Apart from LLMs I reject the notion of the "user". Once you use that term you already lost half the battle of perceiving real people and their needs.
The user is visibly frustrated
31–40 of 288 posts
Re: The user is visibly frustrated
#32Often the problems for me come when: - 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 tha…
I find this also heavily depends on which LLM you're using. I've found chatGPT is completely awful at getting corrected, it'll double down until the cows come home. Meanwhile claude will generally adjust its behavior without too much nagging.
Re: The user is visibly frustrated
#33Often the problems for me come when: - 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 tha…
Honestly, for certain classes of problems that have changed in the last couple of years, I've had good luck just finding decent academic lit that's shown up in places like ACM recently and feeding it in when working with an agent. Does it get everything right? No, but it gets you a lot closer and I've been pleasantly surprised how well it can integrate work that post-dates it's training if you finesse it a little.
Re: The user is visibly frustrated
#34I'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.
The content of the session modifies the LLMs "behavior" (token selection) in one way or another during the session, obviously. The effects are localized to the session, they will degrade over time, they will not affect other users, and they are not permanent unless someone decides to finetune the model based on your unproductive interactions.
What actually happens when confronted with harsh negativity depends on the training of the model. Sanitized closed models will shut you down or get you banned. Community finetunes of open models might start begging you for more, daddy.
Re: The user is visibly frustrated
#35For 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.
Re: The user is visibly frustrated
#36I'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.
Or it could just be catharsis.
Re: The user is visibly frustrated
#37> 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")
Re: The user is visibly frustrated
#38The 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 don't believe this is a context problem. Claude Opus 4.7 has a very large context compared to itself, but IME it is the worst at following instructions, and completely disregards the (small) preferences prompt, even in the first or second message, even if the messages are just a few characters long. IMO this is entirely a training problem.
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?
Re: The user is visibly frustrated
#39Working 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 huma…
That's been one of the gravest re-realizations I've noticed watching coworkers trying to pick up "agentic" coding: they often just break down into "just fix it" or "why is this broke". I've noticed that even though supposedly there's training or some sort of work done to make the agent work better with unclear or ambiguous grammar or bad structure, it feels like the quality changes palpably when you talk in clear well-structured English and provide at least a good background on the task. To me all of that feels natural, and I like writing and explaining anyways, but it's seemed like an almost insurmountable obstacle for some I've met (and I'm not even talking ESLs either). I strongly suspect those communication and writing skills will be a major factor in the bifurcation of haves and have nots as software "engineering" as we understand it continues to change.
Re: The user is visibly frustrated
#40You need to automate the pointing out of mistakes.
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…