AI-powered code reviews for your Expo projects

This is a guest post from Aleks Volochnev - a seasoned technologist and passionate open source maintainer currently working in DevRel at CodeRabbit.

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Reviewing is hard. Reading someone else's code is harder than writing your own. Jumping between files, holding state in your head, asking "why did they do it?", it all takes a lot of effort, even for an excellent pull request that doesn't introduce any issues.

Reviewing was always hard, but it's gotten much worse now with the rise of LLMs. Don't get me wrong – Cursor and friends are fantastic. They do help to ship fast (which is great), but many people are pushing changes without verifying what the AI wrote (which is not). It compiles, the tests pass, and it's already 5pm. Push it.

For many teams, this means twice the pull requests, needing much stricter reviews. Did I mention reviewing is hard?

CodeRabbit is an AI code review platform that automatically reviews every pull request. You connect your repo, open a PR, and within minutes you get inline comments pointing out actual issues. Not just formatting nitpicks, but the stuff that matters.

If you're building with Expo, you're already juggling a lot: performance tuning, native modules, App Store compliance, the eternal "works in simulator but crashes on device" dance. Cross-platform means your reviewer needs to think about how every change behaves on iOS, Android, and maybe web too. Very few can keep all that in their head, and no one has enough time.

CodeRabbit gets it. It understands React Native patterns and flags things like exposed API keys, memory leaks, platform-inconsistent behavior, and race conditions. All the stuff that turns into 1-star reviews and Slack messages at 2am.

This is much more than just "hey Claude, review this diff," there’s a big infrastructure behind it. When you open a PR, CodeRabbit spins up a sandboxed environment, merges your changes there, and analyzes how the merged code affects your entire codebase. It traces code graph, runs linters, checks for breaking changes downstream, and understands how your modifications go through the system.

This matters for Expo apps. You rename a prop in one component, and suddenly three screens break on Android but not iOS. CodeRabbit traces those connections, so you find out in the PR, not in your crash logs.

It also reads linked issues – whether from GitHub or Jira – and checks if your PR actually addresses the requirements. If the issue says "add offline support" and your PR only handles the happy path, it'll point that out!

There are reviewers who leave 47 comments pointing out problems but zero suggestions on how to fix them. CodeRabbit isn't that person. For simple issues, it generates ready-to-commit fixes you can apply with one click. Literally, click a button in the PR comment, and the fix gets committed right into your feature-branch.

For complex stuff that needs multi-file changes, it generates detailed, well-crafted prompts you can feed directly to your AI coding assistant. These aren't generic "please fix this" suggestions but structured prompts that provide context, explain the issue, and guide the fix. (Honestly, I've learned a lot about prompt engineering just by reading them.) So the loop becomes: AI writes code → CodeRabbit reviews it → CodeRabbit gives you a prompt → AI fixes it. Robots all the way down.

CodeRabbit runs security scanners automatically and uses their output to strengthen vulnerability checks. There are dozens of them, here's what matters most for your project:

Gitleaks catches exposed API keys. This is huge for mobile. Your app bundle ships to users' devices and can be reverse-engineered. That hardcoded Firebase key? Someone will find it. CodeRabbit flags it before you ship.

OSV Scanner checks your dependencies for known vulnerabilities. Unlike web apps, you can't just push a hotfix when a supply chain attack hits. Users have to update through the App Store. Better to catch it early enough.

It gets the most interesting when it gets to Learning. CodeRabbit learns from your team's patterns and feedback. Tell it "we prefer functional components" or "ignore this pattern, it's intentional" – and it remembers. The reviews get smarter over time.

And right in the PR comments, you can just ask it to do things! "@coderabbitai fix this memory leak" or "@coderabbitai add tests for this function." It'll make the changes right there in the PR. It's like having a very patient, very fast teammate who never gets tired of your requests, day or night.

Setup takes just a few minutes. Install the GitHub/GitLab app, pick your repos, and your next PR gets reviewed automatically. We've put together a demo repository with example PRs showing the kinds of issues CodeRabbit catches in Expo projects. Clone it, open a PR, and see what happens.

For the complete installation walkthrough, check out our tutorial on configuring CodeRabbit for Expo projects:

Oh, and if you're building open source, it's free. Seriously.

Your team is already using AI to write code faster. CodeRabbit helps you ship that code with confidence. No more "I hope this is fine 🙏". Just better code, reviewed in minutes.

Give it a try. Your future self (the one not debugging an App Store rejection) will thank you.