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Substrate-Portable Execution for Production LLM Workflows

arXiv · AI, language, vision and robotics · article · Sep 5, 2026 · UTC

Production LLM agents execute tool-calling loops, retrieval chains, and compositional workflows in multiple modes, yet execution semantics are often coupled to one runtime. We encountered this portability problem in Rufus, a conversational AI assistant with a large tool catalog that serves millions of Amazon customers. Rufus supports real-time serving, asynchronous background tasks, and high-volume batch workloads such as evaluation and content pregeneration. Each mode has distinct service-level objectives and typically uses a separate runtime. Reusing streaming orchestration makes asynchronou

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Evidence & attribution

First collected: 2026-09-20T21:32:07.623Z. This is not the publication date.