Building AI Agents for Complex Multi-Step Tasks

Discover how to move beyond simple chatbot prompts and build autonomous systems that can plan, reason, and execute multi-step workflows. As artificial intelligence evolves, the ability to design self-directed agents is becoming one of the most valuable skills in modern technology. In this text-based course, you will transition from writing basic prompts to understanding and structuring architecture-driven AI systems. You will learn how to design intelligent agents that use external tools, access custom data sources, and collaborate to solve complex tasks. What you'll learn: Understand the foundational definitions, core terminology, and cognitive architectures of modern AI agents; Configure agents to interact with external environments using tool-use and function-calling techniques; Implement retrieval-augmented generation (RAG) patterns to give your agents access to private knowledge bases; Design collaborative multi-agent systems where specialized units delegate and review work; Apply systematic prompt engineering strategies to guide agent planning and self-correction; Practice building robust error-handling mechanisms to manage unexpected agent behaviors. The course begins with foundational concepts of agency and decision-making before guiding you through written explanations of agent design, tool integration, and collaborative architectures. This course is designed for developers, technology enthusiasts, and curious beginners who want a clear introduction to AI agent design, with no prior AI engineering experience required. Start reading today to build autonomous systems that can think, plan, and execute.