Code reviews catch bugs, but they also teach. Here's how I use Claude Code to make both processes more effective.
The Pre-Review Checklist
Before pushing code for human review, I run it through Claude Code with specific prompts.
1. Logic Verification
"Walk through this function step by step. What are the edge cases I haven't handled?"
This catches the obvious gaps before a colleague has to.
2. Security Scan
"Review this code for common security vulnerabilities: SQL injection, XSS, improper authentication, exposed secrets."
Not a replacement for proper security tools, but catches low-hanging fruit.
3. Performance Questions
"Where are the potential performance bottlenecks in this code? Are there any O(n²) operations hidden in loops?"
4. Readability Check
"If a new developer joined the team tomorrow, what parts of this code would confuse them?"
This question surfaces naming issues, missing comments, and overly clever solutions.
5. Test Coverage
"What test cases would you write for this function? What boundary conditions should I cover?"
The Post-Review Learning Loop
After receiving feedback from human reviewers, I share the comments with Claude Code:
"My colleague suggested [feedback]. Can you explain why this approach is better and show me an example?"
This transforms review comments into learning opportunities.
What Claude Code Won't Catch
Domain-specific logic errors. Business requirement misalignment. Team conventions that aren't codified. Always pair AI review with human review.
At Logic Leap, we believe in augmenting human expertise with AI tools—not replacing it. Need help building effective code review processes? Let's talk.
What's your code review workflow?
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