Foundations of AI Agent Development

Artificial intelligence is shifting from passive chat interfaces to active, autonomous agents capable of executing complex workflows. Understanding how to design and build these agents is becoming an essential skill for modern developers and tech enthusiasts. In this course, you will transition from a curious observer to a confident architect of autonomous systems. You will learn how to structure agents that can reason, plan, use external tools, and maintain memory to accomplish specific goals. What you'll learn: - Understand the foundational architecture of AI agents, including planning, memory, and tool execution. - Explore how large language models function as the central reasoning engine for autonomous systems. - Implement basic prompt engineering patterns and retrieval-augmented generation (RAG) to ground your agents in real-world data. - Configure agents to interact with external APIs and execute basic function calling. - Analyze real-world use cases to identify where agentic workflows can automate complex tasks. This text-only course begins with essential terminology and structural concepts before guiding you through written walkthroughs of agent design patterns. You will study code snippets and conceptual frameworks that illustrate how memory, tools, and reasoning engines work together. Designed for beginners, this course requires no prior experience with AI development, though a basic familiarity with programming concepts will help you get the most out of the written examples. Start reading today to build your first autonomous AI agent architecture.