FYI a quick fix for claudish is to ask for the response to be in ASD-STE100 (Simple Technical English). Then it is far more readable. But I would agree that this is an annoyance and shouldn't require user workaround to get something readable.
FYI a quick fix for claudish is to ask for the response to be in ASD-STE100 (Simple Technical English). Then it is far more readable. But I would agree that this is an annoyance and shouldn't require user workaround to get something readable.
I think this is more a meme than anything else, for a couple reasons:
First, after a while it's just as grating as Claudeish. Second, my hunch is that it constricts the actual thinking of the LLM, like the same way that Newspeak does in 1984. It shrinks the range of thought that can be expressed if used as an input.
I think the real way to do it is to have another Claude entirely deal with the user as a liaison, but to keep the thinking in whatever format it came in.
Latent space reasoning, if you think about it, is exactly this to a crazy degree: why even formulate a thought as words if you can just keep it as matmuls until the user needs it? And then, if the user needs it, have it always specifically formulated for the user by another LLM rather than constrict its range of thought? Anyway, that's my take.
The fact that it might affect quality is something that is on my mind. In fact, I have mainly been using Astra after being primarily on Claude for several years exactly because of this annoyance. Ultimately, the model (at least for coding purposes) should just... not have this writing style.
I do think an infrastructure where another Claude retranslates the output would be better. Oftentimes I forget to put it in the actual prompt and when I receive back 8 paragraphs of Claudeish I ask for it then.
I would have to disagree that it gets as grating as Claudeish though. Its just direct and professional instead of ring-around-the-rosy clickbait.
The Claudeish drove me back to OpenAI and Codex as well. I find the Claudeish can be improved but it’s impossible to fully mitigate. Opus is unusable for anything I’m going to read.
“I would have to disagree that it gets as grating as Claudeish though.”
It’s hard to imagine anything more grating than Claudeish. To quote Rainer Wolfcastle, "My eyes! The goggles do nothing!"
This is the same reason why I am a bit skeptical of LLM superintelligence. LLMs in the end have to operate in natural language concepts and the complexity of natural language is bounded by limits of human cognition. I'm sure super advanced AI could use concepts that humans not only have no words for, but might not be able to understand alltogether. As such if my thesis is correct, the only way forward for true superintelligence may be getting rid of natural language COTs.
> LLMs in the end have to operate in natural language concepts and the complexity of natural language is bounded by limits of human cognition.
I don't think this is true.
They have to express themselves as tokens. The meaning of those tokens doesn't have to be text. See any model that can handle images/video. Also, I don't think math, svg, etc, are "natural" language.
And, only the final expression is tokens. The intermediate layers, with the encoded concepts, aren't "natural language".
But, to address your concern (which nobody can disagree with, since even humans can't fully express through text/pictures), potentially: https://news.ycombinator.com/item?id=49758615
Yeah, as I understand it, natural language is tokenised and vectorised, and then maths takes ahold.
The model isn't limited to concepts that can be expressed in natural language.
It's only once the AI gets to the output layers that natural language comes back into play.
After all, they're all made out of weights[0].
0: https://maxleiter.com/blog/weights
Reality cannot be reduced to tokens
Can it be reduced to ion concentrations? Because that's how we perceive it. A useful perception is all that really matters.
Thoughts are a poor reflection of reality to begin with.
There are two separate questions, right?
1. Is natural language holding LLMs back by some %? 2. Is natural language serving as a hard gate that will prevent LLM intelligent progressing past some specific point?
The answer to 1 seems like an obvious yes to me.
Your thesis says the answer to 2 is "yes." That doesn't feel right to me. Think about all of the humans who have pushed various fields forward: Einstein, Newtown, Bach, whoever. If natural language doesn't prevent an entity from surpassing humans in one intellectual field, why would it prevent an entity from surpassing humans in all intellectual fields?
(To be clear, I'm not claiming superintelligence will or won't be achieved; I'm considering your specific thesis about whether or not natural language will be a hard gate)
Strong Sapir-Whorf making a comeback wasn't on my 2026 bingo card.
By the way, how good is Claude's Hopi?
Each letter has it's own token. LLMs can invent new words if they want to, just like humans do. All the fancy words we use today in science did not exist even 100 years ago. And that didn't stop us.
How would this word inventing thing work? And how useful would it be? Can we make a POC around this?
A few weeks ago two "Claude wrapper" projects showed up here within 24 hours of each other. Both seemed to just sand the details away--useful if Claude is too wordy, I suppose, but seemed to also lose real substance.
Ask for output to the user in "simple technical English", let it think how it wants. It is hard to believe all the flowery prose is actually helpful to the model.
Does not work for Claude, at least for me and I put it as the system prompt
For me it works at first but Claude models forgets it after some prompts, despite only using like 100k tokens.
Your best bet is to use hooks and inject it after every file edit / response by first running the content through haiku and asking if it is asd 100 ste.
It burns more tokens but is the only way to get tolerable text.
Doesn't it just get attenuated and start ignoring those commands?
The hook sends the text to another agent/context with a request to validate and return a good or bad + reason response. Every request is a fresh context.
https://code.claude.com/docs/en/hooks-guide#agent-based-hook...
Yes but Claude starts ignoring messages when it keeps getting told the same thing over and over.
I don’t think system prompts are particularly reliable way to do much at all. It’s better to put it as a hook after each response, or a skill at least so you can trigger it at will if you don’t want it everytime.
Do you think they're unreliable based on the position in the conversation or other factors?
Anthropic has probably RL’d the system prompt into nothing because of their fear of the user being able to control the model. If it listened to you about the slop language, it might listen to you if you asked it to help you with no-no tasks.
It does work, you however have to put it into every single prompt in which you didn't want a rubbish response
Literally every one, even 1-2 prompts later it starts to go back
I created a custom output style based on this (borrowing some from github.com/AminBlg/SimpleEnglish) and I've found it to be better than the default or concise output styles, but still not as good for me as current GPT or Gemini models when it comes to communicating.
I tell mine to address me as a tech priest of the adeptus mechanicus. Works great.
I'm wanted to try this exact thing! I'll have to try this now.
I tried this a while back and I felt like the result was the same weird shoehorning of ideas into language, just with a different vocabulary. I’d really like for it to work, though.
This fixed claude! Thanks!
I put this rule in my CLAUDE.md: "Always write a TLDR in layman terms", it seems to do the trick