Multi-Agent AI Needs an Orchestration Layer, Not Just a Shared Workspace

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A developer writing on DEV Community argues that giving multiple AI agents a shared workspace and context does not by itself produce effective collaboration. In enterprise workflow experiments, agents without coordination worked on overlapping tasks, produced contradictory outputs, blocked one another on shared resources, and lacked failure recovery. The author proposes an explicit orchestration layer that decomposes tasks, dispatches subtasks to specialized agents, reconciles results, and manages timeouts and retries. The article cites iflytek's astron-agent, which uses a meta-agent called a SuperAgent for this purpose, and astron-rpa as applying similar principles to robotic process automation.

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