Overview

A self-sufficient AI agent capable of acting like a software engineer.

This project was created to explore building a self-sufficient AI agent capable of acting like a software engineer. Inspired by Jerry Li, who led efforts in developing a SWE AI agent, I decided to prototype a smaller-scale version by automating GitHub pull requests and integrating the agent into existing CI/CD pipelines. This was also inspired by CodeRabbit — I created this project to understand what happens under the hood, with my attempt to reverse-engineer how these AI review systems work.

Why

Automating repetitive tasks like code reviews and PR checks can significantly increase developer productivity.

As software teams grow and engineering workflows become more complex, automating repetitive tasks like code reviews, PR checks, and formatting can significantly increase developer productivity and reduce bottlenecks. This project addresses the need for intelligent automation in modern development pipelines. By integrating an AI agent into GitHub and CI/CD workflows, I aimed to demonstrate how such agents can accelerate code review processes, enforce consistent coding standards, and reduce manual overhead.

How It Works

The agent listens for PR events, reviews changes, summarizes them, notifies your team, and merges automatically.

The system includes a REST API integrated with the GitHub API, configured to listen for pull request events on specified repositories. When a pull request is opened, the AI agent automatically reviews the changes, generates a summary of what the PR entails, and sends a notification to either Slack or Discord based on the user's preferred platform. After notifying the user, the agent attempts to intelligently validate the changes and, if all checks pass, proceeds to merge the PR into the dev branch — streamlining the review and deployment pipeline.