Code Reviews: Why They Matter

Introduction

Over the years, I’ve reviewed a lot of code — from junior developers’ first PRs to AI-generated bug fixes. I’ve seen code reviews save weeks of future debugging, and I’ve seen them miss the one line that caused a production issue. This series highlights the areas I pay the most attention to when helping teams set up or improve their code review process.

Code review can be many things: a quality gate, a chore, a box to tick, or a mission to ensure code meets your standards. But at its core, it’s nothing more than the four-eyes principle. When used well, it helps ensure consistency across a codebase and creates opportunities to learn — both for the reviewer and the author.

With the current wave of AI tooling, strong review skills are becoming even more important. The fundamentals haven’t changed: code still needs to be readable, testable, and suitable for long-term use. Review is where human judgment steps in — especially to assess clarity, intent, and whether a change truly belongs.

When AI writes the code, the developer’s role shifts: it’s now more about specifying requirements upfront and reviewing the output carefully. This can be surprisingly challenging — see the SmartBear article in the “Further Reading” section for some thoughts on why.

Read More in This Series

🔎 My key points for code reviews
What I personally check in a PR, and why. Includes practical examples and team strategies like limiting comment threads and encouraging questions.

🛠 Let the Tools Do Their Job
Formatters, linters, analyzers — what should be automated, what shouldn’t, and how to set up a useful baseline (with examples for .NET and TypeScript).

🚫 Zero Warnings: Signals, Not Noise
Warnings exist for a reason — I explain how and why I enforce a no-warnings policy and how teams can handle exceptions properly.

👓 Different Roles, Different Review Goals
How architects, leads, and juniors each bring a different perspective — and why that diversity is a strength when reviewing well.

🔍 Code Review as a Skill: For People and for AI
AI can write code — but only review ensures it does the right thing. Why review skills are evolving, not disappearing.

Further Reading: How Do Others Approach Code Review?

The practices in this serries reflect my personal approach — shaped by years of working across teams, mentoring developers, and watching both subtle bugs and poor handovers emerge from unclear code. It doesn’t cover everything, but it highlights what I’ve found matters most.

There are many ways to do code review well. The resources below represent thoughtful perspectives from well-known organizations. They may differ in process, tone, or focus — and that’s the point. If you’re refining your team’s process, it helps to compare several approaches.

• Microsoft .NET Design Guidelines
  Not a code review guide per se, but relevant when assessing whether changes fit .NET idioms. If you’re reviewing C# code, this is a useful baseline for naming, layout, and general design patterns.
• Google Engineering Practices – Code Review Guide
  Still one of the most referenced review guides. Its real value is not just in technical advice, but in how it handles team dynamics, reviewer responsibility, and disagreements. A must-read for anyone involved in long-term code collaboration.
• SmartBear – Peer Code Review Best Practices
  Focused on practical concerns like time limits, frequency, and batching reviews. Helpful if you’re looking to increase review efficiency while keeping quality high.
• Palantir – Code Review Best Practices
  A comprehensive, experience-based article. Covers the why of code reviews, includes a sample checklist, and offers tips for both reviewers and authors. Balances process and developer mindset well.
• Mozilla Firefox – Code Review Checklist
  A practical checklist used in the Firefox codebase. Especially useful for open-source or multi-contributor teams where clarity and consistency are crucial.