Teams building multi-agent systems are encountering scalability issues due to a common "manager" pattern, where a central agent routes tasks and holds all decisions, creating a single point of failure and context window bottlenecks. A more effective approach involves structuring agents as nodes in a graph, with edges defining control flow and a shared state object managing context, as demonstrated by LangGraph. This graph-based architecture, exemplified by Lyft's customer support system, enables observability, composability, and resilience, ultimately avoiding the limitations of the manager pattern.
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