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Daniel S. Scott | Microsoft Agent Framework in Practice. Build, orchestrate, and scale production-grade AI agents with Python, .NET, MCP tools, and cloud-ready workflows (2026) [PDF, EPUB] [EN]


 
 
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Daniel S. Scott | Microsoft Agent Framework in Practice. Build, orchestrate, and scale production-grade AI agents with Python, .NET, MCP tools, and cloud-ready workflows (2026) [PDF, EPUB]
Автор: Daniel S. Scott
Издательство: Independently published
ISBN: 979-8196459627
Жанр: Microsoft Programming, Software Testing, Microsoft .NET, Python Programming, Generative AI
Язык: Английский

Формат: PDF, EPUB
Качество: Изначально электронное (ebook)
Иллюстрации: Цветные и черно-белые

Описание:
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:

Build AI agents that produce structured, reliable decisions instead of inconsistent outputs
Orchestrate multi-agent workflows with clear roles and controlled execution paths
Integrate MCP tools and external APIs without losing control of your system
Design scalable architectures that handle real traffic, not just demos
Implement memory, state management, and workflow checkpointing
Debug agent systems with confidence using tracing, logging, and metrics
Enforce security, authentication, and governance in sensitive environments
Deploy and scale agents using containers, serverless runtimes, and cloud platforms
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:

Why do my agents behave differently in production?
How do I safely connect AI to real-world actions?
What does a scalable agent architecture actually look like?
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.
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