Comment by moezd | Hacker News Reader

Comment by moezd | Hacker News Reader

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AI assisted code can't even stick to the API documentation, especially if the data structures are not consistent and have evolved over time. You would see Claude literally pulling function after function from thin air, desperately trying to fulfill your complicated business logic and even when it's complete, it doesn't look neat at all. Yes, it will have test coverage, but one more feature request will probably break the back of the camel. And if you raise that PR to the rest of your team, good luck trying to summarise it all to your colleagues.

However if you just have an easy project, or a greenfield project, or don't care about who's going to maintain that stuff in 6 months, sure, go all in with AI.

I definitely wonder if the people going all-in on AI harnessing are working on greenfield projects, because it seems overwhelming to try to get that set up on a brownfield codebase where the patterns aren't consistent and the code quality is mixed.

So just iterate on it? Your complaint is that the model isn't one shotting the problem and reading your mind about style. It's like any coding workflow, make it work, then make it nice.

No, I never expect AI to one-shot (if I see such a miracle, it's usually because I needed a one-liner or something really simple and well documented, which I can also write on the whiteboard from memory).

Try iterating over well known APIs where the response payloads are already gigantic JSONs, there are multiple ways to get certain data and they are all inconsistent and Claude spits out function after function, laying waste to your codebase. I found no amount of style guideline documents to resolve this issue.

I'd rather read the documentation myself and write the code by hand rather than reviewing for the umpteenth time when Claude splits these new functions between e.g. __init__.py and main.py and god knows where, mixing business logic with plumbing and transport layers as an art form. God it was atrocious during the first few months of FastMCP.

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