Building AI Agents with OpenAI

Artificial intelligence is shifting from passive chat interfaces to autonomous agents that can plan, use tools, and execute complex workflows. This course provides a clear, step-by-step path to understanding and building your own AI agents using OpenAI tools and modern orchestration frameworks. You will transition from writing basic prompts to developing structured, stateful agents capable of solving real-world problems. By reading through conceptual breakdowns and analyzing structured code snippets, you will learn how to give your agents memory, connect them to external data sources, and coordinate multiple agents to work together. What you'll learn: - Understand the core architecture, terminology, and design patterns of autonomous AI agents. - Implement agent memory systems to maintain context across complex, multi-step interactions. - Integrate Retrieval-Augmented Generation (RAG) to ground your agents in custom, external knowledge bases. - Configure tools and APIs using modern protocols to allow agents to interact with external data sources. - Design multi-agent workflows where specialized agents collaborate to achieve a shared objective. - Apply best practices for testing, debugging, and deploying agents securely and efficiently. The course begins with foundational AI agent concepts and terminology before moving into hands-on configuration of memory, tool integration, and multi-agent deployment. Each module reinforces the concepts through written explanations and clear, readable code examples. This course is designed for software developers, tech enthusiasts, and curious beginners who want to build autonomous systems. No prior experience with AI agent development is required, though a basic understanding of programming concepts is helpful. Start reading today to build and deploy your first intelligent AI agents.