How pdf.net Used GitHub Actions and Claude AI to Auto-Triage E2E Test Failures

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pdf.net, an AI-first software team, faced a scaling challenge with 18 developers merging an average of 17 pull requests daily but only one QA engineer overseeing quality. To avoid bottlenecks, the team shifted end-to-end testing to run on every merge to staging rather than waiting for a single daily release, which multiplied the number of test failures requiring investigation. They built a reusable GitHub Action that integrates with Claude AI, Allure TestOps, Linear, and Slack to automatically triage each failed test run and assign blame to a PR, an infrastructure issue, an external service, or a flaky test. The bot collects failed test steps, job logs, deploy commit ranges, and PR diffs before prompting Claude for a verdict and a fix hypothesis, then routes notifications or tickets accordingly. The entire automated triage system costs less per month than one hour of engineering time, effectively replacing what would otherwise be repetitive, manual detective work after every merge.

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