@freddy It's not about the hardness of the puzzle.
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@freddy It's not about the hardness of the puzzle. I don't think I'm even that skilled at solving hard puzzles.
I like things like "if-else" constructs. I like how when I see one, I know what it does.
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@sunfish @freddy I wonder if it's just a matter of taste and personal interest, or if part of it is you understanding that good software requires people who understand how the software is written and how it works. Generating or modifying the software with AI creates an understanding debt that could be fatal to the software long-term (or medium-term, really).
So if your personal satisfaction relies on doing a good job, avoiding AI might be a good instinct.
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Florens Verscheldereplied to Florens Verschelde last edited by
@sunfish @freddy See @baldur on how building and maintaining software requires building a theory of how the software works: https://www.baldurbjarnason.com/2022/theory-building/
Could be that AI code generators are not a big threat to this theory-building, but on the surface it does sound like shipping code that no-one has more than a fuzzy understanding of. I’ll wait for research showing that this downside is manageable and not too costly before jumping on that bandwagon.
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@gunchleoc @fvsch @sunfish "AI can only suggest things that have frequently been solved before. It cannot solve new problems."
Exactly. Because it's not actually "I" (as in intelligent).
It's "C." As in AutoComplete.
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@quixote @gunchleoc @fvsch @sunfish
And that's why I don't use stuff like copilot because I get frustrated by autocomplete as it is half the time when it does something I don't want it to.
Autocomplete is ok when writing new code but as soon as your making modifications to existing code it ends up inserting extra characters where they don't belong and just being a nuisance. -
@gunchleoc @fvsch @sunfish @freddy @baldur yep, the "smart code completion" JetBrains supply is right about half the time and that can save a bit of typing. But it doesn't replace the thinking.
Bigger snippets of AI code end up creating work because first you have to do a very detailed review, then you can run a static analysis tool over it, then you start writing tests, and those tests have to be unusually thorough because AI makes mistakes that people don't.