Combining Claude Code with GitHub Actions and Pull Requests to Scale AI Coding

My initial experiments with letting Claude add features to my app using GitHub Actions and GitHub Pull Requests

The GitHub integration stands out as one of Claude Code's most powerful features. There are many exciting aspects of it, but what I'm most excited about is the ability to have dozens of agents running in isolated environments and adding features to your codebase, all in the extremely well-documented and battle-tested toolset of GitHub Actions.

GitHub Actions provide isolated container environments for each agent, which means Claude Code can work on multiple features simultaneously without agents stepping on each other.

Code Review, Linting, and Testing

Before diving into the scaling potential, there are some immediate wins from this integration. For example, very often when you make a new code change, it fails “linting” (static code analysis tool that catches bugs and style issues). Now, you can forget worrying about fixing those issues and just ask Claude to fix it for you after you’re done, eliminating the 10-15 minute cycle of fixing linting errors, running tests, and checking results.

Something I found even more frustrating during code review were minor style issues that modern linting tools weren’t quite sophisticated enough to catch, but that a code reviewer felt strongly about. In this case, you have to manually read the code review comments, fix the issues, and test everything again, which can be a huge time drain. Now Claude can handle all of that for you in the background so you can focus on more important work.

Scaling Feature Development

A former colleague has been chatting to me about the topic of scaling coding AI agents quite a bit using sketch.dev. He has very positive things to say about it other than the high cost of running so many agents, but when I took a look at the product, I found the UI/UX a bit intimidating and ambiguous.

Meanwhile, GitHub Actions is extremely well-documented, battle tested, and well understood. It’s very likely that you already use GitHub Actions to run your testing and possibly your continuous deployments.

Now, by running a single command in Claude Code (/install-github-app) you can mention @Claude on your Github Issue and it will spin up a pull request in an isolated environment. This implies that if you have 20 Github Issues, you can mention @Claude on each of them and have 20 Claude agents get to work adding 20 features to your app, each in an isolated environment.

My Experience Setting Up Claude Code and Github Actions on My Project and the Value of Vercel Preview Environments

The top of this post will include a Youtube video where I walk through my experience setting up Claude Code on my Github repo, but ultimately it was just running /install-github-app and following a few OAuth steps.

This experience reinforced a key insight: AI coding agents make robust testing more critical, not less. While Claude codes incredibly fast, it still hallucinates and makes mistakes. The more you can rely on automated testing to catch these issues, the faster you can move with confidence.

Of course, Claude Code was helpful in getting a Jest integration test suite setup very quickly. But its initial pass ended up writing a lot of tests that didn’t even catch bugs I introduced, so I had to coax Claude a bit more to accomplish what I actually cared about, which is a test suite that catches app breakages. In Claude’s defense, I’ve seen plenty of human engineering teams write huge amounts of useless tests.

Once I had those tests, and I setup the /install-github-app command, it truly was as simple as creating a GitHub Issue and mentioning @Claude, and it created the feature. This is demonstrated in the video.

Additionally, besides automated testing, since I deploy to Vercel they automatically create a preview deployment of the changes Claude made. This is useful to manually check everything looks good before merging the changes, and an easy path to set up end-to-end tests on a real environment.

Conclusion, Cost / Pricing, and Looking Forward

I'm curious about the cost and scalability of running many agents simultaneously, and will learn more as I continue to use this integration. But for now I wanted to share this initial setup experience

Thanks for reading! As always happy to read comments on Substack or by replying to this email.