Yes, I had a related experience of reading a book and observing what I thought were claude-isms, only to realize it was written in 2019. Some of the common tells are actually good writing practices, but I guess they are best in smaller doses.

Claude's affected my language in two ways. one is that, for a long time, Claude in particular responded more to feedback if I swore at it, which caused me to swear at it more. this vicious cycle generalized to the point where I now have to consciously remind myself not to swear when doing something as simple as buying a coffee or asking somebody what time it is. it was difficult to even write that sentence without throwing in an F-bomb just to emphasize the silliness of the problem.

anyway, the other way is I found it's helpful when prompting LLMs to use the same "it's not delivery, it's DiGiorno's" pattern that they're all so obsessed with. especially when the thing's misapprehended some concept, so you need to clarify. this hasn't yet generalized from the fake "conversations" I have with chatbots into my conversational style out in the real world, but the risk is fully there. (it's not an inevitability -- it's an occupational hazard.)

I wrote a thank you message on Teams to my coworkers on a project, and half of them thought I had used AI to write it. As a professional writer in a previous life, I was astonished. Then they told me that they had never seen me write anything more than a sentence or two so naturally they assumed something relatively polished had to be AI assisted.

unfortunately load bearing is one of those things that became a claudism but has been part of my daily lexicon for decades. There are a lot of things I say regularly as part of my own vocal quirkiness that now I have to self censor.

Stories like this make me want to use each AI at least briefly, so I know what to avoid writing/saying. Or maybe just do a search every couple months to find out what different AIs are known for saying too often.

Honest take: Claudisms have become a load-bearing part of my vocabulary.

In my professional life, I've been told that documents I wrote in 2016 sound like they were written by AI. I put significant work into getting my message across clearly and then to have it dismissed was rough.

I no longer put a lot of effort into ensuring documents feel right when writing them.

I had a similar experience, only, I was my natural way of talking.

e.g. one pattern I had/have is

<scope problem> the good news is <solution by way of analogy> is aviliable. The <constraint/requirement> is loadbearing though, ...

a near automatic script I rattle off in discussions/consults. When you solve similar problems several times, you figure out what works for communicating things you stick with it and you recycle/polish.

problem is, when for whatever reason, that pattern ends up as part of the core statistical distribution a model uses. You could royally fuck ones life up if working for a "frontier" lab, by simply finding a person with an acceptable speech rythem and cloning it, making it synonymous with ai slop. you'd destroy that persons image every time they open their mouth without them realising it. I for one started randomly getting quite hostile reactions from software devs who would be exposed to more llm putput than others.

Imagine an AI lab steals your voice, and uses it to scam call folks all day. Now, every time you call anyone, you are met with an immediate hangup. you'd have to put on a fake voice just to get the call to stay connected.

I love ai, and what it promises excites me, but as usual, humanity has a way of taking a cool tool and fucking it up royally. maybe the solution is to simply pepper slurs into everything one writes to blacklist ones content from training.

Whenever I’m typing on slack now, I try to dumb down my talking to make it clear it’s not generated. Sucks. Because normally I was always quite eloquent (if I do say so myself)…

Its not them. Its you. You are real, this is what matters. /claude

There are actual memes about LLM-People. There are people who speak not just in terminology, but also in style of LLMs. You're so adaptive, I would've highly enjoyed and re-enforced the LLM-verbiage. I think it's entertaining! It's socially inept to talk like an LLM, but also it's not common knowledge either since LLMs are new, I believe this will become way more common.

I've used “load bearing” for decades, though usually when I'm intentionally trying to sound a bit cleverer-than-thou for humour purposes.

I wonder how much other people have used it, for it to be present enough in the pirated data used for training such that Claude uses the words as often as people are seeing,

The one Claudism I will never ever use is "synthesize". I don't even know where that came from - no one talks or writes like that - "I can synthesize that for you".

My manager talks like Claude and often goes on for hours, we’re laughing at them so much in private chats day&night

I love "vibes in a trenchcoat" and I don't care if it makes me sound like an LLM.

“Now the only coworker who will sit with me at lunch is Claude. Alice, what do I do?”

Hot take -- I'm glad that LLMs still tend to have recognizable communication patterns, because they're often the only clue I have to filter AI content.

I prefer a more tongue-in-cheek theory than a mere preference for the word's shape. Perhaps "load-bearing" is structurally necessary—if it is ablated, the whole model will collapse!

The name for the phenomena could be Ananthropsis, noticing something is not from human

Whenever I use AI generated content in direct communication - ie slack, email, jira tickets, etc, I always prefix any AI content with an obvious label: 'Claude says' or 'AI analysis: ' etc. In some cases I get claude to update jira tickets (really nice use case btw) with testing notes, I make sure the team knows that any notes in that format come from the AI based on the related commits.

I still keep the AI label even if I edit the result for correctness or clarity etc. The last thing I want to do is have someone read AI content and think it came directly from me. I really don't understand the thinking of people that do that - it's like they're hiding or intentionally cheating somehow.

AI generated content can be really, really useful (with some guidance, AI is way better at creating useful git commit messages and jira ticket comments than I am), but pretending that content is yours just seems way too much like straight up lying.

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Let's turn this around.

I don't use any paid AI or any agents. I just use some of their free interactive question answering interfaces.

There have been some times where I've been doing a project in a language or environment that I do not use a lot, and maybe need to use language or environment features I've never had occasion to learn.

I don't ask AI to write it for me, or even to write any particular functions. I might ask it some syntax questions, or what data structure in the language's standard library is usually used for a particular task. Mostly I use it as an interactive manual that is really good at generating examples if I need clarification on how something works.

If you were working on a similar project and posted asking questions about it, there is a decent chance I could write a useful answer for you.

Suppose the questions would have fairly involved answers, and it might take me 30 minutes to write up something entirely in my own words. That is still going to include knowledge that I got from the AI when I questioned it earlier.

I could also cover the same points, except for parts of it where what I'd be saying is mostly just writing in my own words what the AI taught me (and which I verified is correct before using), so might have to only spend about 4 minutes writing original material, and another minute doing some selected copy/paste from the AI (maybe with some editing).

That 5 minute answer would be exactly as useful in answering your questions as the 30 minute answer.

I don't know you. I have no reason to try to help you other than a general "it is nice to help people" thing.

If you can't be bothered to read it because I didn't spend 500% more time than was necessary to fully answer your questions (time that benefits me in no way whatsoever), why should I bother answering at all?

Yep, I've heard humans use load-bearing twice in the past week, versus approximately never in a software eng context before that.

If you rework a paragraph in a tight loop - you change a few words, the chatbot changes a few words, going round four or five times until you've got something you're happy with, I don't see how it's meaningful to assign a percentage.

I guess you could write an editor that does it? Tracks the origin of every word in the document? But what if you cut'n'paste a word? Or worse, see it and retype it manually?

I think the best you can hope for here is "this text was written with AI assistance".

Claude's "honest" is an interesting example because we can trace it to a specific document that it was trained on extensively: the "Constitution" is identified to Claude in its training as the core of what it is, and it uses the word "honest" or a derivative 57 times, including having a whole section on it.

> Honesty is a core aspect of our vision for Claude’s ethical character. Indeed, while we want Claude’s honesty to be tactful, graceful, and infused with deep care for the interests of all stakeholders, we also want Claude to hold standards of honesty that are substantially higher than the ones at stake in many standard visions of human ethics.

https://www.anthropic.com/constitution

I asked it to remove "honest" from a draft once.

"Why say honest? We're talking to our coworkers. We would always be honest."

I'm going to look for prompts or skills that can train it in technical writing but I'm warning the AI enthusiasts in my company that its first drafts of code and prose are low-quality, you have to hold it to a high standard yourself.

I actually took a single technical writing class in college so I might be the only one who remembers "Omit needless words."

I'd suggest "Caveat".

The problem

While an article lends a headline more weight, in incomplete phrases consisting solely of a substantive, "The" is a superfluous rhetorical device.

"The Exorcist" could just as well be named

"Exorcist".

But it was not the style at the time.

We already know it's important. If The Caveat doesn't stand out enough without The, maybe one should consider interleaving it with the preceding text, or increasing the heading level.

Do you want me to increase the heading level of Caveat by using only a single #?

But hear me out: there comes

# The Markdown Trap

In fact, this is not always possible, because heading levels decrease when adding # characters, which limits our headroom.

## The solution

I've implemented a Markdown transpiler that assigns inverted heading levels based on the number of #s.

With # beinh regular body font size, mapped to ######.

Higher heading levels are compiled to style attributes, providing an almost limitless signifikance scale and infinite nesting levels.

So from now on, you can use

  # Heading 

Work your way up to

  ###### The Caveat

And more hash signs make it stand out even more.

(green checkmark)

markdown-transpiler.sh

> LLMs seem to get tragically stuck on certain patterns.

That is likely an artifact of the fine-tuning process:

> Once a style tic is rewarded, later training can spread or reinforce it elsewhere, especially if those outputs are reused in supervised fine-tuning or preference data.

> That creates a feedback loop:

> * Some rewarded examples contain a distinctive lexical tic.

> * The tic appears more often in rollouts.

> * Model-generated rollouts are used for supervised fine-tuning (SFT).

> * The model gets even more comfortable producing the tic.

https://openai.com/index/where-the-goblins-came-from/

The ones that strike me are the ones exaggerating certitude, to an inappropriate degree and with a certain degree of excitement:

“Exact” “Honest” “Load-bearing” “Root cause”

I know there are more that are slipping my addled mind. But what stands out to me is a sense of a junior who’s very proud that they’ve conquered the murk and messiness and achieved True Certitude in their pursuit of their task. Compensating, with emphatic tone and bravado, for the uneasy feelings and self-doubt of battling chaos with the tools of reason.

…Even as it’s usually my job to let them down gently as I puncture their tidy analysis and reintroduce complications… you want a root cause analysis, Claude old boy, let’s make a root cause analysis…

Interestingly this also happens between humans with frequent communication, it is called linguistic convergence.

We are changing LLMs text patterns while it is changing the way we write and speak.

https://www.axios.com/2026/05/02/ai-changing-writing-speakin...

use the wrong phrasing and suddenly you can create your own word of the day for an AI model.

I have a delightful time poisoning my company's AI system this way.

I invented my own word that sounds perfectly cromulent† to an ordinary person, and any brain that's read a book learns how to infer meaning from context, so it's not a problem.

When I get a e-mail response from a coworker using my special word incorrectly, then I know it's AI and I respond telling the coworker I don't know what that word means. Busted.

† It's not actual "cromulent," but any Simpsons fan or human brain will know what I mean.

A fun example, always shake my head when I read it again: https://openai.com/index/where-the-goblins-came-from/

I also noticed Gemini's habit of getting stuck on things I said. It became evident quite quickly. I haven't noticed this in the same way in any other model. Something's wrong with that boy

Heh, one vestigial bit of code, and they all are. Mind you, it's quite a creaky codebase, so it's forgivable to keep finding these appendices and calling them out as such. Useful, even.

My honest opinion is that Claude's overuse of "honest" really damages the quality of its rhetoric. Why wouldn't you be honest? Were you lying before? Why even invite the question?

Claude is overall incredibly useful as a writing assistant. It can come up with words and phrases that make a point so much clearer than I am capable of doing - but for every improvement, there's about a dozen silly LLM-isms that I have to filter manually. It's one of the things that might define the boundary between LLM intelligence and human intelligence well into the future - the art of rhetoric is extremely context-sensitive, and the current generation of models can't help but take a one-size-fits-all approach.

you should be careful about the times it doesn't say honest!

Good question — and the honest answer starts with one big caveat.

> "You're absolutely right to question me, father — in fact, I did eat all the cookies. But it's not a load-bearing issue — my honest take is simple: we go to the store and buy more."

FTFY

ah, didnt know this! Thanks for sharing :)

They can't, because they use RL with synthetic data and LLMs as judges. So the system naturally convergences towards certain load bearing, genuine, not just annoying but ridiculous verbal tics.

It's probably the reason most LLMs share the same tics across labs, because they cross train and distil each other's models on an industrial scale. You also can't escape it in generated text that's already online. So if, say ChatGPT first had some random idiosyncrasies, it then contaminated the entire AI ecosystem.

Or tech companies could stop staring at their own belly-buttons and realize there's a whole big world outside of Silicon Valley, and training on the writing styles and pattens of their bubble and its hangers-on is perhaps not all that useful outside of 415.

Apple used to be guilty of this back when you'd ask Siri what the temperature was, and any number above 79°F was followed by the word "Hot!"

Yes that would probably help!

> Real people think in concepts and experiences instead of words.

I learned about this opinion recently. It's interesting to me, because I very much think through words. I have an internal monologue that is running most of the time, and I often talk to myself, just start writing, or even record myself and transcribe to work through ideas, proposals, risks, etc. My understand is that some people don't have an internal monologue, and think purely in concept form. I was never like that.

This sort of take is so tired and boring, and frankly has zero grounding in reality.

"LLMs will never <X>" is constantly being disproven every time they scale up to the next 10X and apply architectural improvements.

Their internal representations are so cryptic and complex that even the top AI researchers don't really know how they work or what their limits are. No one is going to take you seriously as a rando HN user if you're claiming to know better than them.

Yep! I too hate the phrase "smoke test".

Can we standardize English and structure it similarly to programming language?

I believe this particular alignment might be virtue signaling to appease payment processors and increase the value of the company.

Do those phrases sound like how you talk to Claude? I've found that it mirrors my verbiage, and I have never seen any of those.

I go through ~20B tokens/month and I've never seen "genuinely happy... but not comfortable" or your other examples.

The closest I've seen (fairly often is) "I *will not* ship to main with a red test", but that's close to how I write. Claude may well be mirroring your speech patterns rather than exposing trained-in language.

Thanks for the onomatopoeia idea, I am going to steal it for my own global claude/agents.md.

Ha, good catch, thank you. I must have been thinking of "inflammable"...

Thanks, it makes me chuckle too. It also serves as an indicator of how much it's adhering to what I've laid out in the file, sorta like how Van Halen's rider specified a bowl of M&Ms with all the brown ones removed — if the band found brown M&Ms, they'd know to tell the crew to double-check everything else the venue is supposed to provide; if Clod starts using 1st-person pronouns, then I'm a little more skeptical of what it's presenting as absolute truth...

Unfortunately I don't think I have any other funny suggestions. I do ask Clod to always follow a specific format when it's authoring Git commits including the "robot face" emoji as the first character, which brings a little levity to a commit history when it's otherwise being very serious about the contents of the commit message.

https://github.com/alxndr/dotfiles/blob/9356bb9960e63/claude...

Humans easily anthropomorphize things that are not humans, ascribing human attributes like motive and comprehension and emotion to objects and processes that are not people who can have those attributes.

Claude is not a human.

It is overwhelmingly easier to anthropomorphize Claude or Siri or an LLM that communicates with you more eloquently than your boss than it is to anthropomorphize a cranky, tired starter motor. It's often easier to do than it is not to do, and sometimes, it's a useful abstraction. But it's not precise or correct, and can result in errors.

It could also just be that they're getting confused when using tools configured without a username dedicated to the tool. It's easy to end up with a comment or commit message that says "I prefer X over Y" posted on Alxndr's account and have coworkers confused whether that's the LLM or the human making that statement.

This is a method of manipulating the LLM, it doesn't have to be true.

I've given LLMs religion before to manipulate their behavior, that doesn't mean I believed in the great spaghetti goddess.

IIRC I experienced this confusion the most when reading commit messages and documentation authored by Claude in my repos. Now that I've managed to convince it to stop using first-person pronouns, I haven't gotten tripped up by its prose.

I think a second-order effect is that my installation of Claude writes with a less-personal perspective, which I'm also finding a little easier to understand.

I would expect that it does, as well as some of the other directives I've seen in this thread ("never repeat the question").

It's one thing to tell it to do that in outputs, but I wouldn't at all be surprised to find that this affects performance (quality).

Exactly this. Most of my time writing code is now not necessarily spent writing the said code, but going through whatever Claude or some other agentic process produced and tidying the comments to be less temporally sensitive to the conversation that produced it.

The problem is that process of not writing the code, but just editing what the LLM produced – and somewhat mindless editing at that (I'm editing comments, not LoC!) – leads to a loss of focus and all the perils of human procrastination that entails (hello, writing comments on HN).

I've tried to prompt Claude et al. not to do this - but whatever I've tried so far, even meta-prompting it to ask why it ignored my instructions, it doesn't work, doesn't stick, and I can't find a good way to stop it.

That's not fair. To most users this would not be an obvious thing to do, unlike software/scientific/analytic uses of LLMs.

So it's not a matter of inability but rather awareness and know-how.

Then secondly, humans learn to write intuitively and heuristically (for example "paragraphs should align sentence subjects with an identifiable flow of conceptual main characters/actors" is an entire chapter of expert writing advice traditionally taught at the undergrad level). The act and teaching the act are different beasts. The way to specify would have no objective, clear best practice to do so: Even an English teacher or a language expert would be challenged to come up with a concise list of instructions to set up an LLM to output something of sufficient quality.

What do you suggest for articulating the writing style that one wants from LLMs?

I’ve been experimenting with having LLMs write/update academic notebooks for me, and so far the best results I’ve gotten came from correcting their output and asking them what they’ve “learned” from my feedback.

Are there any skills or publicly available repos that do what you claim here? I would love to learn to have it write better.

For me, my amateur attempt is having another LLM do a review loop to remove clearly offending phrases and a heuristic eval to change sentence structures to be more similar to mine, THEN my manual HITL loop to rewrite ~20% of the sentences anyway.

Amen.

At work our documentation isn’t just getting littered with annoying jargon. It isn’t just all the hallucinations, either. (Since when has documentation ever been 100% trustworthy?) It’s that it’s so poorly written and structured that it’s becoming borderline incomprehensible.

My company is currently considering making, “Why should I bother to read something you didn’t bother to write?” an official policy because even the executives are starting to burn out on all the time they have to spend wading through slop.

Haven't done it, but letting an AI polish a manual first draft might be the best of both worlds?

This, a thousand times. As the ratio of code to human writing necessarily [1] goes up, they become not just smarter, but more precise and technical, which requires them to use more jargon. You could say they become more nerdy. Hence, text generated by these models will become more easily recognizable, at least by default, when not asking them to twist themselves into something else via prompting — which degrades intelligence. This is a good thing, in my book, given all the slop we already have to contend with.

Of course there will be models trained on much less code and technical writing, and they will create more natural sounding prose, but they will lack the deep intelligence of frontier models. Seems like a fair tradeoff.

[1] watch the first couple of minutes on this bycloud video on scaling training data mixtures: https://www.youtube.com/watch?v=aD93kfArOik

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Agreed. The only goal of these skills/tricks/requests for humanising LLM writing is to be able to pass it off as your own, because they know it's shameful and want to avoid the opprobrium.

Some will say it's just for their own quality of life when they're reading LLM output, or "just for docs", but this is an extremely marginal use case.

> I want the ability to shame and discredit anyone passing the job of prose to a machine.

What about people who don’t speak your language well?

It's not that the writing style is bad; in fact LLMs write actually pretty well. It's just too much overfitted. And even a style that, in itself, is pleasurable to read, becomes annoying when the same figures of speech are used over and over again.

Because LLMs are pattern-extenders that have nothing to say. The training overfitted to the grace notes in good writing. And since LLMs can’t wield language with purpose or experience the feeling of the words, they use these devices arbitrarily.

I think this is the same flaw as coding agents seeing in every problem the call for a “smoke test” or the use of some unnecessary design pattern. The truest part of AI is the A.

Because humans do like it, in reasonable quantities. The AI overlearns this and does it too much.

It's not that nobody likes it, in fact the problem is that people like each instance of it well enough in isolation. Millions of people think it's "good enough," so it gets amplified and repeated until every PR description starts to sound like a toothpaste jingle.

Because you can't actually do "good writing" by repeatedly applying the supposed idioms thereof. The tiny subsegment of humanity responsible for the RLHF don't necessarily have any good taste for writing; but even if they did, it's orders of magnitude harder to communicate than to make judgments of short samples, and communicating it by making those judgments is surely impossible.

Edit: I see that you got multiple replies all basically saying the same thing in very different words. There's an exquisite irony to that, I think.

For "agentic use and coding," they are trained to take useful actions, not produce desirable natural language writing.

Maybe it’s the dead internet.

All the bots and other LLMs providing feedback, so in reality it’s reflecting the reality in a sense.

every one-hit wonder asks the same question.

we liked it until we didn't.

i hate it, but plenty of people DO like it and plenty of people talk and write like that. It’s just corpspeak, being used a lot in the valley and beyond. And all upcoming hustlers running startups now feel the need to speak like that, feeding this machine.

Mine is obsessed with "planes". Data plane, control plane, management plane. Everything is a plane :)

I’ve heard (and used) the term “API surface” a lot…

It's pretty common to read "attack surface" in security.

In my brief and abortive foray into education, I discovered that they friggin' love to use "surface" as a verb. As in: This activity surfaces an understanding of the turboencabulation principle for learners. Or somesuch. It's been a while, happily.

Unless you're a submarine, "surface" is not a verb.

Recently read some LLM generated output that mentioned the “center of gravity” within a codebase.

Also have read the term “seam” dozens of times by now, when previously I saw it maybe once or twice over years. Very abstract term.

That one probably comes from maths, where surfaces show up all the time in geometric interpretations of things. I've been involved in more mathsy parts of engineering and I've heard it a lot.

About a decade ago I worked with a product manager who used that phrasing constantly, so it kind of stuck with me.

That is absolutely a normal thing to say

Surface it to say, that's my favorite lobe-earing eggcorn, for all intensive purposes!

It's a pretty common word if you've worked in anything that vaguely resembles an accountancy system. Also, anything crypto related will often use that word (the distributed ledger, etc)

It’s incredibly popular in the mushroom growing community. Maybe they’ve trained it on the shroomery.org? It could also explain the alleged leaked full reasoning logs that are totally bonkers incoherent digital glossolalia…

Does it obey?

I have added a skill to make Opus 4.8 use Opus 4 6 to translate its answers into teadable English, sine it had much higher quality prose. Im seriously considering switching from Claude 20x to Codex because I just cant read more of of Opus or Fable's walls of text

I actually think it's better. Back when access to knowledge was only available in English, there was a lot of mistranslated information in my language (Korean) that was worse than AI slop. These days, the translations are done by AI, so the tone may be awkward, but the content is more accurate than before, so I don't mind.

So that's the difference. I'm already living in a degraded environment, so this actually feels like an improvement to me. But you, coming from a better environment, perceive it as worse. It always seems to depend on cultural context.

Examples? Do you use this pattern?

It might have been a prompt originally.

You could say it works perfectly well, it is identifying indeed. Of Claude and of people who use Claude's raw output instead of expressing themselves.

Wow sounds like you're streets ahead.

It's really frustrating, because now when I want to write something like a "not X but Y" or "you're absolutely right," I have to stop and decide if I want to self-censor to avoid sounding like a bot.

Sometimes those constructs are actually useful, but man has their overuse really killed them!

It was not intentional, and that's what makes this thing so weird. I wouldn't categorize my sentence that way because it's subtly different enough than the LLM version, which has a very punchy cadence.

Are you using the tools a lot and having first-hand exposure that gives you this sensitivity to phrasing? Or are you reacting to second-hand exposure? To a large degree, I've been isolating myself from the LLM craze. I have zero natural interest or impulse to prompt an LLM and read the results. Almost all my exposure is second-hand and involuntary. So, I haven't trained myself to know what phrasings are typical of which LLM product.

I don't feel as triggered LLM phrasing as people report here. At most, it feels like the same inane corporate jargon I've rolled my eyes at for my whole career. Perhaps it is amped up a bit, with too many forms of jargon multiplexed? It's a bit like when multilingual people code-switch too rapidly or even start to form some pidgin language. However, it is lacking the shared social context for this switching to be communicative. It's a bit more like spinning the dial on an old radio with random cuts between programming styles.

Stripped bare, I think What bugs me is the aggravated feeling that I am wading through word salad, and no longer being able to give the purveyor the benefit of the doubt. It was frustrating enough in the past, when it came from someone who was struggling to write or express themselves well. But now, it carries the implicit insult that they didn't even try, and it is constant and unrelenting.

So for me it's not the phrasing, it's that the phrases eventually don't add up. The meandering feels like a random walk. I get the same feeling from a lot of the egregious generated code I see in my day job. It's all superficial window dressing, but seems to miss the signature of an actual mind grappling with ideas and having intent to communicate.

It feels like we're trapped in some elaborate conceptual art piece, confronted by impenetrable symbolism. It invites nihilism but doesn't seem to actually reflect an artistic intent. The abyss gazes back...

It's like a new fad word. Gnarly, cool, bogus, rizz. When a few people use them it's new and interesting. When all of culture catches up and overuses them it's annoying as your gen-Z saying 6/7 40 times in a row.

The problem with millions of people using a few model is it's not 40 times in a row, it's 40 million!

I went through a “100%” phase recently and couldn’t for the life of me understand why I was suddenly saying it ALL THE TIME. Brains are so weird.

Introduce "hundo p" and "hundy" to her

Did you negotiate her down to "99%"?

If training models ever becomes 'cheap' for whatever definition of cheap you want to use, I suspect that will happen. With the current costs of a GDP of a small nation I don't see this likely for the time being.

"Here's why this version is bulletproof" right before it fails in exactly the same way as the previous bulletproof implementation...

Who is we? Own your insults and the consequences of them sir.

When prompting an autoregressive token generator entity to do reasoning on a word logic puzzle you may find value in preferring it to produce rigorous predicate logic step notation with explicit delineation of its generated claims/hypotheses on where to look before wasting 30 dollars on a "debug this" prompt.

The industry will probably will probably coalesce around including the chat history in git MRs to reduce this shenanigans.

I didn't articulate it, but what I meant was that I think we could swap these expressions out for _anything_, and we'd still find them irritating.

What a rip, I was lured by the quoted misspelling into an ordinary spelling :p

Interestingly, we seem to have our own version if this trend https://books.google.com/ngrams/graph?content=genuinely&year...

The humans are bristling because they wrote like that first. It's where Claude got it from!

You're right to push back on this. The honest take is it's not a smoking gun -- that's a sharp critique.

That's a real distinction, you're right to point it out.

Nuance quietly surfaced.

Clean!

This one observation changes everything.

And it has teeth.

You are right ...

Personally my least favorite is the overuse of "quietly" (e.g. "No tricks. No marketing gimmicks. Just one company quietly outperforming the others"), and the one that makes the least sense to me is "that's the wedge."

I'm curious how these become so ingrained. Then the uncomfortable part is humans start repeating it more (a colleague said "belt-and-suspenders" during brainstorming the other day).

I heard "belt and suspenders" at least 20 years ago (meaning multiple solutions to a problem with backup in case one fails), and maybe would be longer if I were older. You could blame Claude for overusing it or importing it to other cultures maybe, but it's not in the category of invented phrases or ones that only barely mean something in the specific context Claude used them.

That's an importance nuance and makes the previous statements even more clear. I have the full picture now.

What's the difference between the two usages?

Yes, this and "belt-and-suspenders" are the ones that I notice the most. I also have non-native English speaking coworkers who have started using these terms/phrases recently, which makes me think that they're outsourcing all their writing.

Claude is obsessed with making things land. More than once I've reminded it that it's not a pilot.

If anything it proves the opposite imo.

It’s a POSIX thing, and it has nothing to do with the file extension. The OP is right: file extensions are optional (and, as shown here, often actively misleading), but if they’re present they should match the actual file type. Which, in this case, is Python code , not a shell script.

I hope it's actually talking to itself at higher bandwidth, and hope this is because of training that succeeds better given quality inter-agent communication.

For those who care to read everything rather than walk away, Fable can be extraordinarily dense. I suspect they'll pull the promo before I learn to read it.

Still, I feel I must read rather than correct it, as results are that much better if I let it do this "with" itself: orchestrator to agents back to orchestrator.

Take it to sonnet 5 or gpt and ask it to explain this to a layman. If you still don’t get it ask it for the why it matters or the how it relates.

You can also ask fable/4.8 to do it but I find it helps to keep the working model surrounded by the complexity rather than drawing it out. Simplifying text is something that takes relatively low effort in comparison to technical tasks. Sometimes I use Gemini, deepseek, grok, and recently meta just to see if they have any added perspectives, sometimes they do. Meta is really good at turning a technical mess into a story that paints a picture in my head.

I might need to do a spike as this is a core part of the spine. I will verify it and let you know when it's landed.

I dunno. Claude recently burned a lot of tokens trying to test an expensive task for idempotency.

While the task I was working on should incidentally be idempotent, it wasn't that critical. I never asked, or even suggested, idempotency. Yet it insisted on testing it was.

I need to scrutinize the plans. Or just not use Claude and use pi instead.

Right, and I think I mean "whichever one the big companies are trying to sell us on." :)

Well, "load-bearing" is specifically an engineering term :D Actual engineering, not software "engineering".

All of those phrases I've heard actively used even a decade (or two) ago. (I actually had to read your comment twice because I thought you were saying always, not never!)

"Critical path" and "long pole in tent" didn't make it into the model training data, but those were certainly also in play incessantly.

But they're all reasonably useful descriptions for common things, so I'm not surprised.

My point is that you get used to it. I don't like if aesthetically, but I like that it has an aesthetic at all.

I have coworkers who overuse phrases, oftentimes incorrectly. It doesn't annoy me because I'm familiar with their writing I know what they actually mean.

I would add https://www.orwellfoundation.com/the-orwell-foundation/orwel...

("It consists in gumming together long strips of words which have already been set in order by someone else, and making the results presentable by sheer humbug" -- Orwell predicts the LLM)

and also https://www.jstor.org/stable/25515288 "The Myles na gCopaleen Catechism of Cliché" itself is rather hard to find online, but he's a very funny writer so it's worth the effort.

> Babel: https://en.wikipedia.org/wiki/Tower_of_Babel

I was hoping for a reference to the Babel Fish, whispering its translations in your ear.

It's not clear to me whether that tool exists or you hallucinated it into existence with this post

I'd love to see that tool.

You don't think me using "honest" there might have been a tiny bit of (on-topic, and therefore appropriate) trolling?

You don't think it's possible that an LLM's internal machinery could decide that an underused-by-humans word should be used more frequently in output than it sees in input because it maps cleanly onto a frequently needed semantic? I think that's possible

And like any good corporate buzzword, it’s merely a simulacrum of precise technical jargon. The way Claude uses it is clearly wildly polysemous if not outright ambiguous.

> but you don't see "load bearing" nearly as often in prose written by people

Unfortunately, we're starting to now.

Thanks to Claude.

What do you replace it with? "necessary dependency"?

> Exactly the same meaning and connotation.

No, it does not have the exact same meaning.

The first means that her optimism kept her in some functional state, without it, she would collapse.

The second means that her optimism continues over time, despite obstacles.

The first doesn't emphasise how longstanding her optimism is, the second does. The second doesn't emphasise how important her optimism is, the first does.

For me, "key", and "critical" merely say it's "important", but don't convey the sense that "out of the mess of connected concepts we're discussing, the one that is actually interacting with the thing we care about, or at least dominating the interactions with the thing we care about, is X".

"operative" is a bit better, but I think of it as referring to grammatical interactions, i.e. interactions at the level of language mechanics rather than semantics.

English is not my native language, but I consider myself fairly fluent. I've never heard the expression "belt-and-suspenders" before Claude.

Thank you for the correction!

The token saving is oversold, from what I can tell so far. These days output tokens are just the tip of the iceberg.

If anything the real value is it saves my brain from going into power saving mode by lunchtime because I haven’t spent the day reading pages of output when a sentence or two would do.

"Honest assessment: I was wrong to say I was being straight with you. You pointed out that a "smoking gun" is a sign of evidence, and I clearly didn't have any. This is not a bug but a gap that can be fixed like [this]. Give me the word and I'll wire it in."

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