How we built an automated debugging workflow at Sentry

Sentry describes an automated debugging and issue-triage workflow designed to manage the growing volume of AI-generated code fixes without increasing engineers’ manual workload. Its Seer AI agent monitors instrumented applications, diagnoses issues, proposes fixes, and can open GitHub pull requests, with organizations able to choose how much human oversight is required. To ensure generated PRs are reviewed, Sentry uses a scheduled Claude routine that scans Slack notifications, asks Seer to identify the most relevant reviewer based on repository history, verifies that each PR remains open, and prompts the reviewer to merge or close it while leaving brief feedback. After several weeks of iteration to avoid duplicate messages and inappropriate notifications, the workflow showed early improvements in PR action rates and 48-hour response rates, while more PRs closed without merging were largely attributed to duplicate or broader alternative fixes rather than poor proposals. Sentry emphasizes that successful automation depends on routing work to the right people at the right time and notes that the required components, including Seer, Slack, GitHub, and automation tools such as Claude or Cursor, are available for others to implement.

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