Building AI Agent Skills with Anthropic

In the rapidly evolving landscape of artificial intelligence, static chat interfaces are no longer enough. To build truly helpful systems, you must learn how to design autonomous agents that can actively interact with external resources, retrieve precise information, and execute complex workflows. This text-based course guides you through the foundational concepts of agentic design, focusing on how to extend agent capabilities safely and predictably. By completing this course, you will transition from writing simple prompts to architecting structured agent workflows that can perform reliable coding, data analysis, and deep research. You will gain a clear mental model of how agents think, plan, and execute actions based on the parameters you define. What you'll learn: - Understand the core architecture of autonomous agents and the fundamentals of tool calling. - Configure structured inputs and outputs to ensure predictable communication between agents and external systems. - Implement secure retrieval-augmented generation patterns to feed real-time knowledge to your agents. - Design robust error-handling and fallback strategies for when agent execution paths deviate. - Apply modern prompt engineering patterns specifically optimized for agentic decision-making. You will begin by mastering essential agent terminology, exploring the anatomy of a tool call, and understanding how models process structured instructions. From there, you will progress through practical, text-based walkthroughs that demonstrate how to design, test, and refine agent workflows for real-world reliability. This course is designed for software developers, product builders, and tech enthusiasts who want to move beyond basic API calls. No prior experience with agent architectures is required, though a basic understanding of programming concepts will help you get the most out of the written examples. Start reading today to build smarter, more capable AI agents that work for you.