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Learn Microsoft Semantic Kernel in C# with this step-by-step tutorial. Build AI agents, plugins, and copilots in .NET with runnable code. Start today. If you want to add real AI capabilities to a .NET application, Semantic Kernel C# is the fastest, most production-ready route available today. Microsoft Semantic Kernel (SK) is an open-source SDK that lets you plug large language models like GPT-4o, Claude, or local models into ordinary C# code, give them tools (called plugins ), and let them plan and execute multi-step tasks. In this Semantic Kernel tutorial you will build an AI agent step by step: from a "hello world" chat completion, through function calling with your own C# methods, to a stateful copilot that can answer questions about your own data. Every example targets .NET 8 or later and uses the stable Microsoft.SemanticKernel package. You can copy the code straight into a console app and run it. What Is Microsoft Semantic Kernel and Why Use It in C#? At its...

Learn how to build AI agents in C# using Semantic Kernel. Step-by-step tutorial with runnable code, best practices, and pitfalls. Start building today! Building AI agents in C# used to mean wiring up raw HTTP calls to a large language model and parsing JSON by hand. Today, Microsoft's Semantic Kernel gives .NET developers a production-ready framework for creating autonomous task-solving agents that can reason, call your code, and chain multiple steps together to complete real work. In this tutorial you'll learn how to build AI agents in C# from scratch using the Semantic Kernel Agent Framework, with runnable code examples, best practices, and the common pitfalls to avoid. Whether you're a beginner searching for "how to build an AI agent in C#," an intermediate developer looking for Semantic Kernel best practices, or a senior engineer designing advanced agent architectures in .NET, this guide covers the full picture — and explains why each piece matters...