Multi-agent system (agent crew)
Multi-agent system (agent crew) is a multi-agent system, or agent crew, is a set of AI agents that work together on a larger goal, each handling a specialty — one researches, one writes, one checks, one executes. A coordinating layer or lead agent breaks the work down, routes tasks, and assembles the results.
One agent doing everything tends to do everything averagely. A crew splits the work the way a team would: for an exhibitor outreach campaign, a research agent gathers company context, a writing agent drafts personalized messages, a review agent checks tone and facts against your guidelines, and a scheduling agent queues the sends. Each agent stays simple and inspectable because its job is narrow. For event teams, crews make sense when a workflow has clearly distinct stages and enough volume to justify the setup — think processing hundreds of exhibitor renewals, or turning post-event data into per-exhibitor ROI reports. They're overkill for one-off tasks, where a single agent or a human with a copilot is faster to set up and easier to trust. The honest nuance is that coordination is the hard part. Errors compound across handoffs: a research agent's wrong fact becomes the writing agent's confident sentence. Good crews build in checkpoints — a verification step between stages, and a human review before anything leaves the building. Start by automating one stage of a workflow with one agent, prove it, then add the next. Crews assembled all at once are debugged all at once, painfully.
Direct answer
A multi-agent system, or agent crew, is a set of AI agents that work together on a larger goal, each handling a specialty — one researches, one writes, one checks, one executes. A coordinating layer or lead agent breaks the work down, routes tasks, and assembles the results.
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