AI Code Analysis
Submitted code is analyzed and returned with structured feedback.
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AI Code ReviewApp
A full-stack developer tool that analyzes source code and provides structured AI-generated feedback, improvement suggestions and review history.
AI
Code analysis
Full Stack
Application type
JWT
Authentication
10
Free AI reviews
Project overview
An AI assistant for reviewing source code
The product helps developers identify code issues and improvement opportunities through structured AI feedback.
AI Code Review App is a full-stack developer tool that allows users to submit source code and receive AI-generated review feedback.
The application organizes feedback into a readable interface and stores previous reviews so users can return to earlier results.
It includes authentication, usage limits, review history, account settings and a structured backend service connected to an AI provider.
My contribution
Full product implementation
Designing the dashboard and review experience
Building the React and TypeScript frontend
Creating Node.js and Express backend endpoints
Implementing JWT authentication
Integrating the OpenAI API
Adding usage-limit logic
Deploying frontend and backend services
Problem and solution
Making code feedback faster and easier to understand
Developers often need a second perspective on code quality, structure and maintainability.
01
The problem
Manual code review can be slow and unavailable for individual developers
- Developers may not always have an available reviewer
- Small issues can be overlooked during implementation
- Unstructured feedback can be difficult to act on
- Previous reviews may become difficult to track
- AI usage requires limits and error handling
02
The solution
A structured AI review workflow with saved history
Code submission through a dedicated review interface
AI-generated feedback and improvement suggestions
Authenticated user accounts
Saved review history
Usage tracking and free-review limits
Core functionality
Features designed for developer productivity
The product combines AI analysis with account and history management.
Secure Authentication
Users can register and sign in through a JWT-based authentication flow.
Review History
Previous AI reviews are stored and available through the user dashboard.
Usage Limits
Free users receive a limited number of AI-powered reviews.
Settings and Upgrade
Dedicated pages support account settings and future subscription plans.
Responsive Dashboard
The application remains usable across desktop and smaller screens.
Technology stack
A secure AI-enabled full-stack application
The stack connects a responsive frontend with authenticated APIs and an external AI service.
Frontend
ReactTypeScriptViteTailwind CSS
Backend
Node.jsExpress.jsTypeScriptREST API
Database & Auth
MongoDB AtlasMongooseJWTbcrypt
AI & Deployment
OpenAI APIPrompt EngineeringRenderVercel
System architecture
How a code review request is processed
Authenticated review requests move through the backend before being sent to the AI service.
Code Editor
User review request
Backend API
Validation and limits
AI Service
Code analysis
Review History
MongoDB storage
The backend verifies the user, checks the remaining review allowance, sends the code to the AI service and stores the resulting feedback for later access.
Engineering challenges
What required the most attention
AI integrations require predictable prompts, reliable responses and clear fallback behavior.
CHALLENGE 01
Producing structured AI feedback
The prompt needed to return useful review sections instead of unpredictable free-form text.
CHALLENGE 02
Tracking free usage limits
The backend needed to associate AI usage with authenticated users and prevent unlimited free requests.
CHALLENGE 03
Handling AI failures
The interface needed appropriate error states when the AI service was unavailable or returned an invalid response.
CHALLENGE 04
Securing review history
Users must only be able to access reviews associated with their own accounts.
Key learnings
What the AI Code Review App taught me
The project strengthened my ability to integrate AI into a user-facing full-stack product.
Designing prompts for structured technical feedback
Integrating an external AI API with Node.js
Building authenticated full-stack workflows
Tracking usage limits in a database
Creating review history and account pages
Handling AI response and network errors
Separating frontend, backend and service responsibilities
Deploying an AI-enabled application
Project gallery
A closer look at the review workflow
Screenshots from the dashboard, code submission and AI feedback experience.
Explore the application
See how AI can support developer workflows
Try the deployed product, inspect the repository or explore my other AI projects.