The Unbearable Slowness of AI Coding
I’ve been coding entirely with Claude Code for the past two months. At first it was exhilarating. I was speeding through tasks. I was committing like mad.
Now, as I’ve built up a fairly substantial app, it’s slowed to a crawl. Ironically, the app I’m building lets me parallelize many instances of Claude Code at once.
Often, I’ll have 5 instances running while I’m thinking about new features.
The slowness comes in when I actually need to review all the PRs. One by one, I have to apply them locally. One by one, I have to step through the console logs. One by one, I have to tell Claude to fix the issues it created.
Yes, it’s faster. I’m committing an incredible amount of code these days—more than I ever have.
It also feels incredibly, maddeningly slow. Once you’ve felt that first boost of speed with Claude Code, you want every coding task to feel like that. It’s addictive.
Instead, as you build, you still have to serve as Claude’s QA engineer.
Maybe one day we’ll solve that. But I’m skeptical it will be in the form of a CLAUDE.md. I can barely get Claude to consistently follow the bare set of rules I have, much less ensure it performs a complex integration test for a web app.
Until then, I’ll keep pulling PRs locally, adding more git hooks to enforce code quality, and zooming through coding tasks—only to realize ChatGPT and Claude hallucinated library features and I now have to rip out Clerk and implement GitHub OAuth from scratch.