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Google Explores Scaling Principles for Multi-agent Coordination

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Monday, February 16, 2026

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Google Research tried to answer the question of how to design agent systems for optimal performance by running a controlled evaluation of 180 agent configurations. From this, the team derived what they call the "first quantitative scaling principles for AI agent systems", showing that multi-agent...

Google Research tried to answer the question of how to design agent systems for optimal performance by running a controlled evaluation of 180 agent configurations. From this, the team derived what they call the "first quantitative scaling principles for AI agent systems", showing that multi-agent coordination does not reliably improve results and can even reduce performance.

By Sergio De Simone

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