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Intersting.

So engineers that like to iterate and explore are more likely to like LLMs.

Whereas engineers that like have a more rigid specific process are more likely to dislike LLMs.

I frequently iterate and explore when writing code. Code gets written multiple times before being merged. Yet, I still haven't found LLMs to be helpful in that way. The author gives "autocomplete", "search", and "chat-driven programming" as 3 paradigms. I get the most out of search (though a lot of this is due to the decreasing value of Google), autocomplete is pretty weak to me especially as I macro or just use contextual complete, and I've failed miserably at chat-driven programming on every attempt. I spend more time debugging the AI than it would to debug myself. Albeit it __feels__ faster because I'm doing more typing + waiting rather than continuous thinking (but the latter has extra benefits).

FWIW I find LLMs almost useless for writing novel code. Like it can spit out a serviceable UUID generator when I need it, but try writing something with more than a layer or two of recursion and it gets confused. I turn copilot on for boilerplate and off for solving new problems.

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