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Scaling Multi-Agent Systems: The 45% Threshold
Everyone's building multi-agent systems. But a new Google DeepMind and MIT paper tested 260 configurations across six benchmarks and found something counterintuitive: independent agents amplify errors 17x compared to single agents, every multi-agent variant degraded sequential reasoning by 39-70%, and coordination overhead costs 1.6-6x more tokens for matched performance. The research reveals a clear threshold—the "45% rule"—where multi-agent coordination stops helping and starts hurting. We break down what's actually happening mechanically, why the industry got this wrong, and when agent…
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