Developing AI Agents with the Agent Framework

AI agents are transforming how we automate complex workflows, but building them requires a structured approach to orchestration and tool integration. This text-only course guides you through the core patterns of agentic design using the powerful Agent Framework. You will transition from understanding basic LLM prompts to designing cooperative multi-agent systems that can plan, use external tools, and execute tasks autonomously. Through clear written explanations and practical code walkthroughs, you will gain the skills to build production-ready agent workflows. What you'll learn: Understand the core architecture and design patterns of the Agent Framework; Configure individual agents with specific roles, instructions, and system prompts; Implement tool calling to allow agents to interact with external APIs and databases; Design multi-agent conversation flows and collaborative problem-solving patterns; Integrate Retrieval-Augmented Generation (RAG) to ground agent responses in custom data; Practice debugging and optimizing agent interactions through written code exercises. The course begins with foundational definitions of agentic workflows before moving step-by-step through single-agent configuration, tool integration, and multi-agent orchestration. You will read detailed conceptual breakdowns and analyze real-world code snippets to reinforce your learning. This course is designed for software developers and AI enthusiasts who are new to agentic frameworks, with no prior agent development experience required. Start reading today to build your first autonomous AI agent system.