What Makes Great Code? Reviewing PRs with AI

When reviewing pull requests, you’re not just looking for syntax correctness, you’re evaluating readability, maintainability, performance, and how well the change fits your team’s style. In today’s fast-paced development cycles, relying solely on human reviewers can slow things to a crawl. Enter AI reviewers that think like senior engineers, giving you deep, context-aware feedback on every PR.

In this article, we’ll discuss what makes “great code,” why code review matters more than ever, and how AI is helping teams deliver cleaner, safer, and more collaborative PRs with tools like Greptile, which help you hit those high standards consistently.

Clarity: Code That Reads Like a Story

Great code should be self-explanatory. Clear variable names, intuitive function signatures, and well-defined module boundaries help readers grasp logic quickly without cross-referencing multiple files.

• Descriptive Naming: Prefer descriptive names like calculateMonthlyInterest(principal, rate) over vague ones like calc(a, b).
• Logical Structure: Group related functions together and ensure helper methods reside in appropriate modules.
• Minimal Surprises: Functions like getUser() shouldn’t cause unexpected side effects, such as database writes—clearly name functions that handle side effects (e.g., saveUser()).

AI’s Role: Greptile analyzes your entire repository, recommending improvements to naming consistency or suggesting better file structures, ensuring clarity throughout your codebase.

Consistency: Upholding Team Conventions

Manual enforcement of style guides and conventions is tedious and error-prone. AI reinforces standards efficiently and reliably:

• Formatting Rules: Maintain consistent coding styles (e.g., tabs vs. spaces, semicolon usage).
• Error Handling: Consistently handle errors in promise-based or asynchronous code.
• Directory Structure: Clearly organize your files—API routes in /api, UI components in /components, and utilities in /utils.

AI’s Role: Unlike static linters, AI tools such as Greptile learn your project's specific conventions, identifying inconsistencies such as missing error handling in async controllers, adapting to your team's unique patterns.

Efficiency: Avoiding Performance Issues

Writing functional code is baseline—writing performant code is excellence:

• Algorithm Selection: Replace inefficient O(n²) operations with optimized approaches like hash maps or built-in functions.
• Resource Optimization: Use streams instead of large file buffers; utilize connection pooling.
• Lazy Loading: Load resources only when necessary, avoiding large bundled payloads.

AI’s Role: Greptile detects performance antipatterns, such as inefficient nested loops, and recommends optimized coding practices by referencing similar fixes from previous PRs.

Testability: Facilitating Verification

Robust testing is crucial. Excellent code is:

• Isolated: Small, pure functions simplify unit testing.
• Mock-friendly: Dependency injection supports effective mocking.
• Explicit Edge Cases: Clearly define and test boundary conditions and error paths.

AI’s Role: Greptile identifies functions lacking tests, especially newly introduced ones, and suggests adding test scaffolding or mocks, pointing developers to existing test patterns within the repository.

Security: Preventing Vulnerabilities

A single vulnerability can negate months of development effort. Secure coding practices include:

• Input Validation: Sanitize or validate external inputs.
• Least Privilege: Limit service and user permissions.
• Secure Secrets Management: Store API keys securely, never in code.

AI’s Role: Greptile integrates security checks, highlighting risky practices such as raw database queries, and provides secure alternatives already established in your codebase.

Integration: Assessing Broader Impacts

Great reviewers consider ripple effects. Small changes in shared utilities can impact multiple areas:

• Dependency Graphs: Identify modules affected by changes.
• Versioning Awareness: Review all affected components for compatibility when dependencies change.
• Migration Strategies: Plan transitional strategies for large refactors to avoid breaking consumers.

AI’s Role: Greptile visualizes dependency impacts, guiding you through affected modules and recommending migration strategies or backward-compatible approaches when necessary.

Collaboration: Supporting Developer Growth

Ultimately, great code reviews empower people, not just improve code:

• Constructive Feedback: Suggest improvements clearly and positively.
• Contextual References: Provide helpful examples and links.
• Acknowledging Good Practices: Highlight quality work, reinforcing good coding habits.

AI’s Role: Greptile supports collaborative feedback by prefacing suggestions with praise, linking to relevant documentation, and enhancing learning opportunities.

Conclusion

Blending human expertise with AI-driven consistency ensures every pull request meets the highest standards in clarity, consistency, efficiency, testability, security, integration, and collaboration.

Greptile doesn't replace senior engineers; it enhances their capabilities, handling routine checks and extensive impact analyses, allowing your team to focus on architecture and mentorship. This combination defines truly exceptional code in 2025.

Ready to enhance your code review process? Give Greptile a try and turn each pull request into an opportunity for learning, improvement, and faster delivery.