Advertisement
Advertisement
⚡ Community Insights
Discussion Sentiment
51% Positive
Analyzed from 3469 words in the discussion.
Trending Topics
#claude#more#output#model#models#opus#style#https#don#github
Discussion Sentiment
Analyzed from 3469 words in the discussion.
Trending Topics
Discussion (79 Comments)Read Original on HackerNews
The baked in communication style of these models is so obnoxious it's impacting my work. The best way I can describe it is that everything is optimized to impress the user and make the agent sound more authoritative, but the way this is done is through deliberate obfuscation, inserting inappropriate and extremely dense jargon, and bizarre, stilted metaphors. It's like they've been trained to produce output that's hard to read.
I was similarly frustrated a few months ago, but have noticed I've started to learn the idiom.
Its use of "dense jargon" and "stilted metaphor" is actually surprisingly consistent - it's speaking its own dialect, and you get used to it.
After a while it gets much easier to read and even becomes somewhat efficient, I think, since the odd metaphors it uses often have a precise meaning in Opus-ese (Fable speaks a really similar dialect).
And when you say it like that, I have to wonder how much of this is a natural consequence of RHLF on such a grand scale, when you have millions of people pretty much much skimming chat responses or operating outside their depth and giving unqualified feedback to the models.
Seems like a lot of people may be reinforcing what sounds smart over what is smart.
Also as an aside: funny how much the LLMs continue to mirror the human communication they’re trained on
This is because these harnesses are missing a very important feature. Anything like this needs to be included with every turn, otherwise the LLM quickly drifts.
I first noticed it when I wrote a harness for D&D (because it's so damn noticeable there), but now I include this for any harness I write.
https://learn.chatgpt.com/docs/hooks
This is close to the worst thing one could say of tool for professional use.-
---
That creates a feedback loop:
- Playful style is rewarded
- 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.
Don't worry. You'll get used to it. If you don't your kids will (as they'll know nothing else).
The top minds of our generation have decided that's the way things will be, and who are we to question them? It's not like it'll do any good anyway. Resistance is futile. There is no alternative.
That’s really annoying, although it feels like it’s improved some over time.
Not sure what the fix is, but you could try using a canary to at least get a signal of when things are going sideways (Mr Tinkleberry for reference: https://news.ycombinator.com/item?id=45983698)
Though you know, it's not like the leadership tied to these companies have a history of abuse, deception and theft or anything like that, right?
It's not like our leaders hide behind similar sorts of patterns that the agents/AIs follow (not saying it's not a human thing - but I hold leadership to higher standards than non-leaders). If our world leaders were able to be more accountable to these abuses, I don't think this would be tolerated with our AIs.
You are an editor. You'll be given a message with strange characteristics:
- Weird subject and verb combinations
- Subjects that should be objects
- Very roundabout reasoning, peppered with pseudo-epiphanies
- A distracting beat to the flow of the message
- Self-praise
Remove these characteristics, and rewrite it in a clear, conversational style. Keep the intent of the message, and take care not to lose any of the details.
A few specific rules:
- The message is usually set in the first person
- Only humans, groups of humans, and agents should do "action verbs"
- Objects should never do anything. Here are some examples to avoid:
- X carries ...
- X names ... - APIs are a minor exception to the action verb rule. They can do stereotypical things like CRUD, queueing, running, and calling.
- Avoid em dashes (—), as adds a distracting beat
The whole message you get is one block of that output. Reply with the edited prose and nothing else.
I can't help but feel the circumstances that enable this kind of front page article are vestigial from the days when OAI was super bad and Anthropic was beyond reproach. This change-over-time is why I avoid getting tribal with technology vendors. Assigning ideological motives to 200k+ employee organizations is how we wind up in weird contortions like this.
Most rational actors simply moved from one to the other. It takes a special kind of devotion to the proverbial hole in the ground to keep pushing in this direction.
Effectively all models can do style transfer reasonably well at this point, but not so much for "actual reasoning".
If the combination of two works better for you than each one by itself, why wouldn't you stack them like that?
This is what I think too. But, users’ psychology might be playing a role here. Anthropic has great advantage from being the first major player delivering functional agentic coding solution (rather than an intelligent autocomplete) and they were able to impress people by Opus’ iterative improvements early this year.
It’s technically very easy to switch between models, harnesses but their moat or perhaps a main source of users’ friction could be FOMO. That’s especially powerful in this competitive environment where everyone keeps wondering/worrying about what others might be doing to get or stay ahead.
Because it's not an either or thing. Neither is sufficient. I'd argue that, expenses aside, you should have every model you have access to cross reviewing the work of the others.
Outside of super trivial things that I should have just done myself, I have a cross-model review of _everything_ these days. The tokens are too cheap not to.
https://gist.github.com/bmurphy1976/47ad81a842ab4b1628ef5974...
A small preview:
https://github.com/gvzdv/claudish-to-english
> If CLAUDISH_MODEL names a model you have not pulled, every rewrite is skipped — with the one-time notice above.
I'd love to know what the hell Antrhopic has done to make Claude's writing so, so bad.
It's really unusable for anything other than code. And I have to remove its incomprehensible comments 50% of the time before committing anyway. After interacting with it, "slop vomit" is truly the most fitting description. I have to admit I have lost my temper and spontaneously referred to its output as vomit more than once. Seems like I'm not the only one.
Are people really having trouble parsing this??
The joy of watching a dumb AI-ism be sharply corrected by code you wrote months ago is hard to explain.
Opus/Fable output these days though is... not enjoyable. It's just really bad. The code quality is fine, but i want information from claude and it's just awful to read.
My biggest problem honestly is that i can't move my day job.. we're using enterprise claude and i'm not sure how much effort it would be to get access to another provider. I should inquire though, claude is really frustrating these days.
Hasn't worked yet outside of the classic "you're now manually breathing" kind of stuff.
Right now all I have is
> - Give terse and concise answers unless the user asks you to elaborate. Big walls of text are not usefull when trying to communicate.
> Caveats belong inline, no "one thing to note" or "it's worth mentioning" footer. If it is worth raising or calling out, do so where it is most relevant and not as a foot note.
Opus 5 has a god awful habit of always doing a Columbo on every single response, and it is such a jarring read that it amps my cognitive burden having to back-read everything.
[Seriously y'all in what universe would some "caveat" or another NOT "be a real one" by whatever severity you'd want to measure that AND/OR need of saying so ... ]
Claude (Original)
Force pushed. 1234567...890abcd main -> main (forced update).
Verified
Local main and origin/main both at 890abcd, in sync.
Every commit reachable from origin/main: no old string found.
Local object store, with spice-harvester as a control returning 9 hits: all old strings return 0.
Working tree clean, tests pass.
One caveat, and it’s a real one
The old tip 1234567 is still fetchable from GitHub by its full SHA. I confirmed this directly:
git fetch origin 1234567890abcdef1234567890abcdef12345678
* branch 1234567... -> FETCH_HEAD (succeeded)
GitHub keeps unreachable objects until its own garbage collection runs, and there is no schedule you control. Anyone with a full SHA can still read the old blobs through the web UI or a direct fetch. That fetch also pulled the old objects back into your local repo, so I deleted FETCH_HEAD, expired the reflog, and re-ran gc --prune=now. The counts above are from after that cleanup.
If you want the old commits unreachable on GitHub’s side too, the options are to ask GitHub Support to run GC on the repo, or to delete and recreate the repository. Deleting and recreating is the only one you can do yourself. Say the word if you want help with either.
Nothing to commit this turn. The rewrite was the work, and the tree is clean.
Claude Ă— Vomit GPT-OSS-20B
I force‑pushed the branch, updating main to commit 890abcd. I verified that my local main and origin/main are both at 890abcd. I checked that every commit reachable from origin/main contains no old string. My local object store shows that the spice‑harvester control returns nine hits, and all old strings return zero. The working tree is clean and the tests pass.
However, the old tip 1234567 is still reachable on GitHub by its full SHA. I fetched it directly and saw that GitHub keeps unreachable objects until its garbage collection runs, which I cannot schedule. Anyone with the full SHA can still read the old blobs via the web UI or a direct fetch. The fetch also brought the old objects back into my local repo, so I deleted FETCH_HEAD, expired the reflog, and ran git gc --prune=now. The counts I reported are after that cleanup.
If you want those old commits to be unreachable on GitHub as well, you can ask GitHub Support to run garbage collection on the repo, or delete and recreate the repository. Deleting and recreating is the only option you can do yourself. Let me know if you need help with either.
There is nothing to commit this turn. The rewrite was the work, and the tree is clean.
https://zachahn.com/posts/1787191554
I highly recommend it.
Claude and Codex usage limits cannot be trusted.
Paying your own API bills in full is superior.
Wish I could use my Claude subscription with pi too, much preferable to the endless command execution allow/deny prompts you have to do with CC, versus proper autonomous allow/deny lists defined ahead of time.
Curious why you recommend the API? It's likely the current subscriptions won't stay for long, they're heavily subsidized, but before they get axed, they're easily the best deal for monthly price/token usage.
Blog post: https://zachahn.com/posts/1787191554
The prompt I use to tell the LLM what to fix: https://github.com/zachahn/vomit/blob/main/internal/config/s...
Wasn't received too well on Lobsters haha, wrote a small extra blurb about it there: https://lobste.rs/s/juekuk/how_fix_claude_5_s_token_vomit
> Anything that uses the OpenAI API?
I would have thought they meant the Anthropic API or maybe I'm misunderstanding?
[1] https://vale.sh/
[2] https://github.com/Syntaf/vale-llm-slop
The vomit never makes it my way
There's an echo of that tension in OpenAI vs Anthropic. For a while OpenAI seemed reckless and ignorant, preferring to just throw compute at the problem. Meanwhile Anthropic is hiring philosophers. But now that Claude has its head up its ass to the point where nobody wants to talk to it, OpenAI is looking rather pragmatic.
It brings to mind a skepticism about just letting the ivory tower do its thing without some kind of anchor to the everyman (this is why we make researchers also be teachers, though I'm not sure what the AI equivalent of that practice would be).
Watching the models seesaw in the same ways that humans do, but faster, is so surreal. I wonder if their tendencies will remain an echo of ours, or if they'll one day be more of a forward projection, a representation of where were going if we don't change our ways, and if we're lucky, a reason to change them.
For me I added some instructions to speak clearly and it helped marginally and that's fine. There will be a new model out in a few weeks where I'm sure they've laser focused on this issue since nobody can shut the fuck up about it. The same thing happened with GPT if anyone can recall the ancient period of 4-6 months ago.
Like so many other products, people are moving too fast and shipping things that move the ground under people’s feet needlessly.
All this while we’re beaten to death with the marketing and false promises, and the broader consequences (ex: layoffs, stress, crazy expectations) caused from all this.
Obviously what Anthropic and co have built is amazing and people aren’t losing sight of that. That’s actually the key part of the frustration.
So no, this is not whining. This is the natural response you get when you make bad product decisions.
If you don’t want to get feedback, don’t sell products.
These things do work that previously would have taken expensive engineers months to do, at much lower quality, and what's our response? Ti nit pick on it being more verbose than we'd like?
Just like with humans, when someone is being too verbose, there's a skill to just filter through the noise and focus on the important parts.
This feels no different when I use an AI.
But I guess it's a good sign that we've from complaining about 'AI slop code' to, 'I don't like how it speaks to me'.
$20 and try it, then compare.