An evidence-based promotion/demotion lifecycle converts validated LLM agent traces into zero-token deterministic workflows, reducing per-incident cost by 70% in a production cloud-networking system.
ReAct: Synergizing reasoning and acting in language models,
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Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production
An evidence-based promotion/demotion lifecycle converts validated LLM agent traces into zero-token deterministic workflows, reducing per-incident cost by 70% in a production cloud-networking system.