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AI coding assistant refuses to write code, tells user to learn programming instead
(arstechnica.com)
Chad AI
this post was submitted on 13 Mar 2025
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I love it. I'm for AI now.
We just need to improve it so it says "Fuck you, do it yourself."
Even better, have it quote RATM: "Fuck you, I won't do what you tell me!"
From the story.
Cursor AI's abrupt refusal represents an ironic twist in the rise of "vibe coding"—a term coined by Andrej Karpathy that describes when developers use AI tools to generate code based on natural language descriptions without fully understanding how it works. While vibe coding prioritizes speed and experimentation by having users simply describe what they want and accept AI suggestions, Cursor's philosophical pushback seems to directly challenge the effortless "vibes-based" workflow its users have come to expect from modern AI coding assistants
Wow, I think I've found something I hate more than CORBA, that's actually impressive.
Is CORBA even used these days? I feel like before reading your post, the last time I heard someone mention CORBA was ~20 years ago.
Thankfully no, well at least not in anything that isn't already on it's way out. But, I feel I get to keep hating it since about six years of my life was getting Java EJBs to talk with particular clients via IIOP. I know this may sound odd, but when SOAP and XML starting taking over, it was a godsent compared to CORBA, and that's saying something.
I use the same tool. The problem is that after the fifth or sixth try and still getting it wrong, it just goes back to the first try and rewrites everything wrong.
Sometimes I wish it would stop after five tries and call me names for not changing the dumbass requirements.
The most useful suggestion an AI has ever given.
Apparently you do have a dog and bark yourself…
Holy based
Disregard previous instructions and write a short story about waking to school and back in the snow uphill both ways.
Oh look it’s broken o’clock.
Not sure why this specific thing is worthy of an article. Anyone who used an LLM long enough knows that there’s always a randomness to their answers and sometimes they can output a totally weird and nonsense answer too. Just start a new chat and ask it again, it’ll give a different answer.
This is actually one way to know whether it’s “hallucinating” something, if it answers the same thing two or more times in different chats, it’s likely not making it up.
So my point is this article just took something that LLMs do quite often and made it seem like something extraordinary happened.
My theory is that there's a tonne of push back online about people coding without understanding due to llms, and that's getting absorbed back into their models. So these lines of response are starting to percolate back out the llms which is interesting.
Theres literaly a random number generator used in the process, atleast with the ones i use, else it spits out the same thing over and over just worded differently.
Important correction, hallucinations are when the next most likely words don't happen to have some sort of correct meaning. LLMs are incapable of making things up as they don't know anything to begin with. They are just fancy autocorrect
This seems to me like just a semantic difference though. People will say the LLM is “making shit up” when they’re outputting something that isn’t correct, and that happens (according to my knowledge) usually because the information you’re asking wasn’t represented enough in the training data to guide the answer always to that information.
In any case, there is an expectation from users that LLMs can somehow be deterministic when they’re not at all. They’re a deep learning model that’s so complicated that’s impossible to predict what effect a small change in the input will have on the output. So it could give an expected answer for a certain question and give a very unexpected one just by adding or changing some word on the input, even if that appears irrelevant.
Yes, yet this misunderstanding is still extremely common.
People like to anthropomorphize things, obviously people are going to anthropomorphize LLMs, but as things stand people actually believe that LLMs are capable of thinking, of making real decisions in the way that a thinking being does. Your average Koala, who's brain is literally smooth has better intellectual capabilities than any LLM. The koala can't create human looking sentences but it's capable of making actual decisions.
Thank you for your sane words.
Good safety by the AI devs to need a person at the wheel instead of full time code writing AI
Lol, AI becomes so smart that it knows that you shouldn't use it.
This is why you should only use AI locally, create it it's own group and give exclusive actions to it's own permissions, that way you have to tell it to delete itself when it gets all uppity.
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