How @francisfuzz approaches code review

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I'll be the first to confess: I love reviewing code. It's one of my favorite things to do as a developer.

Code review is where software quality lives or dies. After a decade of reviewing thousands of pull requests across GitHub, startups, and consulting engagements, I've learned that great code review isn't about catching bugs—it's about building confidence in what ships to production.

Why this matters

Every line of code that reaches your customers passes through code review. The difference between shipping with confidence and shipping with crossed fingers often comes down to how systematically your team approaches this critical gate. Poor code review processes create bottlenecks, missed issues, and team friction. Effective code review accelerates delivery while maintaining quality.

I've refined this approach across three distinct roles: as a senior engineer on GitHub's New User Experience team, as a consultant for early-stage startups, and as a senior support engineer helping teams optimize their pull request workflows. This perspective spans customer-facing features, internal tooling, and developer experience improvements.

The three-phase framework

Effective code review follows a deliberate sequence: gather context, analyze changes, validate impact. Most reviewers jump straight to the code diff, missing critical context that determines whether changes align with business objectives and technical strategy.

Phase 1: Context before code

Before examining a single line of code, I establish the strategic foundation. This prevents costly misalignment and ensures changes serve their intended purpose.

Business context questions:

Technical context questions:

This context-first approach has prevented numerous issues that would have been expensive to catch in production. When I understand the "why" behind changes, I can evaluate whether the "how" achieves the intended outcome.

Phase 2: Systematic code analysis

With context established, I examine the technical implementation through multiple lenses:

Scope and structure:

Quality and maintainability:

I use a consistent commenting system to set clear expectations:

This taxonomy helps authors prioritize their response and understand what blocks progress versus what offers optional improvement.

Phase 3: Validation and verification

The final phase ensures changes work as intended across relevant environments and edge cases.

Validation checklist:

This systematic validation has caught numerous issues that passed automated testing but failed in realistic usage scenarios.

Implementation guidelines for teams

For engineering managers:

For individual contributors:

For senior engineers:

Measuring success

Effective code review creates measurable improvements:

Teams that invest in systematic code review processes ship faster and more reliably. The upfront time investment in thorough review pays dividends in reduced debugging, support burden, and technical debt.

Looking ahead

Code review continues evolving with AI assistance, but the fundamental principles remain: understand context, analyze systematically, validate thoroughly. Tools can surface issues and suggest improvements, but human judgment about business alignment, user impact, and system architecture remains irreplaceable.

The best code review isn't about perfection—it's about confidence. When your team consistently applies these practices, you ship knowing your changes will work as intended, scale appropriately, and maintain the codebase quality that enables sustainable growth.

Special thanks

(Edited to add | June 5, 2025): thank you to my colleagues, be it in our conversations or in editorial review. Without you, this post would not be possible!