AI Agentic Design Patterns with AutoGen

Artificial intelligence is evolving from simple prompt-and-response interactions to autonomous, collaborative systems. Implementing these multi-agent workflows requires structured design patterns that allow AI agents to communicate, use tools, and solve complex tasks together. This text-based course guides you through the foundational concepts of agentic design patterns using the AutoGen framework. You will learn how to define distinct roles for different agents, set up communication pathways, and build robust systems capable of executing complex multi-step tasks. What you'll learn: Understand the core principles of agentic design patterns and multi-agent collaboration; Configure individual AutoGen agents with specific roles, instructions, and system prompts; Implement structured communication patterns, including sequential chats and group chats; Enable agents to use external tools, execute code safely, and integrate basic retrieval-augmented generation patterns; Apply human-in-the-loop patterns to maintain control and safety in autonomous workflows; Troubleshoot, debug, and optimize agent interactions through written exercises and code analysis. You will start with the fundamental terminology of agentic AI before moving on to practical agent configuration. Through clear written explanations and step-by-step code walkthroughs, you will explore how to orchestrate multiple agents to work together seamlessly. This course is designed for software developers, tech enthusiasts, and AI hobbyists who are new to multi-agent frameworks. No prior experience with AutoGen is required, though a basic understanding of Python is helpful. Start reading today to master the design patterns shaping the future of autonomous AI.