I Built a Starter Repo That Turns AI Coding Tools Into Senior Engineers

I Built a Starter Repo That Turns AI Coding Tools Into Senior Engineers Every new project starts the same way: create a repo, write some code, realize you have no CI, no linting, no test enforcement, no issue templates. Three weeks in, you're debugging a production incident with no runbook, your AI coding assistant is generating code that doesn't follow your conventions, and half the team is committing directly to main. I've set up development practices across multiple production projects — from a multi-cluster AI evaluation platform on GCP to Python evaluation pipelines. The same patterns kept working: Ruff for linting with auto-fix in CI, pre-commit hooks that catch problems before they reach the remote, test coverage enforcement that posts PR comments telling you exactly which test files to create, and incident runbooks that turn 2-hour debugging sessions into 15-minute triage flows. So I extracted all of it into a single, clone-and-go starter repo. But I added something the origina