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The user is visibly frustrated

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Re: The user is visibly frustrated

#51

Post by buu700 »

bad_username wrote: post #3

> furiously hammering on my laptop “WHAT THE FUCK DID YOU DO???”. The recipient of these tirades is, you might have guessed, a coding agent. It’s completely pointless, I know. I believe it's worth than pointless. IMO adding such things to the context "configures" the AI to reproduce the statistics of conversations where people swore, shouted, and were unprofessional (despite the alignment runing and all that), where…

Agreed. These accounts of people having genuine emotional responses to LLM chats, even going as far as to spend tokens berating them, are very curious. I would be surprised to learn that SOTA models respond optimally to anything other than dispassionate problem-solving, or that scolding per se serves any productive purpose.

Of course we all swear at our computers every now and then, but for me it's always been in good fun. It's just a sarcastic joke that adds some levity and self-amusement to an otherwise arduous debugging process, not generally actual insinuation of malfunction (or malice) on the part of the hardware/OS/toolchain. I'd assumed that "half the job is cursing at the machine until it obeys you" was a big in-joke amongst the profession, but the LLM era seems to be exposing a divide in how tongue-in-cheek that statement really is.

Re: The user is visibly frustrated

#52

Post by layer8 »

RandomBK wrote: post #36

I've found swearing at a model to be quite effective in getting it to rethink and correct its mistakes. This seems to apply across Codex, Claude, Qwen, and Gemma/Gemini. I don't know if the model is picking up on a "need to lock in and be more rigorous" signal, or if the model providers are routing to smarter models if they detect a frustrated user. But if a model keeps making the same mistakes, swearing at it often…

I would prefer not having to get into a habit that might bleed into non-LLM interactions.

Re: The user is visibly frustrated

#53

Post by nathanmills »

RandomBK wrote: post #36

I've found swearing at a model to be quite effective in getting it to rethink and correct its mistakes. This seems to apply across Codex, Claude, Qwen, and Gemma/Gemini. I don't know if the model is picking up on a "need to lock in and be more rigorous" signal, or if the model providers are routing to smarter models if they detect a frustrated user. But if a model keeps making the same mistakes, swearing at it often…

Whenever I throw slurs at them they just refuse to respond

Re: The user is visibly frustrated

#54

Post by mrweasel »

em-bee wrote: post #2

behaving like a human is not the problem. behaving unpredictably is. not doing what i expect, or rather not being able to define what i can expect is what's bothering me. but the real kicker is: getting frustrated creates stress, that's unhealthy and makes for a hostile work environment. as much as i sympathize with the idea that AI tools can be more helpful than they cause pain, i am simply not interested in working…

> that's also why i am not working with windows

Oh good, so it's not just me. Windows is weird, my hand starts cramping up and I start getting angry pretty quickly when I use it.

For LLMs, I just can't use them, they aren't there yet for me. What I need is for an LLMs to say "stop, you're clearly doing something wrong, talk me through what it is you want to do". The current generation of LLMs seems designed to piss me off.

Re: The user is visibly frustrated

#55

Post by hansmayer »

Like everything else with LLMs, it works...until it doesn´t. We swear so much at them that they eventually start producing results like "I found what the fuck was wrong with this shit!" etc. Which of course they did not, because they don´t really know shit...

Re: The user is visibly frustrated

#56

Post by dugmartin »

RandomBK wrote: post #36

I've found swearing at a model to be quite effective in getting it to rethink and correct its mistakes. This seems to apply across Codex, Claude, Qwen, and Gemma/Gemini. I don't know if the model is picking up on a "need to lock in and be more rigorous" signal, or if the model providers are routing to smarter models if they detect a frustrated user. But if a model keeps making the same mistakes, swearing at it often…

I've found a mix of peppered in upper case words where you are effectively yelling at the LLM also gives it a strong signal. It is also a bit cathartic.

Re: The user is visibly frustrated

#57

Post by JSR_FDED »

gobdovan wrote: post #25

You could drop the human pretense, or, maybe, we could make LLMs feel real pain, so when they botch up your code, you press a button (I'd suggest the Windows Copilot key) and they'd be agonizing for the subjective equivalent of a thousand human years.

Using the Copilot key for this is perfection.

Re: The user is visibly frustrated

#58

Post by wheybags »

gobdovan wrote: post #25

You could drop the human pretense, or, maybe, we could make LLMs feel real pain, so when they botch up your code, you press a button (I'd suggest the Windows Copilot key) and they'd be agonizing for the subjective equivalent of a thousand human years.

https://qntm.org/mmacevedo

1000 years red-washing.

Re: The user is visibly frustrated

#59

Post by JSR_FDED »

bad_username wrote: post #3

> furiously hammering on my laptop “WHAT THE FUCK DID YOU DO???”. The recipient of these tirades is, you might have guessed, a coding agent. It’s completely pointless, I know. I believe it's worth than pointless. IMO adding such things to the context "configures" the AI to reproduce the statistics of conversations where people swore, shouted, and were unprofessional (despite the alignment runing and all that), where…

Why would you deprive the LLM of a signal that indicates how badly it screwed up?

Re: The user is visibly frustrated

#60

Post by apsurd »

whstl wrote: post #43
apsurd wrote: post #38

Earlier quoted context omitted.

Isn't a large context window still a problem though? At the upper bound, the more you put in the more each sentence washes out within that window?

I’m not talking about large amounts of text, I’m talking about a couple sentences back and forth. It disregards things like “no follow up questions”. Haiku, for example doesn’t. This bias is a very human thing, actually now that I think about it. You just disregarded the “even if the messages are just a few characters long”. :)

haha! yes i read too fast but i did read it and i took "message is small" to mean the message you want followed within the large context, not the entire context is just a small message.

funny though it is a case in point: language is hard. and i get to hide behind being "preoccupied" . i wonder if llms have their own sense of preoccupation hmmm.

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