, and production systems that reshape how modern software is designed and operated. This book is written from the field, by three practitioners and friends who live this transformation every day. Each of us brings a distinct perspective shaped by hands-on work with enterprise customers, startups, and global engineering communities. Together, our voices reflect different angles of the same reality: GenAI is no longer an experiment, and Microsoft Azure is changing the way companies implement enterprise-grade solutions. Understand the technical foundations of generative AI and how the technology has evolved over the last few years Implement advanced GenAI applications using Microsoft services like Microsoft Foundry, Copilot, GitHub Models, Azure Databricks, and Snowflake on Azure Leverage patterns, tools, frameworks, and platforms to customize AI projects Manage, govern, and secure your AI-enabled systems with responsible AI practices Learn to avoid common pitfalls, future-proof your applications, and more