Design an AI-Powered Code Review System
Last updated: May 21, 2025
Quick Overview
Design a system that automatically reviews pull requests using LLMs. Cover code understanding, issue detection, comment generation, and integration with existing code review workflows.
Cursor
May 21, 20256
4
3,057 solved
Design a system that automatically reviews pull requests using LLMs. Cover code understanding, issue detection, comment generation, and integration with existing code review workflows.
Cursor could extend its AI capabilities beyond the editor into the code review workflow. This question tests your ability to design an AI system that integrates with developer workflows. The interviewer expects discussion of how to make AI review comments useful rather than noisy, and how to handle the trust and adoption challenges.
What the Interviewer Expects
- Design a pipeline that ingests PR diffs and generates meaningful review comments
- Implement noise reduction to avoid low-value or false-positive comments
- Integrate with existing Git platforms like GitHub and GitLab
- Handle codebase-specific conventions using project context
- Design a feedback loop where users rate AI comments to improve quality
Key Topics to Cover
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- How would you handle a review comment that is technically correct but stylistically wrong for the team?
- How would you prioritize which PRs to review automatically vs on-demand?
- How would you measure the impact of AI code review on code quality?
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Practice System Design ProblemsSample Answer
Requirements
Functional Requirements
- Pull Request Ingestion: The system must accept pull requests (PRs) from Git platforms like GitHub and GitLab.
- Code Understanding: Utilize LLMs to analyze code...
Capacity Estimation
To estimate capacity:
- User Base: Assume Cursor supports 100,000 developers.
- PR Submission Rate: If each developer submits an average of 0.1 PRs per day, that equals 10,000 PRs per day.
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