Your team has decided they need a multi-agent system. That was probably the right call. But now everyone is spending time figuring out whether we need three agents or five agents. That is the wrong question. The number of agents is an outcome, not a decision. It comes from the pattern you choose, not from counting tasks on a whiteboard.

In this session you learn to pick the pattern first and let the agents follow. A supervisor that routes tasks to specialists. A sequential pipeline where agents hand off in order. A hierarchical tree where agents manage their own sub-agents. Role-based teams where each agent has a clear job. Controlled loops where an agent refines its own output but knows when to stop. Each pattern tells you exactly how many agents you need and what each one does. You learn how they share state without overwriting each other and how to keep one failure from crashing the whole system. Then you hit the point every growing team hits. Your agents are no longer in one codebase. The research agent lives with the data team. The writing agent lives with the content team. Different systems, different people. That is where A2A comes in. Agents discover each other, negotiate capabilities, and delegate tasks across team and system boundaries. You also learn how to trace every decision across every agent so when something breaks you see exactly where and why.