Building Production AI Agents with Tool Use, Function Calling, and MCP
About this session
AI models write great text, but they become truly useful when they can actually get work done. Connecting models to real-world software like databases, APIs, and business systems takes solid engineering to keep things reliable and safe. In this talk, we will look under the hood of AI agents. You will learn how function calling turns user requests into reliable code, how to give models the right tools without confusing them, and how the Model Context Protocol (MCP) makes connecting data sources much simpler. We will cover practical design patterns for running tasks, fixing errors, managing permissions, and turning fragile AI demos into software you can trust in production.
Speaker
Key takeaways
- How Function Calling Works: Learn how models output clean, predictable data formats instead of making things up.
- Why MCP Matters: See how the Model Context Protocol lets you plug databases, files, and APIs into your AI without writing messy custom code.
- Building Reliable Agents: Discover proven setups to keep tasks on track, prevent crashes, manage token limits, and include human checkpoints.