Code reviews are critical for maintaining quality, but they're time-consuming. At Strug City, we've built AI agents that handle initial reviews, catching common issues before human reviewers step in.
The Problem with Traditional Reviews
Manual code reviews suffer from inconsistency, bottlenecks, and reviewer fatigue. Critical security issues can slip through when reviewers are overwhelmed.
AI-Augmented Review Process
Our AI agents perform three types of analysis:
interface ReviewChecks {
security: SecurityAnalysis;
performance: PerformanceImpact;
style: StyleCompliance;
complexity: CodeComplexity;
tests: TestCoverage;
}1. Security Analysis
Automated scanning for SQL injection, XSS vulnerabilities, and insecure dependencies. The AI flags potential issues and suggests fixes.
2. Performance Impact
Detecting expensive operations, memory leaks, and unnecessary re-renders. The agent provides benchmarks and optimization suggestions.
3. Style and Consistency
Ensuring code follows team conventions and best practices. This includes naming, structure, and documentation standards.
AI code reviews reduced our review time by 60% while catching 40% more security issues.
The key is using AI for initial triage, not replacement. Human reviewers still make the final call, but they can focus on architecture and design rather than catching typos.