运行时无关AI工作流：兼顾生产持久性与快速评估迭代
原标题：Article: Runtime-Agnostic AI Workflows: A Pattern for Production Durability and Fast Eval Iteration
AI 摘要
本文介绍了Brex公司AI工作流平台采用的一种运行时无关（runtime-agnostic）模式，将工作流编排逻辑与执行运行时解耦，使同一套逻辑既能用于生产环境的持久化分布式执行，也能用于快速迭代的离线评估。该模式通过纯业务逻辑和可插拔运行时，避免了逻辑版本漂移问题，但需要架构强制保证代码的运行时无关性，并需权衡对运行时原生特性的访问。
正文节选
Key Takeaways - AI workflows have two needs that trade off directly. Running reliably in production requires persisting and distributing every step so it survives crashes, deploys, and restarts. But that same machinery is what makes runs too heavy for the fast, throwaway loop you need to check an LLM's output quality. The properties that buy durability are the ones that kill iteration speed. - You can serve both needs by writing the workflow as pure business logic that doesn’t know where it runs