alt Hacker NewsI have long felt like "out of the box", I really dislike gpt's coding style. It seems really verbose and likely to write way too much error handling and wordy comments and worse at finding existing functionality to reuse rather than writing everything from scratch. This has been relatively easy to mitigate with prompting, but I still find it annoying.
YMMV I guess!
I think you could be right. I do use excessive error-handling code and verbose comments — that's true.
But most of my time is spent on delivery, and the biggest problem with delivery is that if a bug occurs during runtime, the client curses me out. So to me, GPT code feels meticulous.
Open source contributors might be different. Most of them write code after long periods of deliberation. They take their brightest ideas and put them into open source. Those pieces of code are probably the best answers those programmers can give.
But for someone like me, who works primarily on delivery, we mostly plug in proven patterns and focus on getting things done. 'It works' and 'it's beautiful' are different terms, after all. In that sense, I highly value the meticulousness of GPT code — the very thing you called verbose. Because even if it's inefficient, at least it runs, and it catches and wraps around far more of the parts where things break.
Given a month, I could probably write code at GPT's level, at least to some degree. The problem is the difference between one hour and one month. At its core, AI code is still based on training data.