Multi-Agent AI Patterns: Supervisor, Swarm, and Hierarchy

As artificial intelligence evolves from single-task models to autonomous systems, multi-agent orchestration is becoming the new standard. Discover how multiple AI agents can collaborate, delegate tasks, and execute complex workflows together. This course breaks down the core architectures of Agentic AI into accessible, written lessons. You will start with the fundamental terminology of agent design before exploring how to structure systems where specialized agents work in harmony. By understanding foundational patterns, you will be equipped to conceptualize and design scalable, intelligent workflows. What you'll learn: - Understand key terminology and foundational concepts of Agentic AI. - Design supervisor patterns where a central agent delegates tasks to specialized workers. - Explore swarm architectures for decentralized, collaborative problem-solving. - Apply hierarchical orchestration to manage complex, multi-step AI operations. - Integrate modern concepts like prompt engineering for agent personas and basic tool use. - Practice designing memory management and context-sharing protocols between agents. The curriculum flows smoothly from basic definitions and single-agent limitations to sophisticated multi-agent design patterns. You will read through practical architectural breakdowns and written exercises that solidify your understanding of modern AI systems. This course is designed specifically for beginners, requiring no prior programming experience or advanced AI knowledge. Start reading today to build your foundation in multi-agent orchestration.