The Importance of Code Reviews in the Software Development Lifecycle

Bad code doesn’t show up overnight. It’s the result of a broken code review culture. It’s the result of months or years of speed over quality. And no, focusing on small things like, “Move this hardcoded string to a constant,” isn’t enough. Code reviews should be where growth happens: • Refactor for clarity. • Catch edge cases early. • Challenge design decisions. • Improve tests, not just add them. • Reinforce clean principles like DRY. When done right, code reviews improve not just the code but the entire team. Thoughts?

"The purpose of code review is building, learning, and teaching." Not blaming. But let’s be honest, time gets in the way. You’ve got features to ship, bugs to fix, meetings to sit through... and suddenly that PR review becomes a checkbox. It’s not that we don’t care. It’s that thoughtful reviews take time. • Time to understand the context. • Time to catch subtle issues. • Time to give feedback that actually helps That’s where CodeRabbit comes in. It shows up in your PRs with helpful suggestions, not just “what’s wrong,” but why it might matter. It handles the small stuff, the things that slow you down but still matter: • Formatting issues and style nits • Unused variables or unreachable code • Risky patterns (unhandled nulls or hardcoded secrets) • Missed test coverage • Subtle bugs that hide in plain sight So you can focus on the big stuff: 1. Architecture decisions 2. Business logic 3. Mentorship 4. Asking the right “what if” questions It keeps the review process moving without turning it into a blame game. Because good feedback builds better teams.

Code reviews are critical to an engineering team If you want to assess the health of an eng org The quickest way is look at the most recent Pull Requests (PRs) Over the last 7+ years, I became a better leader Just by leaning into and learning from my orgs’ PR review processes I learned that a healthy engineering org nails these 5 PR components : → Reviewers suggest inline code changes → PRs are reviewed quickly, < 24 hours is ideal → PR sizes are relatively small < 100 changes → Teams use a simple and fun emoji guide to share their feedback → Multiple teammates offer respectful feedback, not just the primary reviewer More recently I have been exploring AI-powering our PRs Both to speed up the review process, and also to improve the quality Modern AI tooling is able to provide some advantage like: 1. Stacked PRs: Allows developers to build upon open PRs without waiting for them to merge 2. Automated PR descriptions: Generates detailed explanations of changes automatically 3. CI failure analysis: Summarizes and even generates fixes for failing CI I am doing POCs with tools like: - Graphite.dev - reviewable.com - LinearB's gitstream & WorkerB framework to take over PR review process to the next level What are your current gaps with your own PR review process?