Genie: Uber的通用AI随叫随到副驾驶

In today’s fast-paced tech environment, maintaining robust on-call operations is crucial for ensuring seamless service functioning. Modern platform engineering teams face the challenge of efficiently managing on-call schedules, incident response, communication during critical moments, and strong customer support on Slack® channels.

在当今快节奏的技术环境中，保持强大的值班操作对于确保服务的无缝运行至关重要。现代平台工程团队面临着高效管理值班时间表、事件响应、关键时刻的沟通以及在Slack®频道上提供强有力的客户支持的挑战。

This post describes Genie, an on-call copilot we built that uses generative AI to optimize communication and question-answering with on-call engineers.

这篇文章描述了Genie，一个我们构建的随叫随到副驾驶，使用生成式AI来优化与随叫随到工程师的沟通和问答。

At Uber, different teams like the Michelangelo team have Slack support channels where their internal users can ask for help. People ask around 45,000 questions on these channels each month, as shown in Figure 1. High question volumes and long response wait times reduce productivity for users and on-call engineers.

在Uber，不同的团队如Michelangelo团队有Slack支持频道，内部用户可以在这些频道中寻求帮助。每月在这些频道中大约有45,000个问题，如图1所示。高问题量和长响应等待时间降低了用户和值班工程师的生产力。

Figure 1: The high number of questions asked across Slack channels at Uber over 5 months.

图 1：在 5 个月内 Uber 的 Slack 频道中提出的大量问题。

Figure 2: The slow process of waiting for an on-call engineer to answer a question.

图2：等待随叫随到工程师回答问题的缓慢过程。

Typically, when users ask a question in a Slack channel, they have to wait for the on-call engineer to respond. The on-call engineer either answers the user’s initial question or asks for more details. Users might then ask follow-up questions, seek more clarification, or provide extra information. This leads to another wait for a response from the on-call engineer. After several rounds of back-and-forth communication, the user’s question eventually gets resolved.

通常，当用户在Slack频道中提出问题时，他们必须等待值班工程师的回应。值班工程师要么回答用户的初始问题，要么要求更多细节。用户可能会接着提出后续问题，寻求更多澄清，或提供额外信息。这导致用户需要再次等待值班工程师的回应。经过几轮来回沟通后，用户的问题最终得到解决。

Many questions could‌ get answered by referring to existing documentation, but the information is fragmented across Uber’s internal wiki called Engwi...