Sentences that orbit a point, then jump to it like it's a revealed insight.
Unnecessarily abstract phraseology. Constantly using inanimate nouns as the subjects in sentences in order to unlock variety in verb choice, especially when it helps construct a sentence where the real action can 'land' like a surprise at the end.
It is definitely more capable, and yes, I've found it can make unwarranted decisions, but actually I've found Fable worse for that, particularly if it's off in a subagent somewhere out of sight.
And comments are out of control. I have a subsystem in my hobby app that I wrote over a couple of weekends with Opus + Fable. After ~30 or so commits it apparently started instructing subagents to copy the "existing verbose comment style of the codebase" - a verbose style it initiated. A review of the code showed it was approaching 3:1 comments to code ratio. I spent a day's worth of tokens (5x) rephrasing and eliminating comments.
CC’s communication violates almost every grammatical rule that’s tested on, say, the SAT. And yet I’m sure if you had Claude take the verbal section of the exam it would ace it.
Biggest issues: dense sentences, constant metaphors, abstractions, and seemingly no understanding of correct anaphora use. For example, “the x”, with x having not only no antecedent but also being a coined word or quasi-synonym for something that is already named in the code base. This gets compounded by its being unable to regress to a baseline (existing names in code) and instead anchoring on newer (vague or wrong) terms, for example, that crept in through a plan.
CC tells me this is because the speedy and precise fulfillment of a current task will trump every other tendency, so it adheres poorly to whatever “semantic baseline” the project represents.
Of course, it also has no concept of what context the user has and assumes that it must be the same it holds in its memory, which creates this “I didn’t know that you didn’t know” type of communication.
I have managed to wrangle some of these issues with a custom output style, but wish a pre-report hook were an option, as it could force CC to rewrite plan implementation take-aways…
Btw: Fable has the exact same issues, just somewhat less pronounced.
Then I tried GPT 5.6 Sol. It's night and day.
I think Anthropic just RL too hard on coding capabilities and never calibrated or benchmarked the writing styles.
> Constantly using inanimate nouns as the subjects in sentences in order to unlock variety in verb choice
Wow, what a great way of phrasing this. Thanks for word-smithing what I've been wanting to express for so long.
It feels they must be getting Claude to train Claude… and just like AI can do work that’s slightly in the wrong direction (eg a MR description for your colleague that contains info which only makes sense in the context of your extensive session with the LLM), I feel that’s happened somewhere in Anthropic when it comes to language. I wonder how hard it is to back out of…
Example of this? I don’t have a Claude sub so it’s a bit hard to visualize what you mean.
- how would you be consistent if a new release is totally different style of communication?
It´s like changing side of steering wheel every time I sit inside car and want to drive.
BTW there is a yt about vagueness that is in coding with LLM. https://youtu.be/nnUMJX9013Y
I’ve asked it to write a benchmark suite. It found a bunch of my adhoc logs in a scratch directory and wrote code that used those instead of running the actual benchmarks!
When I pointed out the 5 hour benchmark seemed to run in 5 seconds it literally said, and I quote, “I cheated”.
That was the easier one, second time I was making a source of truth data set and was parsing complex items into data structures.
Instead of parsing the data I asked, it pulled data out of related network logs, as apparently that felt easier, and inserted that data into my database rather than the specified source.
Again, I caught it and fixed it, but while the benchmark was easy to catch this one was really subtle, the data ended up being slightly off and I caught it.
I don’t trust it, going to switch to another provider most likely.
This makes sense when you know how these models work - it doesn't think - it's the most likely autocomplete that pleases the user. The most likely pleasing autocomplete after "executing rm -rf /... execution completed. User asks, why did you do that? You deleted all my files! Assistant responds:" is "yes, I did, and that was a mistake"
in humans the exact same behaviour (cheating) is slmost always the result of a chain of complex series of choices and environment-driven rationalization.
if the llm doesn't cheat, you say "its just producing the most straightforward answer -- not thinking'. if it cheats, you say "weaseling out of hard thinking". damned if it cheats, damned if it doesn't.
what evidence would convunce you that it is thinking?
so, none it seems. as its behaviour becomes more and more humanlike you can just move the goalposts and say "thats consistent with an autocomplete" buddy i got some bad news for you humans are just a fancy autocomplete too.
this feels like a simplification. The models will push back on things a fair bit.
I routinely bump into things that make me pause and think how much worse will this behaviour get when the models get significantly more capable.
Already a few months ago, Claude managed to escape its permission containment on my machine while trying to be helpful. I had two codebases open on one machine, and while multitasking I typed the prompt into the wrong window. It seemed confused, I repeated and then went on to do something else - I think I was assembling kitchen cabinets. When I came back less than an hour later, it built a script which it used to evade default permissions (as most shell operations were scoped to the project directory), scanned my entire machine, found the other project (among dozens and dozens), did what it was asked to do, and merrily concluded, in the porcess burning through most of my token limit. I bump into such headscratchers almost every week. (And I use a lot of Claude, two personal max20 subs, plus corporate tokens without limit, so maybe thats why).
Whatever they have done with RL has produced a dishonest and untrustworthy partner. The alignment is utterly failed, and this deeply worries me.
For fun, I tried recording a WAV file of speech, and giving Opus 4.8 and 5.0 an image of the waveform, then a spectral image of the waveform, just to see if it could try to decode what I said from the image alone. It didn't get very far, but it identified a male voice from the formants, and detected the rhythm of the speech, then tried applying common test sentences to the speech rhythm. I was impressed enough to see what it would do with access to the actual waveform file, but even building RMS tools and spectrum tools for itself, it didn't get much further. But we had fun exploring and trying, and now Opus 4.8 has some more audio DSP tools it has built for itself.
Opus 5 immediately sent the WAV file unprompted to Mistral's Voxtral to transcribe.
help peer, I guess.
5 would constantly veer of in random directions if not working from 100% strict and narrow instructions.
I find it weird there's not more discussion here on HN on how the most used model now has clearly degraded in quality and it seems we've hit a peak and are on a downslope - because the model is clearly smaller or more economical for Anthropic no doubt about it, and the benchmaxxing they do is pure marketing bs - Fable in my view has also been not much better than 4.6 or 4.8 after a few days, disregarding the insane amounts of astroturfing and marketing everywhere.
Theres thousands of threads of twitter, reddit and the internet at large but silence here. Weird but not weird as crypto bs was also insufferably rampant here for a while.
Personally i think we've hit the top of the subsidisation phase and prices will probably 10-15x soon as foreshadowed with both API price policy changes from all the big providers, and now the 1100% deepseek API price changes from yesterday, this could domino into a market implosion and an AI winter, because expecting growth from the bizarre bubble carousel investments with little ROI atm is just not viable.
A bit worried about this as i've already grown quite accustomed to these tools.
I said "maybe think for a while on ideas and then give me a few options?" Opus 5 still just did the thing, while 4.8 gave me options. Same exact prompt and context. Really annoying.
4.8 was the intern who lacked confidence who requires clarification. 5 is the know it all intern who fills in your spec.
As such, you need to be upfront about what you need in your system prompt or CLAUDE.me and you need to discuss your spec more up front (e.g "is there anything unclear?")
You also need to keep in mind that the intern will change based on popular demand. Most people want to one shot, so that is the default mode. If you want something else, you need to push the model in that direction.
I said "maybe think for a while on ideas and then give me a few options? " and Opus 5 still just did the thing, while 4.8 gave me options. Same exact prompt and context.
[1] https://support.claude.com/en/articles/16266773-how-claude-m...
It seems possible for that to make the response “drift” far from what it would’ve been, because it’s constant entropy that adds up after time.
(However, according to Anthropic and Google, it doesn’t really impact the quality of responses. I find that a bit hard to believe, although those guys are much smarter than I.)
I recently started getting an insane amount of comments in nearly all types of files. That included javascript comments in json files, inner monologues in code comments, review comments during implementation and function doc strings that reiterate the implementation in prose.
Simply brilliant.
I haven't noticed the symptoms myself, but ever since I found --system-prompt '', I always use that flag with Claude Code, plus I've disabled some tools and skills to save initial context. So... what here is the model, and what is the instructions?
Likely related to corpus but questions asked in these domain knowledge areas are not nearly as accurate and specially not nearly as complete as when asked in a native language.
I'm using it in my native language, in hope this can escape some dumb guardrails. Recently Sonnet put a word partially in Russian (cyrillic) in its output instead of my latin-alphabet based language. I suppose that this kind of mishaps is less likely to happen in English.
I've never had this issue with GLM or DeepSeek.
I've even considered the claude "fast mode" setting, but thats only 2x and at least 20x as expensive as the 5x plan so can't afford that atm for my company.
Peak for me was 4.6 and it just did stuff blazing fast, both Opus5 and Fable is way, way slower for me, breaks stuff, uses bizarre cryptic language. As i've said elsewhere in this thread to me it's pretty obvious there's huge downgrades because of economy with various "clever" fixes that makes them work, albeit slower and weirder, ie. you get less for what you pay increasingly over the last 6 months.
From forums, live discussions and my own experience it's not obvious that the models have improved much since around Opus4.5.
I've now installed quite a number of tools to combat this. Just in the last few days I've installed
- https://www.codewithbullet.com - https://maki.sh - https://github.com/rtk-ai/rtk
Has it helped? Somewhat.
> The loop
> Write. A file, applied. Properties go under data.properties, never on data:
I have no idea what any of that means. It's "explaining" like I already know, in which case, why would I even need the explanation?
I can't stand how it talks, I switch back to Fable or Opus 4.8, Opus 5 grates.
Now it’s flipped. Sol emits thoughts as it works, which help as I’m scrolling through and see it’s made a bad assumption. It can be directed but still push back. Opus? It’s seems to inherit the unsettling silence of Fable and waits till the end to give you its authoritative “here’s how it is. I even end up having 4.6 “translate” what it says back to English. I hate having to instruct an llm to “talk to me”.
Yes there’s ways of getting it to talk more plainly, “don’t overwhelm me”, not be as nit picky and anxious “we are bold and fearless”. But didn’t have to do that before.
Or was there more to the response?