Day 43: When hierarchy helps multi-agent work scale
Why hierarchy helps when work has real layers of authority and responsibility.

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Series
A practical pattern catalog for multi-agent systems. This series explains hierarchy, dynamic dispatch, pipeline handoffs, peer collaboration, shared blackboard state, and debate-with-judge patterns through production ownership and reliability questions.
Why hierarchy helps when work has real layers of authority and responsibility.

Why dynamic dispatch needs visible routing decisions and clear final ownership.

Why predictable AI workflows often benefit from pipeline structure before agent autonomy.

Why peer agents need communication rules, round limits, and a final decision owner.

Why shared state needs structure, attribution, and versioning to stay debuggable.

Why AI debate is only useful when the judge has reliable criteria.
