Lilly Tech Systems
Build an AI Code Review Tool
Build a production-ready GitHub PR reviewer powered by LLMs from scratch. This hands-on project walks you through webhook integration, diff parsing, LLM-based code analysis, automated inline comments, custom rule engines, and deploying as a GitHub App — all with full working code.
Project Build Path
Follow these lessons in order to build the complete AI code review tool step by step, or jump to any section you need.
1. Project Setup
Architecture overview, GitHub API basics, LLM integration strategy, tech stack selection, and project scaffolding with full code.
2. GitHub Webhook & PR Parsing
Set up a webhook server, receive PR events, parse unified diffs, filter files by extension, and extract changed code hunks.
3. Code Analysis with LLM
Design prompts for code review, chunk large diffs for token limits, parse structured LLM output, and handle multi-file reviews.
4. Posting Review Comments
Use the GitHub API to post inline comments on specific lines, add severity levels, format suggestions, and create review summaries.
5. Custom Rules & Config
Build a .ai-review.yml config system, create project-specific rules, implement a rule engine, and let teams customize review behavior.
6. Deploy as GitHub App
Register a GitHub App, handle installation flows, deploy to a cloud provider, set up monitoring, and go live in production.
7. Enhancements & Next Steps
Auto-fix suggestions, learning from team feedback, caching strategies, multi-language support, and frequently asked questions.
What You Will Build
By the end of this project, you will have a fully functional AI code review tool that can:
Listen to GitHub PRs
Automatically receive webhook events when pull requests are opened or updated, and extract the changed files and diffs.
Analyze Code with AI
Send code diffs to an LLM with carefully crafted prompts to identify bugs, security issues, performance problems, and style violations.
Post Inline Comments
Automatically post review comments on the exact lines where issues are found, with severity levels and suggested fixes.
Support Custom Rules
Allow teams to configure project-specific review rules via a .ai-review.yml file, controlling what gets reviewed and how.