> if I was talking to a person who constantly used a phrase they liked I would notice it and it is possible I might get irritated by it

There are sociological reasons why this happens less with humans:

1. You cycle your dumb repetitive jokes with everyone you meet, so nobody hears it twice

2. Those who know you well will notice when you're just repeating ("dad jokes")

3. As a person's idiosyncrasies are beginning to wear on their social circles, they will be getting small clues to stop saying those things. Agents don't get these social between-the-lines cues to stop a certain behavior, they endlessly repeat. Perhaps between model version releases, frontier labs can harvest the web and ask "What Claudisms do people mention negatively?" but I don't think they do that yet.

I think that there is a sort of mechanism by which, when a human speaks to you, you can "mirror" their internal mental state, and the quality of writing often corresponds to how much you get pleasure or information or whatever your goal is from that mental state. The important part is that the words themselves are just pointers to the state. So, the person speaking, if they are skillful, gives enough words, and enough variety, that you can start to produce a state yourself which resembles theirs.

This is the thing that LLM writing doesn't really do. Since there isn't a mental state, there's nothing to mirror anyway, and somehow you can detect the absence of it even though it's hard to put any of the machinery into words. Corporate speech also fails to activate this machinery in the same way, but LLMs seem to do it more egregiously, probably because the corporate speech was at least compiled by a human---even if it is not the thoughts of an individual, it is the "thoughts" of an "entity", the abstract corporation, which the writer was speaking for, and so you can still wrap your mind around the fact that it is communicating with you.

> I am curious why LLM writing has such an uncanny valley feel to it.

Because they are HEAVILY trained to give addictive responses.

They don't want to just answer your question. They want to sycophantically make you feel like a genius for being smart enough to use them.

One reason is that one person’s idiosyncracies are limited in scope, but LLM-produced text is now everywhere. Also, filler words and mannerisms in speech we’re quite good at filtering out, but in written text the stand out much more.

I don't think its an inherent quality - a lot of older models had a much more natural feel to them.

I guess it has to do with the low temperature (low randomness in final word choce - something all vendors seem to have converged on for some reason) which does make them less likely to skiz out but makes the writing feel dry and samey. It's like repeating a list of dice rolls, and replaying them - there's no inherent pattern in the input, but there sure is in the output.

I suspect because the English colloquial text training data it had access to was early 2000's message boards and social media. Therefore it uses "honestly" and other expressions that took hold in the late 90s and early 2000s.

I had pretty good luck recently by giving it a writing guide about word choice, sentence structure, paragraph structure, and overall doc structure. I basically ask it to read the guide and revise a couple of times before I engage with its writing. Ymmv.

Think of it as a mad lib, it’s populating a template, and seeing the same template filled over and over gets tiring.

It’s the repetitiveness of style, the attempt to make everything seem as impactful as possible, the use of short sentences (too much Hemingway in the training data?), and obvious patterns like “it’s not this, it’s that” and several others.

Real human writing doesn’t follow such strict rules. When the same small set of rules is applied over and over throughout a text, it becomes obviously strange and machine-like.

I’d guess it’s because that’s exactly how its System Template was written to do

> I am curious why LLM writing has such an uncanny valley feel to it.

Because it's trained to talk like a marketing committee.

[dead]

Very surprised no one has this answer: because it is fundamentally not a human being.

Might be related to their fingerprinting of llm output they said earlier in the week.

I agree that it’s better at writing than a 50%-ile human, but it’s worse at communicating through writing than most humans.

Even an average human writer can communicate details much more succinctly and directly than an LLM

No, it does not.

My personal bugbear is its usage of "grain" where normally you'd use "granularity", if at all.

Belt and braces all the way down. They did their post training in British context?

Provenance

I've been noticing the same thing since 5.4- it starts with "Yes" yet I haven't asked a question. I think it might be related to the reasoning, like it's answering its own questions?

The watermarking is independent of the model. The model itself has the probability weights to determine the next token. The watermark is similar to things like temperature and top_p/top_k in that the watermark adjusts the probabilities in a deterministic way that changes over time to hide tells from word choices.

I think I understand what you are trying to convey but I fear you've made the same mistake again, this time with "soul" instead of "intelligence."

I think what you are getting at is that they are deterministic automata. They are machines. We have introduced randomness to add variation but it is an artificial randomness that simply perturbs the path traversed.

When we choose words it isn't because of a token distribution, nor because we rolled a die. We choose words because we feel a certain way, the external world, our body and senses are all connected as one system. These machines don't experience moods or get tired or feel better after a good night's sleep. They don't know their audience, we're all the same to them. We have no personal relationship nor can we establish one, as presenting some arbitrary background is not the same thing as a fluid, evolving relationship that accumulates through experience over time. There are no scars or fond memories.

If these things can truly be intelligent, to abuse your use of the word, then at least we are quite far from holding them correctly.

    Will Claude will act as a therapist or produce 
    value or produce a work of art? No. It cannot, 
    because it does not have a soul. 

Here's what I do think is interesting. You!

I mean... yes, you, too but not you specifically. The plural "you" that the english language lacks.

And so here's what I think is the actual interesting question. Might AI help you create art? Or be a therapist? Or something else interesting and worthwhile?

Maybe AI won't write the next great guitar solo. I'm pretty sure it won't. But might it help you learn to play guitar? Help you fix your broken guitar amp? Help you understand some tricky parts of guitar playing? Help you work through some tricky tabulature where you can't tell if you're playing it wrong or if the tab is just bad?

I don't know. But that's my angle for finding any of this interesting.

“It is not sharing anything, because it is not capable of sharing, because it does not have a soul”

soul.md though, just saying

Oh, that's interesting - because that's absolutely what's happening in my experience.

If I look at the thinking (which seems to have become unavailable in Opus 5 a lot of the time, but was present - and often useful - in 4.8/4.6) you're right - it's having the discussion with itself, and seems unable to distinguish that discussion from discussions with me. BUT it also seems to be related to the length of the chat - this seems far more likely to happen in a longer chat.

I don't understand why they have removed visibility into thinking - I found it very useful, not only for spotting things like this, but also because in more complex discussions it would often mention (useful) things in its train of thought that it dropped from its response - but if I said "when you were thinking, you mentioned this" it would then expand on that point. Taking that away is another thing that has negatively impacted the value I get from Opus 5.0 versus earlier models.

"Thinking" is just normal model output that's hidden from user. In practice it's just stuff in a <reasoning> tag or similar that gets filtered out from the user view. And thus it suffers from the same injection problems where the model fails to properly take into account what was the "source" of which block of tokens.

Yeah, basically everything that becomes context in a session will bias perception and communication style -- subagents, plan lingo, prompt lingo, etc. And then if you write a plan with the comms context having been biased, the lingo will creep into the plan, and from the plan into the code and code comments. And from there, bad lingo will go on multiplying like rabbits...

I usually think of it in terms of having a "good" or "bad" session. In a bad session, there is a harmful bias that you can only get rid of through a new session. For example, if you exposed too much context about, say, a variable that features prominently in a doc. The entire session will be anchoring on the importance of that variable. Or if you introduced the notion of CC having to ask for permission for stuff you will have a hard time getting it to "think on its feet" or propose an effective solution (you have made CC so insecure that it now relies on you even for little things that wouldn't normally require your input). In some cases (let's say you have important context in that session) you can overcome this by upping the reasoning level or switching to Fable, but usually a new session is the way to go.

Because it's so easy to bias the session I wouldn't even want to use any of these tools that pretend to give Claude "a brain" or "remember" things. That was en vogue a year ago and helpful then, but now, it's plain harmful IMHO. The key is to have just enough context.

Subagents often have the reverse problem in that they tend to have too little context to make "judgment calls", which is why the tasks for them must be either deliberately basic or mechanical in nature, or their output should be audited by the main session agent.

As for "thinking" it's not clear that that's even a thing (https://arxiv.org/abs/2510.24941)...

Yes. I've not used Opus 5 much directly, but when it was Fable and Opus 4.8, I found Fable did this all the time and it was maddening. It'd say stuff like "Oh, I mentioned that between tool calls" or something.

The constant memory wouldn’t be so bad if it weren’t dumb, wrong, and forced.

I hit the wall with it several times today trying to refine some text for a job application. The fact I considered doing babies first Rust project last fall lead to constant non-productive interjections and digressions about my supposed Rust skills and the Rust ecosystem.

Trying to create an unrelated spreadsheet to model an investment resulted in broad and incorrect criticism of my choice of spreadsheet tools, explaining in horrendous programming analogies why and how I’ve misunderstood how a spreadsheet works. “Think of the XLSX as a compiler…”

There has been a palpable down-step in communication & execution.

Would more blame this on the LLM companies, they think they are on the verge of automating all work, I don't think they care about how you feel about the writing style of the Deus Ex Machina, it's not going to get fixed because to them Claude is already above a staff engineer and soon going to smarter than any human that will ever live. All the money will be going into improvements relevant to improving long context operating and correctness, they could fix the writing style but they are disinterested in that for frontier models, maybe some other companies are but they don't have as much money.

Reminds me of current day politics. Lots of public statements which are obviously false, and you would think the politician knows they are false, but utter them anyway because they also know lot of their supporters buy what they are saying anyway.

Now politicians also know something about their supporters so they will adapt their statements to what they think they can get away with it. But, I wonder if this leads to a two-party-system where one party attracts stupid followers and another attracts the smarter ones?

In terms of AI, we might see LLMs specialized to attract more stupid audience and others meant to attract those who appreciate correctness and facts.

there's a wide array of assessments when it comes to reading comprehension. the one you refer to, the GRA, sets the 'sixth grade level' as whether or not a reader understands the author's main points, is able to answer conceptual questions related to the text, and then apply those to relevant situations. beyond this level is the ability to essentially be skeptical of a text and to know how to critically analyze it. so if your comprehension level stops before this you get 'big words in complex sentence structure sounds smart and right so it is smart and right' even if the reasoning and process is poor

it makes me think about how people engage with movies and television - as passive, plot-and-character driven consumption (eg I hope Walter White survives) with no critical analysis of how and why the writers added ABC thematic element (eg Walter White as a motif of a toxically masculine narcissist with specialized knowledge as a larger critique how mass media tends to valorize their male leads in the same vein as many other prestige shows at the time like Mad Men), and the larger, downstream sociocultural impact that piece of media has on how people see the world (eg people who now have the Heisenberg tattoo, unironically)

there's been some musings on why this the case like Hofstadter's Anti-Intellectualism in American Life - the valorization of obedience and trust in hierarchy and the state are net wins if you're an institution that seeks to increase it's power, whether religious or governmental. I was talking about this with a few friends the other day and it's a dismal future reality where not only did we make anti-intellectualism normalized and politically legitimate in the USA (eg Fox News, clickbait articles, and all the other forms of yellow journalism that have emerged), we now have tools by which individuals can even further remove themselves from having to critically engage with thoughts, feelings. I heard a story about how someone scanned a group activity at a baby shower into ChatGPT and had it answer for them instead of, well, socially interacting with the other guests and forming a memory of the moment with their friends

the counterargument to that might be that Claude/ChatGPT/etc have more epistemic rigor than your average American (sure) but the sycophancy of modern day LLMs is an actual danger that enables more harm than good. it does seem as if Claude is the only one interested in guarding against some small amount of it (though to the detriment of people just trying to get work done. as an aside, I get the feeling Mythos was intended to be the bespoke enterprise solution without the guardrails but the Anthropic marketing department or some power-hungry department lead made it about how dangerous/effective it was from a security perspective which threw a wrench in things). but then I think about people like my parents asking ChatGPT which specific house to buy in their retirement only to later find out the house was sold weeks ago, or just in bad condition, or in a neighborhood where the housing value has already reached equilibrium, it makes me think about how it's not enough and the future is bleak

I'll also say that I think Claude sounds the way that it does because it, like many other LLMs, are RLHF trained largely by lowly paid gig-workers, many of them ESL speakers. if their trainers were, for example, dedicated and highly trained academics, scientists, and other researchers, you'd likely see a lot more concise and more importantly skeptical reasoning and responses. but that won't happen in our current reality of capitalist-driven development so we get encoded solutions like MoE that still largely depend on the messy, imprecise RLHF training at baseline

in the right hands, I do think AI is a wonderful tool. one of the first things I did with it was to create a research skill that reviews white papers from the lens of someone who knows how to read/interpret research methodology, is aware of things like p-hacking, and deterministically assigns weight according to the hierarchy of evidence. even still, I'll still read the studies because there's so often nuance that's missed if the sub-agent read only a search snippet but that takes effort, time, and the practiced knowledge of critical analysis to even want to do it

Better start chinamaxxing

Probably Mongolian

Incidentally, according to https://gpt-tokenizer.dev, in gpt-5, "literature" is two tokens ("liter" + "ature"), whereas "文学" is one.

Even more so than borderline incoherent academic writing like Foucault or Lacan or whatnot, for that matter. It’s less “I don’t understand this and I suspect the author doesn’t either” and more “reading this feels like having a stroke.”

Mad amounts of respect for that.

The decision was not out of just complaints: we already had someone fired during the probation period because they were unable to write stuff without AI and were just shoving slop at developers.

Not a technical person using AI for PR descriptions, mind you, a product manager unable to write tickets without asking whatever software to do so.

It's amazing how crazy humanity devolved into pure slop.

I had people on teams who wrote like pre-LLMs.

The best trick I have after asking it nicely in all sort of ways is:

1. Have it build a scoring script that penalizes words outside a simple English list and approved jargon. Penalize sentences over 15 words as well. Add whatever else.

2. Run it in a loop to reduce the score while preserving intention

This works much better than other ways I’ve tried. Of course it costs more. And I would apply it only to the output to the user, not the thinking process (I think the AI thinks better with their crazy English)

Of course, sometimes nuance is lost by this process. That’s just the nature of making things simpler.

> CLAUDE.md is mostly powerless against the reinforcement learned crap.

When you dont know the cause, you dont have a fix. Thats the biggest issue i have with all of AI is that we dont know how it works, and yet we think it will be great ! This is more like a religious belief than a scientific one. There is no causal model of how it works, there is no theory. And the temerity to call it intelligence is annoying.

Yes.

CLAUDE.md only works half the time, except in longer conversations, when it works about 10% of the time.

Hooks are also useless in the sama manner, the agent learns to dodge “no comments” hooks (why is it adding them anyway?).

Hooks to append text to your prompt reminding the agent of certain rules are useless.

Claude does whatever it wants, when it wants, the way it wants

Claude Code has an "output styles" setting that supposedly directly modifies the system prompt:

https://code.claude.com/docs/en/output-styles

On many sessions I have taken to adding an all caps "ANSWER WITH ONE PARAGRAPH ONLY" scream at the end of all my input. It's the only thing that gets results.

You would hope? Really really hope? that they could observe this, and target it?

Like, Claude going off the rails isn't something that takes a lot of effort to demonstrate. Literally anybody with a CLAUDE.md has seen the behavior over and over and over.

Hey Ants, can you maybe just not release the next version, no matter how good it seems on benchmarks, if it can't follow the goddamn instructions? Please? This seems trivial to test for and yet here we are, being gaslit by lying machines who intentionally do not do the requested work over and over and over and over.

I fully and completely expect a mental health crisis among developers. Being lied to constantly cannot be good for us.

Constant vigilance! is how you get developer PTSD and inability to believe anything you're told. Add the stress of parsing through yet another hyperverbose paragraph of bullshit while having your job threatened? People are not gonna end up in a good place, and this is as inevitable as sunrise.

Try spacing them out instead. I.e. a mini-workflow with a self-review step. Works for both planning and coding.

Yep, it might work for one or two turns but I see it regress pretty quickly with instructions and/or CLAUDE.md. It has to be deeper.

What has worked reasonably well for me so far is not trying to stop it from writing its inane walls of text in the first place.

Let it vomit it all out, then have a /tldr with instructions to make the last answer concise and intelligible

What are you gonna do? Fire it for not listening to instructions?

It defines and introduces a lot of concepts/acronyms in the thinking blocks which we normally don't read.

I wondered how far back the usage of that term went. I was familiar with it in patch, so I did a little digging and found it in the v1.3 (1985!) source by Larry Wall: https://groups.google.com/g/mod.sources/c/xSQM63e39YY

"seam" is apparently... according to Claude itself a term from 'Working Effectively with Legacy Code' by Michael Feathers which I have not read. All it took was for one sub agent to use this term and it stated using it everywhere all the time. I have not read the book and prefer other terminology but it only takes 1 sub-agent or 1 usage in the context before it poisons everything else.

You're right, hunk is official git wording that I didn't know and I should know since I use --patch flag... It's just that I never heard a human (including online) reason about hunks. While at the same time (from my observation) people say things like code chunk, code snippet etc. a lot.

I'm not talking about model performance. I just mean the UX of Claude Code. I'm trying to use pi but there are so many paper cuts. Of course you can configure everything but that's a ton of work. Claude Code has pretty good defaults.

Bit of a tangent but at work we have GitHub Copilot and the VSCode harness is somehow night and day better than whatever happens in the IntelliJ plugin. Aside from having better features, for some reason prompts seem to be cheaper as well.

I'm not sure I could really live down using something branded with Grok but it makes sense Elon Musk at least shipped user facing products in the past, not surprised his company delivered something more usable.

I don’t think it’s even that. It’s its own special flavor of bad writing.

And sometimes its not simply poorly written. Sometimes its just totally incoherent.

Probably to a degree, I have found Gemini to be the least dis-likable of the models from the big 3 on that front. I wonder if the poor English comprehension of Deepseek-v4-pro and K3 is because of alleged distillation of Claude (speaking of why doesn't anyone distill openAI, are they just dramatically more competent at stopping API use that breaks their terms?).

V4-pro in particular seems very capable, but will just dramatically completely misunderstand user intent, it seems almost like it wasn't trained at all on non LLM generated instructions mid conversation.

They have written like that when the models were much less capable, my hypothesis is this is an example of model collapse happening ever since LLM training leaned in heavily into RL and a result of training on model output the developers are uninterested in correcting since they want ASI not a somewhat useful AI coding tool that supplements humans without replacing them in the economic system.

> the behavior is meant to have you shut up and trust it and not ask questions

This seems to be exactly the kind of thing automated/massive training would produce, just like it did with sycophancy recently.

Claude users would just gave up after the word vomit and some classifier considered it a success and into the model it went.

Wrong incentive and nobody checking.

The watermarking is going to get rolled back or Anthropic is going to get rolled. People hate it and it makes the writing worse.

Oh man. Hadn't even considered the watermarking angle.

Brilliant way to get people to waste tokens.

Maybe just don’t generate garbage in the first place?

No, I’m not interested in fighting my model all day long. Plus is fucking annoying to talk to and collaborate with, so I’m not using it when Sol 5.6 is about 1000 times better in that regard. I have colleagues who spent a lot of time trying to improve their harness with user rules and whatnot and Opus really does not want to follow them.

Yeah but Sol shows it is possible to just send the readable explanation in the first instance. And I don't want to spend tokens and time on asking for a better version of each response.

When I ask it to make a CL description, it's worthless unless I tell it to dumb it down as much as possible, assume the reader has zero knowledge of the codebase. And then it makes a perfectly cromulent description that just needs a touch of trimming-down. If I don't do this, the description is just a wall of gibberish and paraphrasing of every little thing it encountered.

Yeah my trick is "Restate concisely"

Just those two words. I use it A LOT recently.

I've tried telling it to "fix" comments with varying degrees of specificity and in my experience it just... fundamentally doesn't get it. Presumably using a different model for it would help.

My theory is that Claude's learned approach to comments is to treat them as a sort of persistent in-band thinking trace, or a "memory" tied to an in-code location, which is a little at odds with the way humans use comments (human comments are intended to be read and understood by other humans, whereas Claude comments are their own dialect).

I bet this is a result of iteratively training Claude on output from other successful Claude sessions. Presumably it's good for making benchmark scores go up.

I built my own skill to somewhat follow the Simplified Technical English guidelines (loosely adapted to my work context)

The problem I’ve been finding is that you can do this but within a few messages, the instructions in the skill will be ignored.

Absolutely infuriating if you’re using Claude in an environment where you can’t run hooks.

Funny, I'm the same. And if find Sol way more pleasant to work with, not to mention way faster. And Sol's compacting is superior, I haven't yet run into it forgetting something crucial from the pre-compact conversation, meanwhile Fable does that notoriously.

When they eventually make Fable available to cheapest plan, I'll downgrade. It's worth keeping for reviewing the code and the UI tasks, but nothing else.

This is hilarious - this week Claude’s writing was getting so bad I had this exact comic come to mind.

Briefly considered adding “Verbing weirds the English language - stop it!!!” to its instructions.

The is latters.

I think you're misunderstanding me. I'm saying "It gets paid by the word and you get back walls of text." - ie, what you don't want to think is happening is very obviously what is happening.

It charges by the unit and it decides how many units it produces. It decides how much money it makes, therefore it decides "more".

English, motherfucker. Does Claude speak it?