Designing and Governing Multi-Agent AI Systems

Single AI prompts often fall short when tackling complex, multi-step business workflows. By coordinating multiple specialized AI agents, you can build systems that collaborate, self-correct, and solve sophisticated problems autonomously. This text-based course guides you from the fundamental concepts of agentic workflows to designing and governing your own cooperative AI architectures. You will read through clear explanations of how to assign roles, manage agent communication, integrate external tools, and implement safety guardrails. What you'll learn: Understand the foundational architecture of AI agents, including planning, memory, and tool usage; Design collaborative workflows where multiple agents communicate, share state, and divide labor; Integrate external tools and APIs to give your agents real-world capabilities; Implement modern governance, evaluation frameworks, and safety guardrails to monitor agent behavior; Apply advanced prompt engineering strategies optimized for multi-agent coordination. The course starts with essential terminology and the mechanics of a single agent before moving step-by-step into multi-agent coordination, state management, and lifecycle governance. This program is designed for beginners, developers, and product managers looking to understand autonomous AI systems, with no prior machine learning background required. Start reading today to master the next frontier of cooperative artificial intelligence.