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Posted by Labo333 22 hours ago

Show HN: The load-bearing vocabulary of Claude(louisabraham.github.io)
445 points | 213 commentspage 4
MaxwellM 15 hours ago|
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.

Labo333 15 hours ago|
Author here, thank you so much! I really tried to make it nice to use, beyond the (quite original) modelling.

A prototype I did tried to detect some grammatical constructions, eg "it's not ..., it's ...", but I am not sure how to systematize that.

Also just a disclaimer: I am NOT tracking Claude tics, I am merely finding that a particular cluster of vocabulary increases. Tracking Claude requires labelled data IMO. I tried using model release dates in a structural model to constraint the clusters but the result was not compelling, so I ended up simplifying the model a lot!

simlevesque 16 hours ago||
I wish there was a search bar for the terms, I wanna see for "gate".
Labo333 15 hours ago||
I thought about that, I might add it if I can find a nice design!
khatkhati 16 hours ago||
Chrome's `find` finds it for me ;)
Labo333 15 hours ago|||
I have been using it as well, but I think adding a search bar will heighten the experience. I'm trying out some designs right now :)
shrikant 15 hours ago|||
Yeah Ctrl/Cmd+F works just fine on Firefox as well.
swader999 6 hours ago||
I wonder if this jargon is an attempt or strategy to use less output tokens? It sure is annoying.
nelsonfigueroa 10 hours ago||
I thought I'd see "smoking gun" near the top of the list
dirck-norman 12 hours ago||
Surprised I don’t see footgun. That’s as common as load bearing in my interactions.
damontal 6 hours ago||
No “long pole” either.
dizhn 11 hours ago||
Probably because of the dataset. I don't see sorry or apologize either. They wouldn't be in code or commit messages.
United857 4 hours ago||
Smoking gun should also be there as well.
clbrmbr 15 hours ago||
@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.

https://www.themachinevernacular.net/

glimshe 15 hours ago||
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.
ricardobeat 15 hours ago|
Claude usually rates its own writing very highly, which is a problem when trying to make it write differently.
ziml77 13 hours ago|||
I've tried to push AI to get rid of the AI-isms. And, despite being able to produce a skill file which described all the strange ways that AI "talk", the AI failed to actually make the output sound less like AI. Tried this with ChatGPT and Claude with similar results for both.
smj-edison 14 hours ago|||
Yeah, I once asked it to review its own writing with a subagent with a pretty strict writing guide, and it didn't see anything wrong, lol.
jfultz 5 hours ago|
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. :)

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