Coordination as Architecture
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Multi-agent LLM systems fail in production at rates between 41% and 87%, and the majority of those failures are coordination defects, not base-model capability. Most published comparisons of multi-agent architectures cannot even tell you whether the gain came from coordination or from one configuration just having more context. This paper argues coordination should be treated as a configurable architectural layer, separable from agent logic and information access, then backs the position with an information-controlled experiment.
Information-controlled methodology: Same LLM, same tools, same prompt template, same per-call output cap. The only thing that varies is coordination structure. Once information access is held constant, the actual contribution of coordination becomes measurable for the first time.
Coordination as a separate layer: The paper proposes treating coordination structure (who talks to whom, when, with what aggregation rule) as a first-class architectural axis. That separation lets teams reason about coordination changes without re-running the entire stack.
A vocabulary for the field: Until now, "multi-agent beats single-agent" comparisons have been confounded by context-window asymmetries. This paper provides the methodology and vocabulary needed to actually test coordination claims, which is overdue infrastructure for the multi-agent research line.
Why it matters: If 41% to 87% of failures are coordination defects, fixing coordination is the highest-leverage thing builders can do. The paper turns that intuition into a measurable engineering target instead of a vibes-based debate.
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