{"product_id":"b0hjq2w2wk","title":"Building AI Agents with C# and .NET 10: A Developer’s First Guide to the Microsoft Agent Framework","description":"\u003cp\u003eBetween the launch of ChatGPT and the GA release of the Microsoft Agent Framework in April 2026, a new class of .NET applications emerged: programs that hold a language model in one hand and a set of tools in the other and decide for themselves how to string them together to reach a goal. The framework is ready. The guidance mostly isn’t — it lives scattered across API docs, conference talks, and GitHub samples pinned to preview builds that broke last Tuesday.\u003c\/p\u003e\n\n\u003cp\u003eBuilding AI Agents with C# and .NET 10 is the picture on the puzzle box. Twenty chapters take you from your first LLM call in C# to a production-hosted, observability-instrumented, safety-filtered multi-agent system, all on the stable, generally available surface of Microsoft Agent Framework 1.20, .NET 10 LTS, and C# 14.\u003c\/p\u003e\n\n\u003cp\u003eYou will learn how to: Build your first ChatClientAgent, give it a persona, and expose it over HTTP with Minimal API Solve the amnesia problem with sessions, history providers, and context providers Get typed C# records back from the model instead of strings you have to regex Give agents tools and function calling, with human-in-the-loop approval for the dangerous ones Build and consume Model Context Protocol (MCP) servers in C# Ground answers in your own documents with retrieval-augmented generation Send images, audio, and video to multimodal agents — and treat them as untrusted input Coordinate specialists with multi-agent orchestration and typed workflow graphs Host agents with ASP.NET Core and .NET Aspire, and instrument them with OpenTelemetry Layer guardrails against the OWASP LLM Top 10 and the OWASP Top 10 for Agentic Applications Package domain expertise as Agent Skills and measure quality with local and cloud evaluation Compose the whole stack into one object with the Agent Harness — and know when not to\u003cbr\u003e\nAlong the way you build the Contoso FAQ agent, a small but real production system that grows chapter by chapter until it ships: hosted, observable, guarded, and evaluated.\u003c\/p\u003e\n\n\u003cp\u003eWhat makes this book different is discipline. Every listing compile and runs, and everyone is paired with its expected console output, so you know what success looks like before you press F5. Chapters follow an Explain–Demonstrate–Practice rhythm. Exercises come in three tiers (Basic, Intermediate, Challenge) with full worked solutions in Appendix E. The companion repository — one solution, 125 runnable projects — works against Azure OpenAI, OpenAI, Microsoft Foundry, or a local Ollama model with a single configuration change, and ships a dedicated helper for Anthropic.\u003c\/p\u003e\n\n\u003cp\u003eWritten for intermediate C# developers. No AI or machine learning background required: if you can write a class, use LINQ, and wire up dependency injection, you’re ready. Coming from Semantic Kernel or AutoGen? Appendices B and C are your migration maps.\u003c\/p\u003e","brand":"ANT","offers":[{"title":"Ebook","offer_id":52855454302424,"sku":"YSL84336","price":17.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0835\/3356\/2072\/files\/71cOfWAo8vL._SY1500.jpg?v=1793419793","url":"https:\/\/www.bookmebay.com\/products\/b0hjq2w2wk","provider":"BookMebay","version":"1.0","type":"link"}