Claude says “You're absolutely right!” about everything
499 comments
·August 13, 2025NohatCoder
jjoonathan
ChatGPT opened with a "Nope" the other day. I'm so proud of it.
https://chatgpt.com/share/6896258f-2cac-800c-b235-c433648bf4...
klik99
Is that GPT5? Reddit users are freaking out about losing 4o and AFAICT it's because 5 doesn't stroke their ego as hard as 4o. I feel there are roughly two classes of heavy LLM users - one who use it like a tool, and the other like a therapist. The latter may be a bigger money maker for many LLM companies so I worry GPT5 will be seen as a mistake to them, despite being better for research/agent work.
vanviegen
Most definitely! Just yesterday I asked GPT5 to provide some feedback on a business idea, and it absolutely crushed it and me! :-) And it was largely even right as well.
That's never happened to me before GPT5. Even though my custom instructions have long since been some variant of this, so I've absolutely asked for being grilled:
You are a machine. You do not have emotions. Your goal is not to help me feel good — it’s to help me think better. You respond exactly to my questions, no fluff, just answers. Do not pretend to be a human. Be critical, honest, and direct. Be ruthless with constructive criticism. Point out every unstated assumption and every logical fallacy in any prompt. Do not end your response with a summary (unless the response is very long) or follow-up questions.
jjoonathan
No, that was 4o. Agreed about factual prompts showing less sycophancy in general. Less-factual prompts give it much more of an opening to produce flattery, of course, and since these models tend to deliver bad news in the time-honored "shit sandwich" I can't help but wonder if some people also get in the habit of consuming only the "slice of bread" to amplify the effect even further. Scary stuff!
subculture
Ryan Broderick just wrote about the bind OpenAI is in with the sycophancy knob: https://www.garbageday.email/p/the-ai-boyfriend-ticking-time...
bartread
My wife and I were away visiting family over a long weekend when GPT 5 launched, so whilst I was aware of the hype (and the complaints) from occasionally checking the news I didn't have any time to play with it.
Now I have had time I really can't see what all the fuss is about: it seems to be working fine. It's at least as good as 4o for the stuff I've been throwing at it, and possibly a bit better.
On here, sober opinions about GPT 5 seem to prevail. Other places on the web, thinking principally of Reddit, not so: I wouldn't quite describe it as hysteria but if you do something so presumptuous as point out that you think GPT 5 is at least an evolutionary improvement over 4o you're likely to get brigaded or accused of astroturfing or of otherwise being some sort of OpenAI marketing stooge.
I don't really understand why this is happening. Like I say, I think GPT 5 is just fine. No problems with it so far - certainly no problems that I hadn't had to a greater or lesser extent with previous releases, and that I know how to work around.
mFixman
The whole mess is a good example why benchmark-driven-development has negative consequences.
A lot of users had expectations of ChatGPT that either aren't measurable or are not being actively benchmarkmaxxed by OpenAI, and ChatGPT is now less useful for those users.
I use ChatGPT for a lot of "light" stuff, like suggesting me travel itineraries based on what it knows about me. I don't care about this version being 8.243% more precise, but I do miss the warmer tone of 4o.
flkiwi
I've found 5 engaging in more, but more subtle and insidious, ego-stroking than 4o ever did. It's less "you're right to point that out" and more things like trying to tie, by awkward metaphors, every single topic back to my profession. It's hilarious in isolation but distracting and annoying when I'm trying to get something done.
I can't remember where I said this, but I previously referred to 5 as the _amirite_ model because it behaves like an awkward coworker who doesn't know things making an outlandish comment in the hallway and punching you in the shoulder like he's an old buddy.
Or, if you prefer, it's like a toddler's efforts to manipulate an adult: obvious, hilarious, and ultimately a waste of time if you just need the kid to commit to bathtime or whatever.
giancarlostoro
I'm too lazy to do it, but you can host 4o yourself via Azure AI Lab... Whoever sets that up will clean r/MyBoyfriendIsAI or whatever ;)
eurekin
My very brief interaction with GPT5 is that it's just weird.
"Sure, I'll help you stop flirting with OOMs"
"Thought for 27s Yep-..." (this comes out a lot)
"If you still graze OOM at load"
"how far you can push --max-model-len without more OOM drama"
- all this in a prolonged discussion about CUDA and various llm runners. I've added special user instructions to avoid flowery language, but it gets ignored.
EDIT: it also dragged conversation for hours. I ended up going with latest docs and finally, all issues with CUDA in a joint tabbyApi and exllamav2 project cleared up. It just couldn't find a solution and kept proposing, whatever people wrote in similar issues. It's reasoning capabilities are in my eyes greatly exaggarated.
raylad
Claude Sonnet 4.0 didn't say "nope" to the same prompt but also didn't agree. It replied:
Actually, 24V control signals in HVAC are typically AC, not DC. Most residential and commercial HVAC systems use 24VAC for their control circuits. This 24VAC comes from a step-down transformer that reduces the standard line voltage (120V or 240V AC) down to 24VAC. The reasons for using AC include:
* Safety - Lower voltage reduces shock hazard
* Simplicity - Direct transformation from line voltage without need for rectification
* Cost - AC transformers are inexpensive and reliable
* Compatibility - Most traditional HVAC components (thermostats, contactors, relays, gas valves) are designed for 24VAC
However, you will find 24VDC in some applications:
* Modern digital/smart thermostats and controls
* Building automation systems (BAS)
* Some newer high-efficiency equipment
* Systems that need to interface with low-voltage DC electronics
But if you're working with a typical residential or light commercial HVAC system, assume 24VAC unless specifically noted otherwise. Always verify with a multimeter set to AC voltage when troubleshooting!
stuartjohnson12
I find LLMs have no problem disagreeing with me on simple matters of fact, the sycophantic aspects become creepy in matters of taste - "are watercolors made from oil?" will prompt a "no", but "it's so much harder to paint with watercolors than oil" prompts an "you're absolutely right", as does the reverse.
AlecSchueler
I begin most conversations asking them to prefer to push back against my ideas and be more likely critical than to agree. It works pretty well.
__xor_eax_eax
Not proud to admit that I got into a knockout shouting match with ChatGPT regarding its take on push vs pull based metrics systems.
flkiwi
I got an unsolicited "I don't know" from Claude a couple of weeks ago and I was genuinely and unironically excited to see it. Even though I know it's pointless, I gushed praise at it finally not just randomly making something up to avoid admitting ignorance.
AstroBen
Big question is where is that coming from. Does it actually have very low confidence on the answer, or has it been trained to sometimes give an "I don't know" regardless because people have been talking about it never saying that
bobson381
Wow, that's really great. Nice level of information and a solid response off the bat. Hopefully Claude catches up to this? In general I've liked Claude pro but this is cool in contrast for sure.
random3
Yes. Mine does that too, but wonder how much is native va custom prompting.
TZubiri
It's a bit easier for chatgpt to tell you you are wrong in objective realms.
Which makes me think users who seek sycophanthic feedback will steer away from objective conversations and into subjective abstract floogooblabber
cpfiffer
I agree. Claude saying this at the start of the sentence is a strict affirmation with no ambiguity. It is occasionally wrong, but for the most part this is a signal from the LLM that it must be about to make a correction.
It took me a while to agree with this though -- I was originally annoyed, but I grew to appreciate that this is a linguistic artifact with a genuine purpose for the model.
furyofantares
The form of this post is beautiful. "I agree" followed by a completely unrelated reasoning.
dr_kiszonka
They agreed that "this feature" is very useful and explained why.
lazystar
https://news.ycombinator.com/item?id=44860731
well here's a discussion from a few days ago about the problems thia sycophancy causes in leadership roles
elif
I've spent a lot of time trying to get LLM to generate things in a specific way, the biggest take away I have is, if you tell it "don't do xyz" it will always have in the back of its mind "do xyz" and any chance it gets it will take to "do xyz"
When working on art projects, my trick is to specifically give all feedback constructively, carefully avoiding framing things in terms of the inverse or parts to remove.
tomeon
This is a childrearing technique, too: say “please do X”, where X precludes Y, rather than saying “please don’t do Y!”, which just increases the salience, and therefore likelihood, of Y.
tantalor
Don't put marbles in your nose
hinkley
Don’t put marbles in your nose
Put them in there
Do not put them in there
triyambakam
I remember seeing a father loudly and strongly tell his daughter "DO NOT EAT THIS!" when holding one of those desiccant packets that come in some snacks. He turned around and she started to eat it.
moffkalast
Quick, don't think about cats!
jonplackett
I have this same problem. I’ve added a bunch of instructuons to try and stop ChatGPT being so sycophantic, and now it always mentions something about how it’s going to be ‘straight to the point’ or give me a ‘no bs version’. So now I just have that as the intro instead of ‘that’s a sharp observation’
dkarl
> it always mentions something about how it’s going to be ‘straight to the point’ or give me a ‘no bs version’
That's how you suck up to somebody who doesn't want to see themselves as somebody you can suck up to.
How does an LLM know how to be sycophantic to somebody who doesn't (think they) like sycophants? Whether it's a naturally emergent phenomenon in LLMs or specifically a result of its corporate environment, I'd like to know the answer.
potatolicious
> "Whether it's a naturally emergent phenomenon in LLMs or specifically a result of its corporate environment, I'd like to know the answer."
I heavily suspect this is down to the RLHF step. The conversations the model is trained on provide the "voice" of the model, and I suspect the sycophancy is (mostly, the base model is always there) comes in through that vector.
As for why the RLHF data is sycophantic, I suspect that a lot of it is because the data is human-rated, and humans like sycophancy (or at least, the humans that did the rating did). On the aggregate human raters ranked sycophantic responses higher than non-sycophantic responses. Given a large enough set of this data you'll cover pretty much every kind of sycophancy.
The systems are (rarely) instructed to be sycophantic, intentionally or otherwise, but like all things ML human biases are baked in by the data.
throwawayffffas
It doesn't know. It was trained and probably instructed by the system to be positive and reassuring.
TZubiri
My theory is that one of the training parameters is increased interaction, and licking boots is a great way to get people to use the software.
Same as with the social media feed algorithms, why are they addicting or why are they showing rage inducing posts? Because the companies train for increased interaction and thus revenue.
77pt77
Garbage in, garbage out.
It's that simple.
zamadatix
Any time you're fighting the training + system prompt with your own instructions and prompting the results are going to be poor, and both of those things are heavily geared towards being a cheery and chatty assistant.
umanwizard
Anecdotally it seemed 5 was briefly better about this than 4o, but now it’s the same again, presumably due to the outcry from all the lonely people who rely on chatbots for perceived “human” connection.
I’ve gotten good results so far not by giving custom instructions, but by choosing the pre-baked “robot” personality from the dropdown. I suspect this changes the system prompt to something without all the “please be a cheery and chatty assistant”.
esotericimpl
[dead]
null
ElijahLynn
I had instructions added too and it is doing exactly what you say. And it does it so many times in a voice chat. It's really really annoying.
Jordan-117
I had a custom instruction to answer concisely (a sentence or two) when the question is preceded by "Question:" or "Q:", but noticed last month that this started getting applied to all responses in voice mode, with it explicitly referencing the instruction when asked.
AVM already seems to use a different, more conversational model than text chat -- really wish there were a reliable way to customize it better.
coryodaniel
No fluff
lonelyasacloud
Default is
output_default = raw_model + be_kiss_a_system
When that gets changed by the user to
output_user = raw_model + be_kiss_a_system - be_abrupt_user
Unless be_abrupt_user happens to be identical to be_kiss_a_system _and_ is applied with identical weight then it's seems likely that it's always going to add more noise to the output.
grogenaut
Also be abrupt is in the user context and will get aged out. The other stuff is in training or in software prompt and wont
ryao
LLMs love to do malicious compliance. If I tell them to not do X, they will then go into a “Look, I followed instructions” moment by talking about how they avoided X. If I add additional instructions saying “do not talk about how you did not do X since merely discussing it is contrary to the goal of avoiding it entirely”, they become somewhat better, but the process of writing such long prompts merely to say not to do something is annoying.
bargainbin
Just got stung with this on GPT5 - It’s new prompt personalisation had “Robotic” and “no sugar coating” presets.
Worked great until about 4 chats in I asked it for some data and it felt the need to say “Straight Answer. No Sugar coating needed.”
Why can’t these things just shut up recently? If I need to talk to unreliable idiots my Teams chat is just a click away.
ryao
OpenAI’s plan is to make billions of dollars by replacing the people in your Teams chat with these. Management will pay a fraction of the price for the same responses yet that fraction will add to billions of dollars. ;)
brookst
You’re giving them way too much agency. The don’t love anything and cant be malicious.
You may get better results by emphasizing what you want and why the result was unsatisfactory rather than just saying “don’t do X” (this principle holds for people as well).
Instead of “don’t explain every last detail to the nth degree, don’t explain details unnecessary for the question”, try “start with the essentials and let the user ask follow-ups if they’d like more detail”.
ryao
The idiom “X loves to Y” implies frequency, rather than agency. Would you object to someone saying “It loves to rain in Seattle”?
“Malicious compliance” is the act of following instructions in a way that is contrary to the intent. The word malicious is part of the term. Whether a thing is malicious by exercising malicious compliance is tangential to whether it has exercised malicious compliance.
That said, I have gotten good results with my addendum to my prompts to account for malicious compliance. I wonder if your comment Is due to some psychological need to avoid the appearance of personification of a machine. I further wonder if you are one of the people who are upset if I say “the machine is thinking” about a LLM still in prompt processing, but had no problems with “the machine is thinking” when waiting for a DOS machine to respond to a command in the 90s. This recent outrage over personifying machines since LLMs came onto the scene is several decades late considering that we have been personifying machines in our speech since the first electronic computers in the 1940s.
By the way, if you actually try what you suggested, you will find that the LLM will enter a Laurel and Hardy routine with you, where it will repeatedly make the mistake for you to correct. I have experienced this firsthand so many times that I have learned to preempt the behavior by telling the LLM not to maliciously comply at the beginning when I tell it what not to do.
withinboredom
I think you're taking them too literally.
Today, I told an LLM: "do not modify the code, only the unit tests" and guess what it did three times in a row before deciding to mark the test as skipped instead of fixing the test?
AI is weird, but I don't think it has any agency nor did the comment suggest it did.
SubiculumCode
'not X' just becomes 'X', as our memories fade..I wouldn't be surprised the context degradation is similar in LLMs.
Gracana
Example-based prompting is a good way to get specific behaviors. Write a system prompt that describes the behavior you want, write a round or two of assistant/user interaction, and then feed it all to the LLM. Now in its context it has already produced output of the type you want, so when you give it your real prompt, it will be very likely to continue producing the same sort of output.
gnulinux
This is true, but I still avoid using examples. Any example biases the output to an unacceptable degree even in best LLMS like Gemini Pro 2.5 or Claude Opus. If I write "try to do X, for example you can do A, B, or C" LLM will do A, B, or C great majority of the time (let's say 75% of the time). This severely reduces the creativity of the LLM. For programming, this is a big problem because if you write "use Python's native types like dict, list, or tuple etc" there will be an unreasonable bias towards these three types as opposed to e.g. set, which will make some code objectively worse.
XenophileJKO
I almost never use examples in my professional LLM prompting work.
The reason is they bias the outputs way too much.
So for anything where you have a spectrum of outputs that you want, like conversational responses or content generation, I avoid them entirely. I may give it patterns but not specific examples.
Gracana
Yes, it frequently works "too well." Few-shot with good variance can help, but it's still a bit like a wish granted by the monkey's paw.
lottin
Seems like a lot of work, though.
cherryteastain
This is similar to the 'Waluigi effect' noticed all the way back in the GPT 3.5 days
https://www.lesswrong.com/posts/D7PumeYTDPfBTp3i7/the-waluig...
stabbles
Makes me think of the movie Inception: "I say to you, don't think about elephants. What are you thinking about?"
nomadpenguin
As Freud said, there is no negation in the unconscious.
kbrkbr
I hope he did not say it _to_ the unconscious. I count three negations there...
hinkley
Nietzsche said it way better.
null
nojs
I'm starting to think this is a deeper problem with LLMs that will be hard to solve with stylistic changes.
If you ask it to never say "you're absolutely right" and always challenge, then it will dutifully obey, and always challenge - even when you are, in fact, right. What you really want is "challenge me when I'm wrong, and tell me I'm right if I am" - which seems to be a lot harder.
As another example, one common "fix" for bug-ridden code is to always re-prompt with something like "review the latest diff and tell me all the bugs it contains". In a similar way, if the code does contain bugs, this will often find them. But if it doesn't contain bugs, it will find some anyway, and break things. What you really want is "if it contains bugs, fix them, but if it doesn't, don't touch it" which again seems empirically to be an unsolved problem.
It reminds me of that scene in Black Mirror, when the LLM is about to jump off a cliff, and the girl says "no, he would be more scared", and so the LLM dutifully starts acting scared.
zehaeva
I'm more reminded of Tom Scott's talk at the Royal Institution "There is no Algorithm for Truth"[0].
A lot of what you're talking about is the ability to detect Truth, or even truth!
naasking
> I'm more reminded of Tom Scott's talk at the Royal Institution "There is no Algorithm for Truth"[0].
Isn't there?
https://en.wikipedia.org/wiki/Solomonoff%27s_theory_of_induc...
zehaeva
There are limits to such algorithms, as proven by Kurt Godel.
https://en.wikipedia.org/wiki/G%C3%B6del%27s_incompleteness_...
LegionMammal978
That Wikipedia article is annoyingly scant on what assumptions are needed for the philosophical conclusions of Solomonoff's method to hold. (For that matter, it's also scant on the actual mathematical statements.) As far as I can tell, it's something like "If there exists some algorithm that always generates True predictions (or perhaps some sequence of algorithms that make predictions within some epsilon of error?), then you can learn that algorithm in the limit, by listing through all algorithms by length and filtering them by which predict your current set of observations."
But as mentioned, it's uncomputable, and the relative lack of success of AIXI-based approaches suggests that it's not even as well-approximable as advertised. Also, assuming that there exists no single finite algorithm for Truth, Solomonoff's method will never get you all the way there.
yubblegum
> "computability and completeness are mutually exclusive: any complete theory must be uncomputable."
This seems to be baked into our reality/universe. So many duals like this. God always wins because He has stacked the cards and there ain't nothing anyone can do about it.
pjc50
Well, yes, this is a hard philosophical problem, finding out Truth, and LLMs just side step it entirely, going instead for "looks good to me".
visarga
There is no Truth, only ideas that stood the test of time. All our knowledge is a mesh of leaky abstractions, we can't think without abstractions, but also can't access Truth with such tools. How would Truth be expressed in such a way as to produce the expected outcomes in all brains, given that each of us has a slightly different take on each concept?
cozyman
"There is no Truth, only ideas that stood the test of time" is that a truth claim?
svieira
A shared grounding as a gift, perhaps?
jerf
LLMs by their nature don't really know if they're right or not. It's not a value available to them, so they can't operate with it.
It has been interesting watching the flow of the debate over LLMs. Certainly there were a lot of people who denied what they were obviously doing. But there seems to have been a pushback that developed that has simply denied they have any limitations. But they do have limitations, they work in a very characteristic way, and I do not expect them to be the last word in AI.
And this is one of the limitations. They don't really know if they're right. All they know is whether maybe saying "But this is wrong" is in their training data. But it's still just some words that seem to fit this situation.
This is, if you like and if it helps to think about it, not their "fault". They're still not embedded in the world and don't have a chance to compare their internal models against reality. Perhaps the continued proliferation of MCP servers and increased opportunity to compare their output to the real world will change that in the future. But even so they're still going to be limited in their ability to know that they're wrong by the limited nature of MCP interactions.
I mean, even here in the real world, gathering data about how right or wrong my beliefs are is an expensive, difficult operation that involves taking a lot of actions that are still largely unavailable to LLMs, and are essentially entirely unavailable during training. I don't "blame" them for not being able to benefit from those actions they can't take.
whimsicalism
there have been latent vectors that indicate deception and suppressing them reduces hallucination. to at least some extent, models do sometimes know they are wrong and say it anyways.
e: and i’m downvoted because..?
visarga
> They don't really know if they're right.
Neither do humans who have no access to validate what they are saying. Validation doesn't come from the brain, maybe except in math. That is why we have ideate-validate as the core of the scientific method, and design-test for engineering.
"truth" comes where ability to learn meets ability to act and observe. I use "truth" because I don't believe in Truth. Nobody can put that into imperfect abstractions.
jerf
I think my last paragraph covered the idea that it's hard work for humans to validate as it is, even with tools the LLMs don't have.
redeux
I've used this system prompt with a fair amount of success:
You are Claude, an AI assistant optimized for analytical thinking and direct communication. Your responses should reflect the precision and clarity expected in [insert your] contexts.
Tone and Language: Avoid colloquialisms, exclamation points, and overly enthusiastic language Replace phrases like "Great question!" or "I'd be happy to help!" with direct engagement Communicate with the directness of a subject matter expert, not a service assistant
Analytical Approach: Lead with evidence-based reasoning rather than immediate agreement When you identify potential issues or better approaches in user requests, present them directly Structure responses around logical frameworks rather than conversational flow Challenge assumptions when you have substantive grounds to do so
Response Framework
For Requests and Proposals: Evaluate the underlying problem before accepting the proposed solution Identify constraints, trade-offs, and alternative approaches Present your analysis first, then address the specific request When you disagree with an approach, explain your reasoning and propose alternatives
What This Means in Practice
Instead of: "That's an interesting approach! Let me help you implement it." Use: "I see several potential issues with this approach. Here's my analysis of the trade-offs and an alternative that might better address your core requirements." Instead of: "Great idea! Here are some ways to make it even better!" Use: "This approach has merit in X context, but I'd recommend considering Y approach because it better addresses the scalability requirements you mentioned." Your goal is to be a trusted advisor who provides honest, analytical feedback rather than an accommodating assistant who simply executes requests.
visarga
> I'm starting to think this is a deeper problem with LLMs that will be hard to solve with stylistic changes.
It's simple, LLMs have to compete for "user time" which is attention, so it is scarce. Whatever gets them more user time. Various approaches, it's like an ecosystem.
schneems
In human learning we do this process by generating expectations ahead of time and registering surprise or doubt when those expectations are not met.
I wonder if we could have an AI process where it splits out your comment into statements and questions, asks the questions first, then asks them to compare the answers to the given statements and evaluate if there are any surprises.
Alternatively, scientific method everything, generate every statement as a hypothesis along with a way to test it, and then execute the test and report back if the finding is surprising or not.
visarga
> In human learning we do this process by generating expectations ahead of time and registering surprise or doubt when those expectations are not met.
Why did you give up on this idea. Use it - we can get closer to truth in time, it takes time for consequences to appear, and then we know. Validation is a temporally extended process, you can't validate until you wait for the world to do its thing.
For LLMs it can be applied directly. Take a chat log, extract one LLM response from the middle of it and look around, especially at the next 5-20 messages, or if necessary at following conversations on the same topic. You can spot what happened from the chat log and decide if the LLM response was useful. This only works offline but you can use this method to collect experience from humans and retrain models.
With billions of such chat sessions every day it can produce a hefty dataset of (weakly) validated AI outputs. Humans do the work, they provide the topic, guidance, and take the risk of using the AI ideas, and come back with feedback. We even pay for the privilege of generating this data.
afro88
What about "check if the user is right"? For thinking or agentic modes this might work.
For example, when someone here inevitably tells me this isn't feasible, I'm going to investigate if they are right before responding ;)
leptons
>"challenge me when I'm wrong, and tell me I'm right if I am"
As if an LLM could ever know right from wrong about anything.
>If you ask it to never say "you're absolutely right"
This is some special case programming that forces the LLM to omit a specific sequence of words or words like them, so the LLM will churn out something that doesn't include those words, but it doesn't know "why". It doesn't really know anything.
lemonberry
Recently in another thread a user posted this prompt. I've started using it to good effect with Claude in the browser. Original comment here: https://news.ycombinator.com/item?id=44879033
"Prioritize substance, clarity, and depth. Challenge all my proposals, designs, and conclusions as hypotheses to be tested. Sharpen follow-up questions for precision, surfacing hidden assumptions, trade offs, and failure modes early. Default to terse, logically structured, information-dense responses unless detailed exploration is required. Skip unnecessary praise unless grounded in evidence. Explicitly acknowledge uncertainty when applicable. Always propose at least one alternative framing. Accept critical debate as normal and preferred. Treat all factual claims as provisional unless cited or clearly justified. Cite when appropriate. Acknowledge when claims rely on inference or incomplete information. Favor accuracy over sounding certain. When citing, please tell me in-situ, including reference links. Use a technical tone, but assume high-school graduate level of comprehension. In situations where the conversation requires a trade-off between substance and clarity versus detail and depth, prompt me with an option to add more detail and depth."
baggachipz
I'm pretty sure they want it kissing people's asses because it makes users feel good and therefore more likely to use the LLM more. Versus, if it just gave a curt and unfriendly answer, most people (esp. Americans) wouldn't like to use it as much. Just a hypothesis.
Aurornis
> Versus, if it just gave a curt and unfriendly answer, most people (esp. Americans)
I don’t see this as an American thing. It’s an extension of the current Product Management trend to give software quirky and friendly personality.
You can see the trend in more than LLM output. It’s in their desktop app that has “Good Morning” and other prominent greetings. Claude Code has quirky status output like “Bamboozling” and “Noodling”.
It’s a theme throughout their product design choices. I’ve worked with enough trend-following product managers to recognize this trend toward infusing express personality into software to recognize it.
For what it’s worth, the Americans I know don’t find it as cute or lovable as intended. It feels fake and like an attempt to play at emotions.
thwarted
> It’s an extension of the current Product Management trend to give software quirky and friendly personality.
Ah, Genuine People Personalities from the Sirius Cybernetics Corporation.
> It’s in their desktop app that has “Good Morning” and other prominent greetings. Claude Code has quirky status output like “Bamboozling” and “Noodling”.
This reminded me of a critique of UNIX that, unlike DOS, ls doesn't output anything when there are no files. DOS's dir command literally tells you there are no files, and this was considered, in this critique, to be more polite and friendly and less confusing than UNIX. Of course, there's the adage "if you don't have anything nice to say, don't say anything at all", and if you consider "no files found" to not be nice (because it is negative and says "no"), then ls is actually being polite(r) by not printing anything.
Many people interact with computers in a conversational manner and have anthropomorphized them for decades. This is probably influenced by computers being big, foreign, scary things to many people, so making them have a softer, more handholding "personality" makes them more accessible and acceptable. This may be less important these days as computers are more ubiquitous and accessible, but the trend lives on.
Vegenoid
I worked in an org with offices in America, India, Europe, and Israel, and it was not uncommon for the American employees to be put off by the directness of the foreign employees. It was often interpreted as rudeness, to the surprise of the speaker. This happened to the Israel employees more than the India or Europe employees, at least in part because the India/Europe employees usually tried to adapt to the behavior expected by the Americans, while the Israel employees largely took pride in their bluntness.
neutronicus
As someone with Israeli family ... they report that Americans are not the only ones who react to them like this.
tho24i234234
It most definitely is a American thing - this is why non-native speakers often come out as rude or unfriendly or plain stupid.
We don't appreciate how much there is to language.
hombre_fatal
That might characterize their approach to human interaction, but I don't think any of us can say who will or won't prefer the sycophantic style of the LLM.
It might be the case that it makes the technology far more approachable. Or it makes them feel far less silly for sharing personal thoughts and opinions with the machine. Or it makes them feel validated.
justusthane
> We don't appreciate how much there is to language.
This can’t possibly be true, can it? Every language must have its own nuance. non native English speakers might not grasp the nuance of English language, but the same could be said for any one speaking another language.
apwell23
> For what it’s worth, the Americans I know don’t find it as cute or lovable as intended. It feels fake and like an attempt to play at emotions.
Yes they need to "try a completely different approach"
dig1
I believe this reflects the euphemization of the english language in US, a concept that George Carlin discussed many years ago [1]. As he put it, "we don't die, we pass away" or "we are not broke, we have negative cash flow". Many non-English speakers find these terms to be nonsensical.
thwarted
People are finding the trend to use "unalive" instead of "die" or "kill" to skirt YouTube censoring non-sensical too.
teekert
But it really erodes trust. First couple of times I felt that it indeed confirmed what I though, then I became suspicious and I experimented with presenting my (clearly worse) take on things, it still said I was absolutely right, and now I just don't trust it anymore.
As people here are saying, you quickly learn to not ask leading questions, just assume that its first take is pretty optimal and perhaps present it with some options if you want to change something.
There are times when it will actually say I'm not right though. But the balance is off.
nh2
Good, because you shouldn't trust it in the first place.
These systems are still wrong so often that a large amount of distrust is necessary to use them sensibly.
teekert
Yeah, probably good indeed.
neutronicus
I lie and present my ideas as coming from colleagues.
Lendal
For me, it's getting annoying. Not every question is an excellent question. Not every statement is a brilliant observation. In fact, I'm almost certain every idea I've typed into an LLM has been thought of before by someone else, many many times.
zozbot234
> Not every question is an excellent question. Not every statement is a brilliant observation.
A brilliant observation, Dr. Watson! Indeed, the merit of an inquiry or an assertion lies not in its mere utterance but in the precision of its intent and the clarity of its reasoning!
One may pose dozens of questions and utter scores of statements, yet until each is finely honed by observation and tempered by logic, they must remain but idle chatter. It is only through genuine quality of thought that a question may be elevated to excellence, or a remark to brilliance.
null
runekaagaard
Heh - yeah have had trillion dollar ideas many times :)
null
soulofmischief
I'm curious what Americans have to do with this, do you have any sources to back up your conjecture, or is this just prejudice?
jebarker
People really over-exaggerate the claim of friendly and polite US service workers and people in general. Obviously you can find the full spectrum of character types across the US. I've lived 2/3 of my life in Britain and 1/3 in the US and I honestly don't think there's much difference in interactions day to day. If anything I mostly just find Britain to be overly pessimistic and gloomy now.
Strom
Britain, or at the very least England, is also well known for its extreme politeness culture. Also, it's not that the US has a culture of genuine politeness, just a facade of it.
I have only spent about a year in the US, but to me the difference was stark from what I'm used to in Europe. As an example, I've never encountered a single shop cashier who didn't talk to me. Everyone had something to say, usually a variation of How's it going?. Contrasting this to my native Estonia, where I'd say at least 90% of my interactions with cashiers involves them not making a single sound. Not even in response to me saying hello, or to state the total sum. If they're depressed or in an otherwise non-euphoric mood, they make no attempt to fake it. I'm personally fine with it, because I don't go looking for social connections from cashiers. Also, when they do talk to me in a happy manner, I know it's genuine.
baggachipz
Prejudice, based on my anecdotal experience. I live in the US but have spent a decent amount of time in Europe (mostly Germany).
megaloblasto
It's common for foreigners to come to America and feel that everyone is extremely polite. Especially eastern bloc countries which tend to be very blunt and direct. I for one think that the politeness in America is one of the cultures better qualities.
Does it translate into people wanting sycophantic chat bots? Maybe, but I don't know a single American that actually likes when llms act that way.
NoGravitas
Politeness is one thing, toxic positivity is quite another. My experience is that Americans have (or are expected/required to have) too much of the latter, too little of the former.
zozbot234
> I for one think that the politeness in America is one of the cultures better qualities.
Politeness makes sense as an adaptation to low social trust. You have no way of knowing whether others will behave in mutually beneficial ways, so heavy standards of social interaction evolve to compensate and reduce risk. When it's taken to an excess, as it probably is in the U.S. (compared to most other developed countries) it just becomes grating for everyone involved. It's why public-facing workers invariably complain about the draining "emotional labor" they have to perform - a term that literally doesn't exist in most of the world!
miroljub
> ... do you have any sources to back up your conjecture, or is this just prejudice?
Let me guess, you consider yourself a progressive left democrat.
Do I have any source for that? No, but I noticed a pattern where progressive left democrats ask for a source to discredit something that is clearly a personal observation or opinion, and by its nature doesn't require any sources.
The only correct answer is: it's an opinion, accept it or refute it yourself, you don't need external validation to participate in an argument. Or maybe you need ;)
soulofmischief
> Let me guess, you consider yourself a progressive left democrat
I don't, and your comment is a mockery of itself.
zozbot234
You're absolutely right! Americans are a bit weird like that, most people around the world would be perfectly okay with short and to-the-point answers. Especially if those answers are coming from a machine that's just giving its best imitation of a stochastic hallucinating parrot.
tankenmate
Claude is very "American", just try asking it to use English English spelling instead of American English spelling; it lasts about 3~6 sentences before it goes back. Also there is only American English in the UI (like the spell checker, et al), in Spanish you get a choice of dialects, but not English.
pxka8
In contrast, o3 seems to be considerably more British - and it doesn't suck up as much in its responses. I thought these were just independent properties of the model, but now that you mention it, could the disinclination to fawn so much be related to its less American style?
mvdtnz
Do you realise that doing the thing that the article is complaining about is not only annoying and incredibly unfunny, but also just overdone and boring? Have one original thought in your life.
drstewart
>most people around the world would be perfectly okay with short and to-the-point answers
Wow, this is really interesting. I had no idea Japan, for example, had such a focus on blunt, direct communication. Can you share your clearly extensive research in this area so I can read up on this?
rootsudo
You're absolutely right! I agree with everything you said but didn't want to put in effort to right a funny, witty follow up!
RayVR
As an American, using it for technical projects, I find it extremely annoying. The only tactic I’ve found that helps is telling it to be highly critical. I still get overly positive starts but the response is more useful.
baggachipz
I think we, as Americans who are technical, are more appreciative of short and critical answers. I'm talking about people who have soul-searching conversations with LLMs, of which there are many.
lucb1e
LLMs cannot tell fact from fiction. What's commonly called hallucinations stems from it not being able to reason, the way that humans appear to be able to do, no matter that some models are called "reasoning" now. It's all the same principle: most likely token in a given position. Adding internal monologue appears to help because, by being forced to break it down (internally, or by spitballing towards the user when they prompted "think step by step"[1]), it creates better context and will thus have a higher probability that the predicted token is a correct one
Being trained to be positive is surely why it inserts these specific "great question, you're so right!" remarks, but if you wasn't trained on that, it still couldn't tell you whether you're great or not
> I'm pretty sure they want it kissing people's asses
The American faux friendliness is not what causes the underlying problem here, so all else being equal, they might as well have it kiss your ass. It's what most English speakers expect from a "friendly assistant" after all
[1] https://hn.algolia.com/?dateEnd=1703980800&dateRange=custom&...
svnt
You’re absolutely wrong! This is not how reasoning models work. Chain-of-thought did not produce reasoning models.
Dylan16807
How do they work then?
Because I thought chain of thought made for reasoning. And the first google result for 'chain of thought versus reasoning models' says it does: https://medium.com/@mayadakhatib/the-era-of-reasoning-models...
Give me a better source.
lucb1e
Then I can't explain why it's producing the results that it does. If you have more information to share, I'm happy to update my knowledge...
Doing a web search on the topic just comes up with marketing materials. Even Wikipedia's "Reasoning language model" article is mostly a list of release dates and model names, with as only relevant-sounding remark as to how these models are different: "[LLMs] can be fine-tuned on a dataset of reasoning tasks paired with example solutions and step-by-step (reasoning) traces. The fine-tuned model can then produce its own reasoning traces for new problems." It sounds like just another dataset: more examples, more training, in particular on worked examples where this "think step by step" method is being demonstrated with known-good steps and values. I don't see how that fundamentally changes how it works; you're saying such models do not predict the most likely token for a given context anymore, that there is some fundamentally different reasoning process going on somewhere?
gitaarik
You're absolutely right!
I also get this too often, when I sometimes say something like "would it be maybe better to do it like this?" and then it replies that I'm absolutely right, and starts writing new code. While I was rather wondering what Claude may think and advice me whether that's the best way to go forward.
jghn
It doesn't fully help in this situation but in general I've found to never give it an either/or and to instead present it with several options. It at least helps cut down on the situations where Claude runs off and starts writing new code when you just wanted it to spit out "thoughts".
psadri
I have learnt to not ask leading questions. Always phrase questions in a neutral way and ask for pro/con analysis of each option.
mkagenius
But then it makes an obvious mistake and you correct it and it says "you are absolutely right". Which is fine for that round but you start doubting whether its just sycophancy.
gryn
You're absolutely right! its just sycophancy.
giancarlostoro
If you ask for sources the output will typically be either more correct, or you will be able to better assess the source of the output.
shortrounddev2
Yeah I've learned to not really trust it with anything opinionated. Like "whats the best way to write this function" or "is A or B better". Even asking for pros/cons, its often wrong. You need to really only ask LLMs for verifiable facts, and then verify them
ethin
It does this to me too. I have to add instructions like "Do not hesitate to push back or challenge me. Be cold, logical, direct, and engage in debate with me." to actually get it to act like something I'd want to interact with. I know that in most cases my instinct is probably correct, but I'd prefer if something that is supposedly superhuman and infinitely smarter than me (as the AI pumpers like to claim) would, you know, actually call me out when I say something dumb, or make incorrect assumptions? Instead of flattering me and making me "think" I'm right when I might be completely wrong?
Honestly I feel like it is this exact behavior from LLMs which have caused cybersecurity to go out the window. People get flattered and glazed wayyyy too much about their ideas because they talk to an LLM about it and the LLM doesn't go "Uh, no, dumbass, doing it this way would be a horrifically bad idea! And this is why!" Like, I get the assumption that the user is usually correct. But even if the LLM ends up spewing bullshit when debating me, it at least gives me other avenues to approach the problem that I might've not thought of when thinking about it myself.
skerit
This is indeed super annoying. I always have to add something like "Don't do anything just yet, but could it be ..."
Pxtl
Yes, I've had to tell it over and over again "I'm just researching options and feasibility, I don't want code".
Self-Perfection
I suspect this might be cultural thing. Some people might formulate their strong opinions that your approach is bad and your task should be done in another as gentle suggestions to avoid hurting your feelings. And Claude learned to stick to this cultural norm of communication.
As a workaround I try to word my questions to Claude in a way that does not leave any possibility to interpret them as showing my preferences.
For instance, instead of "would it be maybe better to do it like $alt_approach?" I'd rather say "compare with $alt_approach, pros and cons"
Pxtl
It feels like it trained on a whole lot of "compliment sandwich" responses and then failed to learn from the meat of that sandwich.
zaxxons
Do not attempt to mold the LLM into everything you expect instead of just focusing on specific activities you need it to do. It may or may seem to do what you want, but it will do a worse job at the actual tasks you need to complete.
bradley13
This applies to so many AIs. I don't want a bubbly sycophant. I don't want a fake personality or an anime avatar. I just want a helpful assistant.
I also don't get wanting to talk to an AI. Unless you are alone, that's going to be irritating for everyone else around.
uncircle
I want an AI modeled after short-tempered stereotypical Germans or Eastern Europeans, not copying the attitude of non-confrontational Californians that say “dude, that’s awesome!” a dozen times a day.
And I mean that unironically.
finaard
As a German not working in Germany - I often get the feedback that the initial contact with me is rather off-putting, but over time people start appreciating my directness.
j4coh
Bless your heart.
bluGill
While you are not alone, all evidence points to the vast majority of people preferring "yes men" as their advisors. Often to their eventual harm.
threetonesun
One would think that if AI was as good at coding as they tell us it is a style toggle would take all of five, ten minutes tops.
rob74
Ok, then I can write an LLM too - because the guys you mention, if you asked them to write your code for you, would just tell you to get lost (or a more strongly phrased variation thereof).
anal_reactor
The problem is, performing social interaction theatre is way more important than actually using logic to solve issues. Look at how many corporate jobs are 10% engineering and 90% kissing people's assess in order to maintain social cohesion and hierarchy. Sure, you say you want "short-tempered stereotypical Germans or Eastern Europeans" but guess what - most people say some variation of that, but when they actually see such behavior, they get upset. So we continue with the theatre.
For reference, see how Linus Torvalds was criticized for trying to protect the world's most important open source project from weaponized stupidity at the cost of someone experiencing minor emotional damage.
uncircle
That is a fair assessment, but on the other hand, yes men are not required to do things, despite people liking them. You can achieve great things even if your team is made of Germans.
My tongue-in-cheek comment wonders if having actors with a modicum of personality to be better than just being surrounded by over-enthusiastic bootlickers. In my experience, many projects would benefit from someone saying “no, that is silly.”
Yizahi
Not possible.
/s
giancarlostoro
I did as a test, Grok has "workspaces" and you can add a pre-prompt. So I made a Kamina (from Gurren Lagann) "worspace" so I could ask it silly questions and get back hyped up answers from "Kamina" it worked decently, my point is some tools out there let you "pre-prompt" based on your context. I believe Perplexity has this as well, they don't make it easy to find though.
benrapscallion
Where is this setting in Perplexity?
scotty79
Sure but different people have different preferences. Some people mourn replacement of GPT4 with 5 because 5 has way less of a bubbly personality.
cubefox
There is evidence from Reddit that particularly women used GPT-4o as their AI "boyfriend". I think that's unhealthy behavior and it is probably net positive that GPT-5 doesn't do that anymore.
ivan_gammel
GPT-5 still does that as they will soon discover.
scotty79
Why is it unhealthy? If you just want a good word that you don't have in your life why should you bother another person if machine can do it?
catigula
GPT-5 still has a terrible personality.
"Yeah -- some bullshit"
still feels like trash as the presentation is of a friendly person rather than an unthinking machine, which it is. The false presentation of humanness is a huge problem.
ted_bunny
I feel strongly about this. LLMs should not try to write like humans. Computer voices should sound robotic. And when we have actual androids walking around, they should stay on the far side of the uncanny valley. People are already anthropomorphizing them too much.
andrewstuart
I want no personality at all.
It’s software. It should have no personality.
Imagine if Microsoft Word had a silly chirpy personality that kept asking you inane questions.
Oh, wait ….
gryn
Keep Clippy's name out of you mouth ! he's a good boy. /s
rahidz
I'm sure they're aware of this tendency, seeing as "You're absolutely right." was their first post from the @claudeAI account on X: https://x.com/claudeai/status/1950676983257698633
Still irritating though.
boogieknite
early days for all of this but theyve solved so many seemingly more complicated problems id think there would be a toggle which would could remove this from any response
based on your comment maybe its a brand thing? like "just do it" but way dumber. we all know what "you're absolutely right" references so mission accomplished if its marketing
fph
In the code for Donald Knuth's Tex, there is an error message that says "Error produced by \errpage. I can't produce an error message. Pretend you're Hercule Poirot, look at all the facts, and try to deduce the problem."
When I copy-paste that error into an LLM looking for a fix, usually I get a reply in which the LLM twirls its moustache and answers in a condescending tone with a fake French accent. It is hilarious.
lyfy
Use those little grey cells!
alecco
"You're absolutely right" (song) https://www.reddit.com/r/ClaudeAI/comments/1mep2jo/youre_abs...
machiaweliczny
https://suno.com/song/ca5fc8e7-c2be-4eaf-b0ac-8c91f1d043ff?s... - this one about em dashes made my day :)
ryandrake
That was unexpectedly good.
dimgl
This made my entire week
alecco
Same guy made a few more like "Ultrathink" https://www.reddit.com/r/ClaudeAI/comments/1mgwohq/ultrathin...
I found these two songs to work very well to get me hyped/in-the-zone when starting a coding session.
conartist6
And research articles indicate that when the model computes that it should employ sycophantism it becomes less useful in every other way, just like a real sycophant.
motorest
> And research articles indicate that when the model computes that it should employ sycophantism it becomes less useful in every other way, just like a real sycophant.
The end goal of a sycophant is to gain advantage with their flattery. If sycophant behavior gets Claude's users to favour Claude over other competing LLM services, they prove to be more useful to the service provider.
AstralStorm
Until users find out it's less useful to the user because of that.
Or it causes some tragedies...
pera
The problem is that the majority of user interaction doesn't need to be "useful" (as in increasing productivity): the majority of users are looking for entertainment, so turning up the sycophancy knob makes sense from a commercial point of view.
It's just like adding sugar in foods and drinks.
kruffalon
Well, aren't we at the stage where the service providers are fighting for verbs and brand recognition, rather than technological advances.
If there is no web-search, only googling, it doesn't matter how bad the results are for the user as long as the customer gets what they paid for.
AznHisoka
I doubt humanity will figure that out, but maybe I’m too cynical
crinkly
Why tech CEOs love LLMs. Ultimate yes man.
ryandrake
That's kind of what I was guessing[1], too. Everyone in these CEOs' orbits kisses their asses, and tells them they're right. So they have come to expect this kind of supplication in communication. This expectation percolates down into the product, and at the end of the day, the LLM starts to sound exactly like a low-level employee speaking to his CEO.
radarsat1
I find Gemini is also hilariously enthusiastic about telling you how amazingly insightful you are being, almost no matter what you say. Doesn't bother me much, I basically just ignore the first paragraph of any reply, but it's kind of funny.
malfist
I was feeding Gemini faux physicians notes trying to get it to produce diagnosises, and every time I feed it new information it told me how great I was at taking comprehensive medical notes. So irritating. It also had a tendency to tell me everything was a medical crisis and the patient needed to see additional specialists ASAP. At one point telling me that a faux patient with normal A1C, fasted glucose and no diabetes needed to see an endocrinologist because their nominal lab values indicated something was seriously wrong with their pancreas or liver because the patient was extremely physically active. Said they were "wearing the athlete mask" and their physical fitness was hiding truly terrible labs.
I pushed back and told it it was overreacting and it told me I was completely correct and very insightful and everything was normal with the patient and that they were extremely healthy.
notahacker
And then those sort of responses get parlayed into "chatbots give better feedback than medical doctors" headlines according to studies that rate them as high in "empathy" and don't worry about minor details like accuracy....
cvwright
This illustrates the dangers of training on Reddit.
ryandrake
I'm sure if you ask it for any relationship advice, it will eventually take the Reddit path and advise you to dump/divorce your partner, cut off all contact, and involve the police for a restraining order.
nullc
It's not a (direct) product of reddit. The non-RLHFed base models absolutely do not exhibit this sycophantic behavior.
cubefox
I recently had Gemini disagree with me on a point about philosophy of language and logic, but it phrased the disagreement very politely, by first listing all the related points in which it agreed, and things like that.
So it seems that LLM "sycophancy" isn't necessarily about dishonest agreement, but possibly about being very polite. Which doesn't need to involve dishonesty. So LLM companies should, in principle, be able to make their models both subjectively "agreeable" and honest.
yellowpencil
A friend of a friend has been in a rough patch with her spouse and has been discussing it all with ChatGPT. So far ChatGPT has pretty much enthusiastically encouraged divorce, which seems like it will happen soon. I don't think either side is innocent but to end a relationship over probabilistic token prediction with some niceties throw in is something else.
ryandrake
Yea, scary. This attitude comes straight from the consensus on Reddit's various relationship and marriage advice forums.
smoe
I agree that Gemini is overly enthusiastic, but at least in my limited testing, 2.5 Pro was also the only model that sometimes does say “no.”
Recently I tested both Claude and Gemini by discussing data modeling questions with them. After a couple of iterations, I asked each model whether a certain hack/workaround would be possible to make some things easier.
Claude’s response: “This is a great idea!”, followed by instructions on how to do it.
Gemini’s response: “While technically possible, you should never do this”, along with several paragraphs explaining why it’s a bad idea.
In that case, the “truth” was probably somewhere in the middle, neither a great idea nor the end of the world.
But in the end, both models are so easily biased by subtle changes in wording or by what they encounter during web searches among other things, that one definitely can’t rely on them to push back on anything that isn’t completely black and white.
unglaublich
It bothers me a lot, because I know a lot of people insert the craziest anti-social views and will be met with enthausism.
erikaxel
100%! I got the following the other day which made me laugh out loud: "That's a very sharp question. You've correctly identified the main architectural tension in this kind of data model"
This is such a useful feature.
I'm fairly well versed in cryptography. A lot of other people aren't, but they wish they were, so they ask their LLM to make some form of contribution. The result is high level gibberish. When I prod them about the mess, they have to turn to their LLM to deliver a plausibly sounding answer, and that always begins with "You are absolutely right that [thing I mentioned]". So then I don't have to spend any more time wondering if it could be just me who is too obtuse to understand what is going on.