Structured LLM Agents with OpenAI Function Calling

Large language models are incredibly powerful, but getting them to interact reliably with external databases and APIs requires structured, predictable data. By leveraging structured JSON and function calling, you can build AI agents that execute programmatic tasks with precision. This text-only course guides you from foundational concepts to designing robust, multi-tool agents. You will read clear explanations, analyze structured code patterns, and learn to enforce strict schema compliance to prevent model hallucinations. What you'll learn: - Understand the fundamentals of JSON schemas and structured outputs in language model workflows. - Configure OpenAI function calling to connect models with external APIs reliably. - Implement modern data validation patterns using libraries like Pydantic to ensure strict schema compliance. - Design multi-tool agents capable of routing user queries to the correct programmatic function. - Manage error handling, model fallbacks, and edge cases when tool calls fail. The course starts with essential terminology and the basics of structured data before moving into hands-on API configurations. You will learn by reading practical Python implementations and analyzing agent-routing logic step by step. This course is designed for beginner-to-intermediate developers and AI enthusiasts who want to build structured AI applications, with no prior agent development experience required. Start reading today to build reliable, structured AI agents.