The code I check in at work is nearly all hand-written. I'll often send files and functions and snippets and questions and `git diff`'s to an LLM. In particular the code review is very helpful for catching silly mistakes. But if it generates code, even if it looks fine, I always end up manually moving it around and rewriting and renaming things. I need to understand the code I maintain, and those "prosaic" changes and refactorings that I do while incorporating the code help ground me deeply in how it works.
Also, I'm mostly not very happy with the architectural choices the LLM makes. It can be good at little details, and sometimes I learn about language features or idioms or libraries by reading its code, but I find it often uses wrong patterns. E.g. just this week I saw it creating two huge intermediate data structures for parsing something in a "cleaner" way, completely missing how the library it had suggested actually had something builtin (and prominently featured in the tutorial) that obviated the need for those intermediate structures and was both safer and more readable.
When I've tried full agent coding, I kept getting distracted while waiting. I also have the feeling that my questions to the LLM were getting "dumber" as I lost contact with the code. And I don't have the hardware for local LLM's, so giving full repo access is out of the question for work.
Altogether I feel like I've found a fairly good balance in how to use them in such a way that I can avoid a lot of the downsides and still have a tool that gives me much value that I didn't have before: I check in fewer bugs, I waste less time picking libraries/methods, I have a better rubber duck, I learn little tricks all the time, I never send LLM-generated text to humans.
I tried fd but it seems to ignore so much that it's basically useless. If I wanted `git ls-files|grep` I would `git ls-files|grep`
yells at cloud
..it's probably ok actually and I should give it a real go, but I'm too used to find and even have a keybinding in my ~/.inputrc to insert a find + where loop
"\e\C-f": "find . -type f -print0|while read -rd '' f; do ; done\e-b\C-b\C-b\C-b\C-b\C-b\C-b"
(yes I know about -exec; I find the loop easier to work with)
That's what I tend to do, but since foldr/foldl' is so ubiquitous in Haskell it would be nice if I could just remember the argument order of the callback. kccqzy's explanation (in particular "it replaces the comma") might just help me do that :)
depends on the product and when its applied.
for potatoes sprout inhibitors, the old product you definitely needed to remove the skin and every touched part. For the new stuff (i think its ethylène or something like that), washing it is enough (so you can now eat potato skin in europe). I would still wash my fruits just because of the transport though.
One the one hand, it does sound like one of those movies.
On the other, Idiocracy turned out to be quite prescient.
(Most likely, we'll have some combination of human stupidity, LLM stupidity, and way too much compute in one place all working together to create a perfect storm of unchecked hacks that break something or other that ends up killing people in an unintended way. Then there's some half-hearted attempt at cleaning things up so that business can proceed as usual in an even more broken world, rinse and repeat.)
Not saying that the current civilizations will never end or be shattered to pieces. Looking at history, many civilizations did. But saying LLMs are the highest risk factor for this is just insanity, based on all what we have seen so far (and based on these AI companies crying wolf, I mean, remember just a few months ago that Anthropic saying that Fable is too powerful to be released?)
Oh, I agree. I don't think LLMs will end civilization. I'm guessing climate change will cause many more deaths than LLMs. But I think LLMs will cause some too. (And not in one of those impressively smart ways as it's presented from the OpenAI fearmongers, just in a stupid "we vibe-coded the sandbox for our bruteforce SCADA-hacking agent experiment and oh no it did what we told it to do" way.)
Also, I'm mostly not very happy with the architectural choices the LLM makes. It can be good at little details, and sometimes I learn about language features or idioms or libraries by reading its code, but I find it often uses wrong patterns. E.g. just this week I saw it creating two huge intermediate data structures for parsing something in a "cleaner" way, completely missing how the library it had suggested actually had something builtin (and prominently featured in the tutorial) that obviated the need for those intermediate structures and was both safer and more readable.
When I've tried full agent coding, I kept getting distracted while waiting. I also have the feeling that my questions to the LLM were getting "dumber" as I lost contact with the code. And I don't have the hardware for local LLM's, so giving full repo access is out of the question for work.
Altogether I feel like I've found a fairly good balance in how to use them in such a way that I can avoid a lot of the downsides and still have a tool that gives me much value that I didn't have before: I check in fewer bugs, I waste less time picking libraries/methods, I have a better rubber duck, I learn little tricks all the time, I never send LLM-generated text to humans.
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