Automatic Function Calling with Semantic Kernel SDK

Large language models are incredibly powerful, but they are isolated from your actual applications, databases, and APIs. Semantic Kernel bridges this gap, allowing AI agents to automatically select and run your native code based on natural language user intent. This text-only course guides you through the process of setting up, securing, and deploying automatic function calling in your applications. By the end of this course, you will understand how to transition from writing static prompts to building dynamic, agentic workflows where AI models intelligently execute the right code at the right time. You will learn how to structure your functions so the AI can understand them, and how to manage the interaction loop safely. What you'll learn: - Understand the fundamental architecture of the Semantic Kernel and how plugins operate. - Configure native plugins and register custom functions for the kernel to discover. - Enable automatic function calling to let the AI model decide which tools to execute. - Implement secure input validation and robust error handling to protect your system from unexpected LLM outputs. - Apply state management and context tracking across multiple sequential function calls. We begin with foundational concepts, defining the kernel, plugins, and planners. You will then progress through clear, text-based code examples that demonstrate how to register functions, handle automatic invocation, and secure your execution environment. This course is designed for software developers who are new to Semantic Kernel but have a basic understanding of programming and API concepts. No prior AI or machine learning background is required. Start reading today to unlock the power of autonomous AI agents within your own software ecosystem.