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The Multi-Agent Trap | Towards Data Science

Multi-Agent AI Systems Face Critical Error Amplification Google DeepMind researchers discovered that multi-agent networks amplify errors 17 times compared to single-agent systems, revealing a fundamental challenge in AI architecture. The findings highlight three key design patterns that distinguish successful projects worth $60M from the 40% of initiatives that get canceled before completion.