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The Multi-Agent Trap: Why More AI Agents Often Mean More Failures

Multi-Agent AI의 역설: 복잡해질수록 높아지는 87%의 실패율

Why it matters

Recent studies reveal that Multi-Agent Systems suffer from failure rates as high as 87% due to complex coordination issues and high 'token taxes.' For most production use cases, staying on the lower rungs of the autonomy ladder provides better reliability and cost-efficiency than over-engineered agentic architectures.

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Multi-AgentMAST StudyNeurIPS 2025Agentic AICoordination Tax

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