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Inspiration

AI coding tools like GitHub Copilot and ChatGPT have made software development faster than ever. However, they also introduce a new challenge: developers often use AI-generated code without fully understanding how it works. While building projects ourselves, we noticed that understanding large repositories—especially those with AI-generated code—can be difficult. Developers often struggle to see how components connect, why certain decisions were made, or where potential bugs might exist. This inspired us to create RepoIQ — Your Personal AI Code Teacher, a tool designed to help developers understand their codebases instead of just generating code.

What It Does

RepoIQ is an AI-powered repository analysis platform. Users paste a GitHub repository URL, and the system scans the project to generate a structured learning report. RepoIQ identifies:

Key architectural components

Important programming concepts used in the project

Relationships between files and modules

Potential bugs or risky implementations

A personalized learning path for the developer

Instead of generic explanations, RepoIQ provides context-aware insights based on the actual repository.

How We Built It

The frontend was built using React, TypeScript, and Next.js to create a clean dashboard interface.

The backend processes repositories through a pipeline that:

Clones and scans the repository

Indexes functions, classes, and dependencies

Maps architecture and module relationships

Uses AI to generate explanations and detect issues

Produces a learning report for the user

For scalability, we used Amazon Web Services services like AWS Lambda, Amazon S3, Amazon DynamoDB, and Amazon API Gateway.

Challenges

Handling large repositories with many files and dependencies was a major challenge. AI models also have context limits, making it difficult to analyze entire codebases at once.

To solve this, we created a structured indexing pipeline that extracts key code elements before sending them for AI analysis.

Accomplishments

We successfully built a working prototype that can analyze repositories and generate meaningful insights about their architecture and concepts.

RepoIQ demonstrates how AI can be used not just to write code, but to help developers learn and understand software systems.

What’s Next

Future plans include:

A Visual Studio Code extension

Interactive architecture visualizations

Deeper bug detection and performance insights

Personalized learning recommendations

Support for more programming languages

Our vision is to make RepoIQ an AI learning companion for developers, helping them move from simply using AI-generated code to truly understanding it.