Building Custom AI Agents with Agent APIs

Modern applications increasingly rely on intelligent automation to handle complex user requests, but building these systems from scratch is incredibly challenging. This text-based course guides you through the foundational concepts of designing, deploying, and managing custom AI agents using modern Agent APIs. You will learn how to transition from basic static prompts to dynamic, goal-oriented systems that can maintain context and execute multi-step tasks. By understanding the core mechanics of agentic workflows, you will be able to build smarter integrations that significantly enhance user interaction. What you'll learn: - Understand the core principles of agentic workflows, including planning, tool use, and memory systems - Configure API connections to manage stateful, multi-turn user sessions effectively - Implement retrieval-augmented generation patterns to ground your agent's responses in specific knowledge bases - Apply structured output formatting to ensure your agents return reliable, machine-readable data - Practice secure integration patterns to safely connect external tools and APIs to your agent This course begins with essential terminology, outlining the differences between simple LLM calls and true autonomous agents. You will then progress through the mechanics of session management, tool configuration, and response parsing, supported by clear, step-by-step written explanations and code examples. This course is designed for software developers, product builders, and technology enthusiasts who are new to AI agent architecture and want a clear, conceptual, and practical path forward. No prior experience with AI APIs is required, though basic programming knowledge will help you get the most out of the technical examples. Start reading today to build your first autonomous system.