Multi-agent LLM frameworks make it trivially easy to scale agent count, but provide no principled criterion for when to stop. This paper addresses that gap through the Agent Coordination Bound (ACB): a structural heuristic showing that inter-agent communication channels grow as n(n-1)/2 and coordination overhead eventually dominates reasoning gain. The model predicts an optimal fleet size of n* = ⌈a/c⌉. This paper derives six analytical contributions, including a degradation probability P(harm|n), a topology crossover theorem, and a Coordination Bottleneck Index (CBI) as a deployable scalar diagnostic.
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Benjamin KOUDLANSKI (Mon,) studied this question.
www.synapsesocial.com/papers/69df2c88e4eeef8a2a6b1ac6 — DOI: https://doi.org/10.5281/zenodo.19557626
Benjamin KOUDLANSKI
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