K-Culture GlossaryㅁTechnical words in the news
Multi-agent
A setup where multiple AIs split roles and work together — like forming a research team, a review team, and a writing team.
In plain words
It's a structure where several AI agents divide up the work and collaborate. One handles research, another drafts, another reviews, and they pass results back and forth — applying the corporate logic that a team beats a jack-of-all-trades to AI.
It tends to work better for complex tasks, and having agents check each other's work can reduce hallucinations. On the other hand, costs (in tokens) multiply, and new failure modes emerge, like misunderstandings spreading between agents. When you see terms like "agent orchestration" or "AI team," this is what's being described.
AI Agent vs. Multi-Agent: What's the Difference
Do multiple agents split up the roles, Does one agent see it through to the end
Multi-agent sounds like it just means "running several agents at once," but the real point isn't the number, it's dividing roles and having them check each other's work. Splitting the researching side from the reviewing side reduces the problem of one agent missing its own mistakes. But the more they exchange with each other, the more it costs and the slower it gets.
| Aspect | Multi-agent | AI Agent |
|---|---|---|
| Structure | Multiple agents with assigned roles exchange work | One agent plans and executes |
| Good for | Tasks that need broad coverage and mutual review, like research and reports | Tasks with clear steps, like booking, organizing, editing |
| Catching mistakes | Another agent filters it first | A human reviews the output |
| Cost and speed | More expensive and slower, the more exchange involved | Relatively cheap and fast |
| Analogy | A team with divided roles | One skilled employee |
Rule of thumbIf roles are split and agents check each other's work, it's multi-agent. If one agent sees the task through to the end alone, it's just an agent.
See also
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