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Paper · arXiv

A Policy-Driven Runtime Layer for Agentic LLM Serving

Multi-agent LLM systems have become the dominant production workload, but the serving stack was not built for them. The agent framework above knows agent identities, role, schemas, and dispatch structure but never sees an engine-level event; the serving engine below sees every event but knows nothing about agents. A surprising number of cross-cutting policies depend on both: prefix caching, batch shaping, speculative execution, fairness, tool-result memoization, safety enforcement, and more. Each lives in the seam between the two layers and is currently solved by a one-off patch into one neighbor or the other. We argue this seam is best addressed by an architectural change rather than poi...

AuthorsRui Zhang, Chaeeun Kim, Liting Hu
Primary categorycs.AI
Published26 May 2026
Last updated at source30 July 2026
cs.AI
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