A new GitHub Actions runner launches every week now. But getting faster runners is just one part of what the best engineering teams do to speed up their CI. Introducing CI Playbooks ▶️ an agent-friendly library of 253 GitHub Actions optimizations from companies running software factories. We analyzed 416 pull requests and commits, and 182 blog posts, talks, and podcasts from ten companies: 1. Anthropic: CI job volume grew 25x in six months as Claude came to write 80% of its code 2. DoorDash: build and test cut from 22 minutes to 6 3. Linear: jobs 34% faster while test suites almost quadrupled 4. Mastra: 29m 56s to 5m 06s p95 on StarSling runners 5. OpenAI: about 30 CI PRs took median CI from about 10 minutes to 4.5 6. Ramp: its coding agent accounts for 74% of merged PRs 7. Shopify: an agent running experiments made the Polaris build 65% faster 8. Spotify: deployer image build went from 2h28m to about 17 minutes 9. Stripe: runs about 5% of its full Ruby test suite per build 10. Uber: CI resource usage down 53%, wait times down 37% Some of these companies aren't using GitHub Actions as their CI engine internally so we translated all the optimizations they've talked about or made publicly in their repos, into their GHA equivalents. Every technique comes with its original source and a prompt your coding agent can run on your repo. Add .md to any playbook URL for the markdown version, or just hand this URL to your agent: There's tons to dig into here, I'm going to highlight some of the findings I found most interesting 🧵