Welcome to Architecting Agentic AI: Design and Deployment of Multi-Agent Systems—a technical course designed to help you understand how intelligent AI agents can be organized, coordinated, and architected into powerful Multi-Agent Systems (MAS). As AI systems become more capable and autonomous, many complex problems cannot be effectively handled by a single agent alone. Multi-Agent Systems provide a way to divide responsibilities among specialized agents, coordinate their activities, enable communication, and create scalable architectures for solving complex tasks.
In this course, you will begin with the core principles of single-agent design and understand the foundation on which more advanced Agentic AI architectures are built. You will then explore why organizations may move from a single-agent approach toward Multi-Agent Systems and how multiple autonomous agents can work together as a coordinated system. You will learn the anatomy of a Multi-Agent System, including agent roles, responsibilities, coordination, communication, autonomy, and system-level interactions. The course then examines different architectural approaches, including centralized control, decentralized autonomy, hierarchical systems, heterarchical systems, and hybrid architectures.
A major focus of the course is understanding how agents communicate and share information. You will explore important communication paradigms such as message passing and the blackboard/shared-ledger approach, and understand how these choices influence the overall system architecture. You will also learn how to evaluate different Multi-Agent System architectures and select an appropriate architecture based on factors such as control, coordination, communication, autonomy, scalability, and system requirements.
