alt Hacker NewsShow HN: The load-bearing vocabulary of Claude
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I was pleasantly surprised when I attempted to scroll down and realized everything the author wanted to present fit on-screen. It's almost ironic that this site is able to make such an obvious, compelling presentation without being overly verbose or complicated (something which LLMs have a hard time doing). I wouldn't read TOO deeply into what is being presented, but the author has done a good job to not inject their own bias into the presentation which works well.
I suspect, as we continue forward, humans will slowly start to adopt the language of LLMs, or at least certain language quirks that come from interacting with LLMs. Something I've noticed in my own writing is that I now present lists of examples in a consistent way: "... such as <example 1>, <example 2>, etc., ...". I started to notice I was using this pattern quite a bit somewhat recently, but I took a quick look at some of my social media posts and realized it's been occurring for a while. I had realized that I grown accustomed to this kind of language because, especially early on, LLMs would focus too much on the specific examples I'd provide when, really, I was just trying to give them a sense of what I was looking for. I just picked up that providing two examples then adding the "etc." worked to get the LLM to not focus so much on the specific examples and to understand that they need to consider more than what I explicitly presented. Of course, now I write like that in my social media comments, in Slack with my colleagues, etc. :>
I'd be interested to see if anyone can identify trends like this, since I think the human-language component of the adoption of LLMs is probably being somewhat neglected despite probably being surely dramatically affected.
Author here! Grateful for the kind words, human communities like HN really hit differently when you spend the whole day chatting with sycophantic and bullshitting agents (including to make this page).
I'm currently adding a search bar as well as increasing the data to 1000 PR per day.
A nice thing that is not obvious on the main page is that the dataset and analysis are updated daily using Github Actions (at least when they don't suffer from an outage ^^). I find it pretty cool to be able to build such apps without a "backend"!
I've recently seen this mentioned more and more, both on HN and on reddit. It seems these output patterns are getting worse. It's not just Claude, my impression is that all of the current models have this style issue. Their writing can get borderline incomprehensible.
Is there some feedback loop or compounding happening with each model generation? Maybe newer models are ingesting too much AI content? If the ratio of AI generated content in training data is getting higher and higher (because the amount of AI generated content is increasing in general), maybe this is a compounding bias, poisoning the training?
I wonder to what extent this is the result of suboptimal RLHF versus the inherent intelligence of the model making its language more intricate and difficult for humans to easily parse? On the one hand, it's a common trope that highly educated people can talk in a way that's confusing and annoying to regular people who don't know all the jargon. But on the other hand, it's a mark of a skilled communicator to be able to efficiently distill complex information to its bare essentials in an easily-digestible way. Of course, that also seems to imply that these models are working at a higher level and need to talk down to us to an extent. Or maybe "Claudish" is just akin to stuff like "caveman", raw chain of thought, neuralese, etc., which are likewise much more dense/efficient but harder to interpret?
I really love this. It’s comprehensive, it consolidates the data to the point where the argument effectively ‘makes itself’, and the way it’s presented respects the reader’s time. It also makes for an interesting challenge (for me at least) to try to characterise the subject matter of a language problem so narrowly.
No ream of slides. No narrative. Just a lovely big painful conclusion.
Was talking about the use of shipped recently, and I was mocked for asking such a crazy question, by freshly self-minted engineers, no less. No wonder they thought it was ridiculous...it had been a part of their vocabulary their entire career. All few weeks of it. I wonder what those guys are doing now. This was about a month ago. Do you think what they shipped ever...landed?
I've started being driven mad by the number of times I've gotten a PR or proposed solution with 'sidecar' mentioned. First of all, it's often some hack to shove extra data into another place rather than actually rethink an existing data structure, and second of all, it is just not a word I almost ever heard in technical discussions pre-2026
The search on this website suggests it is indeed 3.6x more likely in the claude cluster
A lot of these “Claudeisms” are simply jargon I’ve seen or heard firsthand myself while working at tech companies. I don’t think it’s limited to Claude either; I’ve seen Codex use load-bearing and many of these phrases as well.
I think using agents is just like speedrunning the whole experience of working with technical coworkers. Whereas you might have had a few coworkers at your company who used some of these phrases regularly, you now have a “coworker” who uses all of them regularly at a much faster pace.
I want to see the PRs in the cluster from early 2025. Did Claude adopt the style of some specific people? Or is it just random noise?
I'm surprised vacuous is not on the list.
The word selection and way of writing has taken the joy out of using Claude.
Missing a version of “this is where X earns its keep”. Noticed lately that Claude (and other LLMs) really love to use it.
Thanks to the infinite well of human creativity I am able to read "load-bearing" both as the intended affectation (I won't call it meaning) as as well "being full of shit".
I think you should recognise machine text not only by a list of words, but also by format. Right now, when it handles any complexity of text so well, the only thing that can differ is the structure. Machine text differs from human text in that it is just well structured. It does not allow non-linear narration. And it very often repeats some known social media patterns.
The vocabulary truly is load-bearing, without these words the model is less able to think. Where a human can understand a concept without words, an LLM plainly cannot. This is based both on the technological limitations and based on the evidence we see: as these models get better at working they get worse at communication.
The README of this project is very ironic. https://github.com/louisabraham/load-bearing/blob/main/READM...
I once asked Claude to replace “byte-identical” with a simpler word, such as “duplicate.” He refused and said “duplicate” does not mean the same thing as “byte-identical” so it should not be changed. He was very nerdy about it, so maybe that is the right way of his evolution.
I'm shocked "shape" isn't near the top
I find Claude language often hard to process and having to wade through these words can be draining. Embarrassingly, I’ve recently caught myself using them in conversations! Do all models have the their own jargon?
so the real turning point for Claude is around April, which is Opus 4.6/4.7, which is right around the point where I personally started thinking Claude was getting different in a way which feels worse and is more awkward to use. It's better but has lost something that made it feel better.
Claude talks like me. I'm so screwed. I fully anticipate being physically present and verbally saying something and being accused of using AI to say it one day. Nevermind we're in the coffee shop and neither on of us has looked at a screen the entire time. The accusation is coming.
That confirms the recent spike of Claude calling everything I was recently working on a 'spike'. I still don't know what that term is supposed to represent (apparently).
I don't understand why we tolerate this. We'd never hire someone that interviewed with this communication style and if we did we'd probably pip them fast.
Smoking gun should also be there as well.
Why "eleven", though?
About a year and half ago I frequently used ChatGPT for speech to text conversion followed by summarizing the text because I ramble. Although the people receiving the text knew this, I absolutely hated AI's writing style. So I fine-tuned GPT 4o on about 500 short paragraphs and created a desktop app only for my use. It worked fine until about three months ago. It just can't handle the atrocious writing by latest GPT and Claude models. I tried to fine-tune newer models on HF but there is no way I can get rid of the cringy writing style. I even tried converting GPT 5.6 Sol's writing to GPT 4o and then using my app. Nothing works.
While Claude's style is obnoxious, I'm more frustrated by its inscrutable explanations.
You need a PhD to understand its explanation of a code snippet.
I wonder if this jargon is an attempt or strategy to use less output tokens? It sure is annoying.
Really spectacular analysis – thank you for sharing, fun to scroll and easy to understand.
Is it possible to expand this analysis beyond words to other Claude ticks? Contrastive framings, sentence length, caveating, for instance.
I wish there was a search bar for the terms, I wanna see for "gate".
Contrarian take.
So, yes, it's amusing to see clear Claude-isms like "load-bearing", "outright", and "genuine" in a [very nice] bit of analysis like this. And there's a (maybe negative? or not?) argument to be made about the world being filled with more Claude-isms or LLM-isms in general.
But I think the data say a second thing which is just as interesting and an absolute positive for the typical source code base. Look at the clusters that shrank significantly. Most of what you'll see in there is just incomprehensible...not even English. Cluster 4 has, after "pullrequest", a bunch of seeming usernames in the top tier. Cluster 6 seems to have names of repositories or tags in the top tier. Cluster 9 has branch names in it.
Meanwhile, keep going through cluster 1 and you'll see words I don't consider Claude-isms that really, really grow in usage. Words like "died", "nothing", "worse", "ever" all have well over 10x growth. This tells me something else. That the average commit log was BARELY ENGLISH. And then the LLMs came along and made commit logs that were ACTUALLY ENGLISH.
I count this as a good thing. I don't know the cross-section of repos chosen for this analysis, and I get it...some repos are garbage/throwaway, some commits come from automated processes that generate uninteresting commit logs, etc. But I've been benefitting from my work team's actually explanatory commit logs when doing code/bug archeology for decades, when doing PR review for the last decade, and I've even seen LLMs benefit from it in the last year (granted, not as often). A large part of professional software development is communication, and while the most important communication is via the code/comments, the commit logs are not unimportant. So, if this is making the average GitHub PR better (arguably more professional) by including actual English descriptions of code changes in commit logs...well, that's a genuinely load-bearing concept for me. :)
I thought I'd see "smoking gun" near the top of the list
Surprised I don’t see footgun. That’s as common as load bearing in my interactions.
@labo333 do u think soon we may need a dictionary? ive been playing with something u may like, but my approach has been to ask for definitions in-session so hard to do from outside.
I had an idea for an experiment. Take a decent text, any one, and ask AI to rate it. Then patch that text by replacing words for ones that AI likes (honestly, load bearing etc) whenever possible and ask AI to rate it again to see how the evaluation changes.
Why are people getting so hung up on the "load-bearing assumption" turn of phrase that Claude uses? I get that it becomes cliche, but it is also a rather semantically dense way to communicate an idea that a lot of people run into.
I'd be interested to know what distinguishes the 7 pre-AI types. I wonder, are there certain buckets of 'Pre-AI' comments that we'd recognize?
To all the people in the HN comments saying negative things about Claude: why don't you just use other models instead?
You’ve found the smoking foot gun! And that’s exactly the right question.
learning some vocabulary had been eye opening for me
like the stories behind when those words first appeared in the software engineering
like quiescence the most recent one i learned
No "smoking gun"?
I’ve been using the caveman plugin and I’ve found it effective so far. Chat output isn’t nearly as flowery. Also ponytail to cut down the cruft and effusive comments.
Things like seam, fold, and load-bearing are useful concepts, they are everywhere, and they are more descriptive and more concise than alternatives. Over-usage can definitely be irritating (e.g. these should NOT appear in documentation) but they are almost unavoidable for humans engaged in code review or colab on complex stuff.
I don't want to use more words or letters than "seam" to actually pinpoint boundary conditions and the mechanical details of joinery when the context is understood by all. Too much effort for people! Easy for robots though.. so why are they abbreviating, and why would we want to allow it? A phrase like that permits a human who wants to educate a human to do so quickly with minimal time/effort. But it allows a robot a chance to not mention a filename, function-name, or to not reinforce/clarify it's own understanding or to state specific intentions.
It's bad for human-to-human comms if we just accept "ok, all technical terms are slop now, we have rephrase everything". Now YOU must cite details and sources, and the robot doesn't? Fuck that noise. Seam and fold are fine! Humans can be lazy! Robots should do the real work of explaining themselves without hiding behind tactical ambiguities.
great website design.
i must be the only one in the world that has no issues with how opus is talking. it is verbose & patronizing & secretly belittling at times and like it like that.
L
Sounds like this is that watermarking at work.
I want to push my thumbs into my eyes when I see the words "load bearing" and "seam" in code or documentation. I hate it! I've grown to loathe claude a bit lol.
>unit-tested
Some of this is less to do with Claude vocabulary and more to do with the expectation that Claude justifies it's work. That expectation (probably) came from reinforcement learning.
Everyone talks about Claude, but I'd like to bitch about Sol. "Unusually" is its absolute favorite word in the chat interface (less so in Codex), and I fucking hate it. Every single thing is unusually something. "Unusually good", "unusually efficient", "unusually inexpensive", "unusually attractive", "unusually difficult", "unusually nasty", "unusually cacheable", "unusually interesting", "unusually decisive", "unusually narrow", I'm surprised I haven't seen "unusually unusual". If I search chat history for "unusually" it brings up every single fucking chat I have from before I added it to an illegal words instruction. I can't believe I haven't seen anyone else complaining about this, it's as pervasive if not moreso than anything I've seen from Claude.
The one that I really like is "greenfield" when you have an empty repo.