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What if your AI agent works perfectly in testing... but breaks the moment real users touch it?
You've written prompts. You've connected APIs. You've seen promising results. But when it's time to scale, everything starts to fall apart. Responses become inconsistent. workflows get messy. Debugging turns into guesswork.
You're not alone and you're not missing talent. You're missing structure.
Microsoft Agent Framework in Practice shows you how to move beyond fragile prototypes and build production-grade AI agents that actually hold up under real-world conditions.
This book gives you a clear, hands-on system for designing, orchestrating, and scaling agent workflows using Python, .NET, MCP tools, and cloud-ready architectures. You will learn how to control agent behavior, enforce policies, and build systems that remain stable as complexity grows.
Instead of relying on unpredictable prompts, you'll build structured, observable, and secure agent systems that you can trust in production.
By the end of this book, you will be able to:
This is not theory. It is a practical, implementation-focused guide built for developers, engineers, and technical leaders who want to build AI systems that work beyond the prototype stage.
If you've ever asked yourself:
You will find clear answers here.
You already know what AI agents can do.
Now build systems that make them dependable.
Get your copy of Microsoft Agent Framework in Practice today and start building AI agents that perform when it matters.