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My experience is very similar.

For greenfield side projects and self contained tasks LLMs deeply impress me. But my day job is maintaining messy legacy code which breaks because of weird interactions across a large codebase. LLMs are worse than useless for this. It takes a mental model of how different parts of the codebase interact to work successfully and they just don't do that.

People talk about automating code review but the bugs I worry about can't be understood by an LLM. I don't need more comments based on surface level patter recognition, I need someone who deeply understands the threading model of the app to point out the subtle race condition in my code.

Tests, however, are self-contained and lower stakes, so it can certainly save time there.



Legacy code, files with thousands of lines, lack of separation of concern... When I feed that to an LLM it says something like:

function bar() { // Add the rest of your code here }

And barely manages to grasp what's going on.




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