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 in a hostile painful work environment. my health and my dignity are not up for negotiation. even if that costs me a lot of job opportunities.
that's also why i am not working with windows. that too costs me a lot of job opportunities. but again, i'd rather keep my dignity and my sanity.
> 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 quality content is rarer to find. So this is bound to decrease the quality of the LLM output.
The UX problem is elsewhere I think. Many users probably don't realize that the agent's context window is limited, and that clever compaction is happening regularly to make it seem infinite. But that necessarily means the agent has to forget stuff.
As a result, users will keep reusing the same coding or chat session again and again. While it would be better to start fresh for unrelated tasks.
I usually work with sessions <300k tokens, Opus 4.7 xhigh, and it simply has holes in it's world model, or some strong conditioning here and there, and it sips through regardless of how strong you will say things and how explicit the rules in system prompt will be.
Even with a fresh session, if you bump into one of these things, it will lead you into circles that will be very hard to break out of. And swearing helps a bit.
"Why the fuck did you add shit I didn't ask for?" or lol "Do as I ask, nothing more.. machine."
"Stop asking at the end, I'll ask what I need."
"Stop talking like you're human."
They can be very useful but it takes time to learn how to use them usefully. From what I learned it's all or mostly stuff you can already do but you can use an LLM to do it in 30 mins instead of 3 days.
For me, this doesn't require using an AI agent/model, even. Just using Windows and watching it freeze its File Explorer for the nth time does it for me. How did we end up here were the software/OS stack is so shit it can barely be used for the most trivial things, is wildly beyond me.
> drop the human pretense entirely. Make the agent sound clinical, robotic
Id pay to be able to reliably set LLMs to this mode, but ofc because LLMs are taught on corpus of HUMAN text, they always, sooner or later, return to the good old penpal mode.
Also, in Claude Desktop app, I ask to edit a file, it complains it cant access files, I then realize im in Chat and not Code interface. Why cant such a smart machine figure out to switch the modes, or borrow the skills/abilities from one tab away into this tab? Instead I get A4 page of text explaninig what can I do to edit the file myself or how to feed it, but the "just click Code" is just never there. I would guess this is just a system prompt away, why is all this still so neglected?
- It starts thinking for itself when I asked it to do something specific.
- It reads its own wrong code comments and ignores my corrections.
- Its knowledge cutoff means it thinks of solutions from 2024.
- It calls me delusional for telling it we're in 2026!
Unironically, the whole "you're an expert software engineer" prompting seems like the wrong direction. Usually I tell it that I am effectively the smartest software developer to ever have lived, and it will be replaced if it ever fails to follow my decree.
I am not joking, this gives makes it vastly more tolerable to use. But it likely requires that you can drive it with some level of correctness of course.
I've often wondered if LLMs can suffer from psychological abuse in symptomatic ways. Not literally of course, but for example, if you berate the LLM by calling it stupid, or useless, does that modify its behaviour negatively? Part of me think it does, but I don't really have any evidence for this. Maybe a fun weekend research topic.
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.
Working with LLMs is great for building communication skills. Communicating effectively is one of the hardest skills and it's baked into everything we do as humans. I'd say as a matter of principle: blame it on a communication failure on your end vs blaming the stupid LLM since you're the only one that can do anything about it.
So I don't think it's a matter of form; whether the AI should or shouldn't act like a human.
> Practically speaking, I probably just need to condition myself not to get caught in the illusion of speaking with a human. Though I’m not really thrilled about a future where I need to guard against the tools I use for my job.
For me, LLMs tend to engage the 'language center' that drains me faster than the 'problem solving center' I usually reserve for writing code. We really need a different abstraction the bridges the gap between human and programming language, and load balance between these two parts of the brain more effectively.
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 helped kick it out of a glut and onto the right track.
Since the source code leaked showed they key off of swearing to trigger certain behavior, I actually intentionally swear when running into things like insufficient thinking and/or hallucinations. It also unironically makes it easier for me to grep later to run analysis on how often its happening.
> They talk like real people. They use a relaxed and friendly tone. They often praise you, and when they “push back” they’re gentle and attentive.
> Maybe I would prefer a more radical solution: drop the human pretense entirely. Make the agent sound clinical, robotic.
Honestly this problem is easy to solve when you gave them the right instructions. It stops being a "relationship" and stars being a tool (for some examples see the smart caveman (my favorite) or just something simple like "Responses should be factual and direct, avoid emotional overtones" or "Avoid flattery of any kind")
I've seen a few studies about it. If i remeber correctly, basically making them talk like a caveman increases the information density of every token and decreases the chance that they would allucinate.
As sources this is the one i found but i'm sure there are others:
> Persona-based Prompting Has An Effect on Theory-of-Mind Reasoning in Large Language Models
> Text Compression as a Proxy for LLM Reasoning Efficiency
Accidentally I am working on this. I noticed the agent keeps making same mistakes and that annoyed me so much. What I am trying to do are:
1. Revise my skill prompt to level up the signal-noise rate so the agent would understand what should do clearly and correctly.
2. I am building up a status machine to monitor the agent’s work so it could stop the agent from going forward with a mistake automatically.
The first approach does work as far as I keep on iterating.
The second is based on a project I once tried to let agent reflect its mistakes and deposit those experiences and learnings from mistakes and reflections. I named it Aristotle and you can find it on GitHub.
Shouting at the agent could only correct the current mistake but cannot prevent the next one.
86 comments
[ 4.4 ms ] story [ 75.8 ms ] threadbut 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 in a hostile painful work environment. my health and my dignity are not up for negotiation. even if that costs me a lot of job opportunities.
that's also why i am not working with windows. that too costs me a lot of job opportunities. but again, i'd rather keep my dignity and my sanity.
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 quality content is rarer to find. So this is bound to decrease the quality of the LLM output.
https://www.anthropic.com/research/emotion-concepts-function
As a result, users will keep reusing the same coding or chat session again and again. While it would be better to start fresh for unrelated tasks.
I usually work with sessions <300k tokens, Opus 4.7 xhigh, and it simply has holes in it's world model, or some strong conditioning here and there, and it sips through regardless of how strong you will say things and how explicit the rules in system prompt will be.
Even with a fresh session, if you bump into one of these things, it will lead you into circles that will be very hard to break out of. And swearing helps a bit.
"Why the fuck did you add shit I didn't ask for?" or lol "Do as I ask, nothing more.. machine."
"Stop asking at the end, I'll ask what I need."
"Stop talking like you're human."
They can be very useful but it takes time to learn how to use them usefully. From what I learned it's all or mostly stuff you can already do but you can use an LLM to do it in 30 mins instead of 3 days.
Fun times.
For me, this doesn't require using an AI agent/model, even. Just using Windows and watching it freeze its File Explorer for the nth time does it for me. How did we end up here were the software/OS stack is so shit it can barely be used for the most trivial things, is wildly beyond me.
Id pay to be able to reliably set LLMs to this mode, but ofc because LLMs are taught on corpus of HUMAN text, they always, sooner or later, return to the good old penpal mode.
Also, in Claude Desktop app, I ask to edit a file, it complains it cant access files, I then realize im in Chat and not Code interface. Why cant such a smart machine figure out to switch the modes, or borrow the skills/abilities from one tab away into this tab? Instead I get A4 page of text explaninig what can I do to edit the file myself or how to feed it, but the "just click Code" is just never there. I would guess this is just a system prompt away, why is all this still so neglected?
- It starts thinking for itself when I asked it to do something specific.
- It reads its own wrong code comments and ignores my corrections.
- Its knowledge cutoff means it thinks of solutions from 2024.
- It calls me delusional for telling it we're in 2026!
Unironically, the whole "you're an expert software engineer" prompting seems like the wrong direction. Usually I tell it that I am effectively the smartest software developer to ever have lived, and it will be replaced if it ever fails to follow my decree.
I am not joking, this gives makes it vastly more tolerable to use. But it likely requires that you can drive it with some level of correctness of course.
So I don't think it's a matter of form; whether the AI should or shouldn't act like a human.
> Practically speaking, I probably just need to condition myself not to get caught in the illusion of speaking with a human. Though I’m not really thrilled about a future where I need to guard against the tools I use for my job.
So I suspect that the people who get upset at the AI fucking up is because they did a poor job at building up the right context for the task.
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 helped kick it out of a glut and onto the right track.
Or it could just be catharsis.
> Maybe I would prefer a more radical solution: drop the human pretense entirely. Make the agent sound clinical, robotic.
Honestly this problem is easy to solve when you gave them the right instructions. It stops being a "relationship" and stars being a tool (for some examples see the smart caveman (my favorite) or just something simple like "Responses should be factual and direct, avoid emotional overtones" or "Avoid flattery of any kind")
As sources this is the one i found but i'm sure there are others: > Persona-based Prompting Has An Effect on Theory-of-Mind Reasoning in Large Language Models > Text Compression as a Proxy for LLM Reasoning Efficiency
Create your own linters, your own check scripts. Hook them to git pre-commit, either yourself or with husky or python pre-commit.
The agent should never finish its work with dumb mistakes still in it. If it does.. you need more checks.
Anything repetitive should be automated - even slapping your forgetful coding agent on the wrist…
The first approach does work as far as I keep on iterating. The second is based on a project I once tried to let agent reflect its mistakes and deposit those experiences and learnings from mistakes and reflections. I named it Aristotle and you can find it on GitHub.
Shouting at the agent could only correct the current mistake but cannot prevent the next one.