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arXiv AI By Subhrangshu Nandi, Hitesh Arora, Yunfei Bai, Udita Patel, Chirag Shah, Hannah Kwon, Wei Zhang, Weian Chen, Chloe Ruoqi Li, Alberto Sconfienza, Ayush Goyal, Yasmine Lee, Ming Xiong, Prathap Ramachandra

Agent Architecture Cost-Success Trade-offs: A Controlled Evaluation across Enterprise-Style SOPs

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The study evaluates four large language model agent architectures—single function‑calling, skill‑augmented, centralized multi‑agent orchestration, and triage swarm—across 13 enterprise standard operating procedures (SOPs). Results show no single architecture dominates; success varies with SOP complexity, and added structural complexity often incurs higher token usage and latency without significant performance gains. The research highlights that implementation quality, rather than the choice between single or multi‑agent designs, is the key determinant of task success.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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