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DoorDash Automates Feature Flag Cleanup with Multi-Agent LLMs

DoorDash已开发了一个使用多智能体LLM的自动化系统来清理过时的功能标志,这些标志是技术债务和运营风险的来源。该系统与MCP集成以获取实时上线数据,并与Jira集成以处理工单,成功为90%的已评估过时标志生成了拉取请求。这种自动清理过程比手动方法效率高得多,每次清理平均花费4.79美元,耗时13.8分钟。 AI

影响 展示了一个可扩展、经济高效的LLM解决方案,用于管理大型代码库中的技术债务。

排序理由 学术论文,详细介绍了LLM在软件工程中的工业应用。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

DoorDash Automates Feature Flag Cleanup with Multi-Agent LLMs

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学术论文,详细介绍了LLM在软件工程中的工业应用。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Jai Datar ·

    利用多智能体LLM系统大规模自动化功能标志清理:DoorDash的工业实践

    Feature flags are runtime configuration mechanisms used for gradual feature rollouts, experimentation, and kill switches. Once a feature is fully rolled out, the flag and its gated code become technical debt and can introduce operational risk through inadvertently enabling dorman…