How many required checks is “too many”?

Start with 3–5: build, unit tests, type check, formatter, and a critical security/secret scan. If your CI list doesn’t fit on a laptop screen without scrolling, you’ve almost certainly over-optimized the wrong thing.

Should we block on end-to-end tests?

Usually no. Run e2e post-merge against a staging canary with a circuit breaker and Prometheus SLOs. Keep PR checks fast and reliable; let deployment safety nets handle integration risk.

Do we need Bazel/Turborepo/Nx for a monorepo?

Not at first. Start with `paths` filters and aggregated checks. Add Turborepo/Nx when CI time and cache hit rates prove the need. Avoid bespoke graph builders unless you truly hit scale.

How do we keep AI-generated code from slipping risky patterns?

Use fast SAST and secret scans as annotations, enforce format/lint/type checks, and promote only critical findings to blocking. Pair that with `CODEOWNERS` on sensitive areas (crypto, auth, PII) for human review.

What metrics should we track to know it’s working?

Median PR cycle time, time to first CI signal, CI duration, re-run rate (flake), review wait time, and post-merge change failure rate. Decisions should be based on these, not vibes.

Platform-productivity · Dec 11, 2025 · 9 minute read

Code Review Automation That Doesn’t Grind Delivery to a Halt

A paved-road approach to PR checks, ownership, and merge discipline that keeps quality high and lead time low—without a bespoke Rube Goldberg machine.

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Code Review Automation That Doesn’t Grind Delivery to a Halt

Key takeaways

Implementation checklist