📄 中文摘要
与全球汽车行业领导者合作，开发其售后软件平台，该平台最近推出了七个模块，每个模块作为微服务构建。服务之间的通信主要通过消息流代理进行，数据流动复杂，涉及上下游依赖、双向通信模式以及基于上下文的条件路由。当最终用户提出投诉时，支持团队需进行初步根本原因分析，然后再升级到工程团队。系统的复杂性使得快速直观的调试变得困难，且“如何连接一切”的思维模型集中在少数人身上。
为全球汽车行业领导者的售后软件部门构建运营支持 AI 代理
📄 English Summary
How We Built An Operations Support AI Agent for a Global Auto Industry Leader's Post Sales Software Department
Collaborating with a global leader in the automotive industry, an operations support AI agent was developed for their post-sales software platform, which recently launched seven modules, each built as a microservice. Communication between services primarily occurred through a message streaming broker, resulting in a complex data flow involving upstream and downstream dependencies, bidirectional communication patterns, and conditional routing based on context. When end users raised complaints, the support team needed to conduct initial root cause analysis before escalating issues to engineering. The system's complexity hindered quick, intuitive debugging, and the mental model of how everything connected was concentrated in a few individuals.