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Comment by fzeroracer | Hacker News Reader

In a world where this entire codebase wasn't generated by ChatGPT, you'd have engineers familiar with the various parts of the system to quickly identify and fix the problem.

Testing and debugging isn't just a matter of stepping through code, it's an exercise of seeing where your mental model of the codebase is faulty versus the current reality of it.

I've encountered similar problems and they'd be fixed in a matter of hours, not days.

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This is spot on, the issue is not the mistake per se but in creating a code base that the team themselves are not familiar with. With some intern or team member generated code you can sit down with them and have them walk you through the code and introduce you to their reasoning, but you can't do that with an LLM. The author even admits to just mimicking the existing structure that the LLM started with when they had to expand, which sounds like a first commit for a team member first getting familiar with some new code. Part of the benefit of being able to write your own code is that you can do it in a way that clicks for you. Hopefully this lets you debug and extend it efficiently. I don't know why someone would squander this opportunity.

> In a world where this entire codebase wasn't generated by ChatGPT, you'd have engineers familiar with the various parts of the system to quickly identify and fix the problem.

I wonder why this victim didn't ask ChatGPT to identify and fix the problem...

Yes I don't understand the perceived benefits of re-writing the code in Python/FastAPI if none of them know Python/FastAPI.

"Requirements"?

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