Agentic AI enables large language models to use tools to interact beyond system boundaries. From no-code implementations in Copilot Studio to developing sophisticated solutions using LangChain and Semantic Kernel, developers of all levels can leverage tools to create agentic solutions.

But how does agentic AI work under the hood?
How are models able to understand when to use a tool and how to use it?

In this demo intensive session Alan will explain the concepts of agentic AI in detail. Starting with the basics of function calling in the Open AI models, he will cover the techniques used to provide tools to models, and how the models are able to understand and use the tools. The use of prompting to guide models and improve tool call behavior will be covered, along with guidelines for adding tools to your solution. Alan will also cover the protocols used by Open AI models as well as how the model context protocol is used to provide compatibility between services and LLM solutions.

Join this session if you want to understand what goes on under the hood of function calling, MCP and agentic AI.