\begin{abstract}
AI agent architectures are often chosen heuristically even though coordination topology strongly affects
error propagation, handoff overhead, and tool-routing cost. We present a compact topology-centered model
of agent systems based on typed wiring diagrams and an epistemic interpretation of what different
coordination patterns make visible to workers and coordinators. From that model we derive
architecture-level results for reviewer-gated execution, independent versus centralized aggregation,
sequential coordination penalty, parallel acceleration under task decomposability, and tool-density
scaling. We then compare those qualitative predictions to large-scale external evaluations of multi-agent
LLM systems rather than claiming direct benchmark fit. The result is a design calculus for choosing agent
topology under reliability and cost constraints.
\end{abstract}
