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The single biggest annoyance with Opus 5 is that it writes too elliptically. Sentences that orbit a point, then jump to it like it's a revealed insight. Unnec

by barrkel 1mo ago

The single biggest annoyance with Opus 5 is that it writes too elliptically. 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.

speerer 1mo ago
Genuine question - are you copying the Claude phraseology for effect (in which case you captured it brilliantly), or is there a more mundane explanation?
- barrkel 1mo ago
  I naturally write half like Claude, but not the antithesis half - that's not me, that's Claude.
FailMore 1mo ago
Yes, it becomes exhausting to read/follow. 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…
demibabs 1mo ago
> 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. Example of this? I don’t have a Claude sub so it’s a bit hard to visualize what you mean.
- jstummbillig 1mo ago
  What they wrote is an example. Very meta.
- ahartmetz 1mo ago
  It feels like they have a bunch of people without good sense of writing style tune the writing style. That, or they cannot or refuse to (short term popularity metrics) predict how a tuning will turn out in the long run when people have plenty of opportunity to get tired of it.
- KptMarchewa 1mo ago
  [flagged]
- gwd 1mo ago
  Here's an actual output from Claude from a conversation about rewording a document to make it more readable: > Start with §1 (Overview) as the register-calibration piece. It's small, it's the section where the skimmability goal bites hardest, and your review of it teaches me the target voice cheaply before the bulk ports (the map and appendix B are the big volume). One review round on §1 is worth more than any amount of me guessing at register. Hard-to-read phraseology above: - "the register-calibration piece", rather than "a good example we can use to establish the writing style" - "skimmability" - "bites hardest" -- what does it mean for the goal to bite? - "bulk ports" -- using "porting software" here as an analogy for rewriting / reorganizing sections of the document - "the big volume" In normal English I'd write something like the following: "Start with rewriting §1 (Overview), and letting you review it to set the expected writing style. It's small, and it's a section where the ability to skim through it is most important. Reviewing it will teach me the target 'voice' cheaply, before we do the larger sections (like the map and appendix B). That's a lot more efficient than me trying to guess while rewriting the whole document."
karimf 1mo ago
This 100%. I was Anthropic-pilled. I had a $200/mo subscription and I only used Anthropic models. I was frustrated by the verbose output and the writing style. I tried ASD-STE-100, it helped a bit, but it's still too verbose for my taste. 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.
- Retr0id 1mo ago
  It's a surprising change from my perspective, because in the past it felt like they understood that Claude should be pleasant to interact with.
  - 8cvor6j844qw_d6 1mo ago
    It's bad enough that I've seen dedicated skills to do comment hygiene scrubbing and consolidation.
    - Retr0id 1mo ago
      I've tried telling it to "fix" comments with varying degrees of specificity and in my experience it just... fundamentally doesn't get it. Presumably using a different model for it would help. My theory is that Claude's learned approach to comments is to treat them as a sort of persistent in-band thinking trace, or a "memory" tied to an in-code location, which is a little at odds with the way humans use comments (human comments are intended to be read and understood by other humans, whereas Claude comments are their own dialect). I bet this is a result of iteratively training Claude on output from other successful Claude sessions. Presumably it's good for making benchmark scores go up.
      - tharkun__ 1mo ago
        I'm not sure why you all have issues with CC commenting too much. My rules in the CLAUDE.md specify that comments are evil, never comment unless there is an actual need to explain a WHY and since I do read what CC writes, if I spot it still adding such WHY comments and they make no sense, I'll have it adjust, in many cases by removing them. Given the code base has a minimal amount of such comments, it's also less likely to go "copy what the rest of the codebase does". Of course I've now jinxed it and some update will cause it to ignore the instructions coz I didn't write them in the new model's style or something.
deleted 1mo ago
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purplepatrick 1mo ago
Agreed. CC’s comms capabilities have decreased gradually since 4.6, and it’s a real challenge. I think the issue is that what works well for code (succinctness) doesn’t work well in prosaic English. 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.
- deleted 1mo ago
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- eterm 1mo ago
  I wonder if the odd phrasing is related to achieving the watermarking that was recently touted by Anthropic.
  - Mtinie 1mo ago
    Models before the announced date don’t have watermarking, so it’s unlikely. Now, if what you are interpreting is precursor work to develop the watermarking system, maybe? I suspect it less insidious: Claude has/had the public sentiment of being the “better writer” of the models. At some point that distinction would have been diluted as other labs’ offerings “caught up” stylistically, unless Anthropic continued to tune their output… I personally think they’ve pushed so far that they’ve overfit and lost the sweet spot they previously occupied.
causal 1mo ago
> writes too elliptically > 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.
- causal 1mo ago
  Follow up thought: I wonder if Claude is overtrained on academic papers, which often suffer the same kind of "prove how good I am at talking before getting to the point" prose.
  - TheOtherHobbes 1mo ago
    Maybe just Calvin and Hobbes. https://www.reddit.com/r/linguistics/comments/ky81y/verbing_weirds_language/ https://www.reddit.com/r/linguistics/comments/ky81y/verbing_...
    - alex_c 1mo ago
      This is hilarious - this week Claude’s writing was getting so bad I had this exact comic come to mind. Briefly considered adding “Verbing weirds the English language - stop it!!!” to its instructions.
    - dctoedt 1mo ago
      "Verbing": For some reason, to me the use of "impact" as a verb has always been fingernails on a chalkboard. But it's hard to see the distinction between that and using "access" as a verb (as in the linked C & H strip), which seems unremarkable.
  - bulder 1mo ago
    If it was overtrained on academic papers it'd reiterate the point multiple times for structure. Instead, it's burying the lede seemingly just to pad.
  - anon7000 1mo ago
    It’s way harder to read because most of Claude’s sentences are hardly communicating anything at all, or are just completely inscrutable. I feel like academic papers are just boring
deskamess 1mo ago
Its a little too much.... I have to ask it to explain some of the terms in the context they are used and I am getting tired of it. 'Seam', 'overload', 'spine'.... having to mentally 'reinterpret/flatten' the sentence is tedious. When asked to re-explain it starts with some half apology. Then, on the next query it does it all over again.
- deleted 1mo ago
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- sparkling 1mo ago
  I call it "jargon slop". Half of my follow-up prompts nowadays when working with Opus were "TLDR please". I switch to GPT 5.6 Sol please and its a much more pleasant pair programming like experience.
  - elwell 1mo ago
    I have a personal rule for Claude to always append a TL;DR: whenever the response is longer than two paragraphs.
- pennomi 1mo ago
  What’s killing me is that the vernacular is creeping into my coworkers’ speech patterns too.
  - renegade-otter 1mo ago
    "SAY LOAD-BEARING ONE MORE TIME!"
    - valleyer 1mo ago
      English, motherfucker. Does Claude speak it?
  - deleted 1mo ago
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jodacola 1mo ago
Yes. I’m not particularly dense but lately the walls of text I get back turn my brain in knots. When I start feeling my brain knot, I know I need to say something along the lines of “I need you to explain this very simply, with examples.” Only then can I parse the results without all the mental weightlifting. On more than one occasion my mind has wandered into “is this purposeful to get me to spend more tokens?” territory, but I’m trying to not get too tinfoil-hat-like.
- Jgrubb 1mo ago
  What's tin foil about that? It gets paid by the word and you get back walls of text.
  - jodacola 1mo ago
    Because it’s one thing to get me to spend more tokens because of how well a model functions, and another thing entirely to purposefully speak in unparseable prose that requires me to spend more tokens to understand what is going on. I’m fine with the former, while the latter is manipulative, and I rationalize to “surely that’s not actually happening.” Maybe I’m not giving my thoughts enough credit, though: maybe it’s not tin foil hat, and is real.
    - Jgrubb 1mo ago
      I think you're misunderstanding me. I'm saying "It gets paid by the word and you get back walls of text." - ie, what you don't want to think is happening is very obviously what is happening. It charges by the unit and it decides how many units it produces. It decides how much money it makes, therefore it decides "more".
      - jodacola 1mo ago
        I get you, and maybe we’re talking past each other. My point is that, while I understand it’s paid by the word, there are more words and less clarity than I previously experienced, leading me to believe it’s intentional to get an artificially inflated increase in engagement and, thus, spend. If it could be as direct as I previously experienced, I wouldn’t need to ask for another different explanation of the same thing and experience the commensurate spend.
unclebucknasty 1mo ago
I noticed a few releases ago a shift to a kind of conversational shorthand that seems to be intensifying—using phrases instead of complete sentences and its own style of jargon, wherein it introduces new terminology on the fly. This is especially common when it is trying to explain an issue, what it's done or what it's proposing to do. I think the idea was for it to be more concise, but it's actually still verbose, only not written in complete sentences. So, it frequently reads as cryptic and requires rereading to parse. The pattern is a wall of words, followed by an explanation that is harder to read and introduces new terms that reference something in that wall. The result is that—on first read—it can have a complete gibberish feel, and you have to really lock in and reread to make sense of it. At times, even that's not enough, and you must ask it to explain further.
lorisdev 1mo ago
The insane comments are why I wrote slopocop - they were driving me crazy! https://github.com/LBognanni/slopocop https://github.com/LBognanni/slopocop
raincole 1mo ago
> 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. Such a charming sentence. I kinda other if you feed Opus 5 its own output could it summarizes this shortcoming of itself?
unclebucknasty 1mo ago
The style... CC: "The problem is that I overreached..." [Wall of words here] "Two things: window surface is limited. Extract template. Buffer result and add to surface. Then, follow-up with new model..." Me: What do you mean by "window surface" and what result are you referencing? Also, why do we need a new model? CC: "Ah, you're correct to point out that no new model is needed. The problem is elsewhere and once we address that, the existing model should work fine. Now, as to your question about..." [Wall of words here]
blks 1mo ago
> I spent a day's worth of tokens (5x) rephrasing and eliminating comments. Surely it would be trivial to do it yourself, and it would have a side effect of making you more familiar with your project.
gundugi-man 1mo ago
> The single biggest annoyance with Opus 5 is that it writes too elliptically. This is even more painful for non-native English speakers like myself. I feel fairly comfortable reading academic papers or in general, communicating in professional context. But with Opus 5, it feels like reading a literature book: load-bearing, inert, wholesale, hunk, verbatim, and so on... I can figure out the meaning, but working with CC became unenjoyable.
- waldarbeiter 1mo ago
  Thank you, my dict.cc search history contains exactly some of these words. I felt like my english got much worse but when Claude kept talking about "hunk" over and over I felt like the problem is maybe not on my end.
  - VeninVidiaVicii 1mo ago
    This is the problem with commercial AI and the way our minds work; it writes garbage and we’re trained to think we’re stupid because we can’t understand it.
  - yorwba 1mo ago
    "hunk" is git terminology. When you use `git add --patch` (which you probably should, if you use `git add` at all) you get prompted "Stage this hunk [y,n,q,a,d,e,?]?" which is self-explanatory (?) and the hunk refers to whatever change git is highlighting at the moment.
    - tempest_ 1mo ago
      "seam" is apparently... according to Claude itself a term from 'Working Effectively with Legacy Code' by Michael Feathers which I have not read. All it took was for one sub agent to use this term and it stated using it everywhere all the time. I have not read the book and prefer other terminology but it only takes 1 sub-agent or 1 usage in the context before it poisons everything else.
      - 1mo ago
jasonlotito 1mo ago
Change the output in settings, or create your own. I know, it would be best if it was just worked like you wanted out of the box (not being sarcastic here) but that is an easy option you can use right now and it works.
madradavid 1mo ago
"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." This. Thank you for expressing this so eloquently. I've tried to put a finger on this and you've done that for me. I wonder what the solution could be , Ask Claude to "Dumb it down" , "Speak plain English" ? I have even thught of building some sort of "middleware" that fixes all this.
- gglitch 1mo ago
  I frequently tell Claude to use "simple, concrete language and uncomplicated syntax, and avoid project jargon, coinages, and abstractions as much as possible," to good effect.
- nmwp 1mo ago
  I’ve asked it to use plain English, avoid jargon, explain terms before introducing them. Its first response was to make memory, it forgot after 5 prompts, then it suggested claude.md. Looked good at the start of a session, forgot after 6 interactions. Then it continued suggesting other locations, sometimes correcting its own corrections. Same effect, so today I got annoyed again. And then it suggested a new thing: add a script in a Stop hook in settings.json. I added another one to the PreToolUse, hoping to prevent it from running all kinds of experiments I didn’t ask for or approve of. I still have to see where this ends up.. Maybe this can help you as well.
  - bcrosby95 1mo ago
    I wrote a harness for running tabletop RPGs. One of the key things to keep the LLM behaving correctly (such as not controlling the PCs) was being able to inject instructions with every new prompt, which I don't include in the history. It seems like all harnesses could benefit from something like this.
  - neilunlimitess 1mo ago
    [dead]
chuckadams 1mo ago
I find Deepseek's house style to be pretty refreshing. It has its own cliches (it does like talking about "seams") but I don't think I've ever caught it saying "load-bearing". I've even watched its thinking where after analyzing some awful legacy code, it started off with "Holy crap". And it certainly doesn't over-comment. I definitely can't one-shot a complex system with it like Fable can, but I prefer iterating over interactive brainstorming sessions anyway.
- basch 1mo ago
  Can any one run a check of the word masterclass against all the models when describing a clever idea?
- iamacyborg 1mo ago
  >it does like talking about "seams" Sounds like it was trained heavily on Opus 4.7.
  - chuckadams 1mo ago
    No doubt distilled, but I can't really condemn that practice, given how all models are trained in the first place.
VeejayRampay 1mo ago
the phraseology is unbearable, it speaks like some kind of pretentious dude from a software engineering discord or something, littered with lingo and catch phrases I try to push through but it's insufferable
- ryandrake 1mo ago
  It speaks like a Senior Staff Software Engineer who was somehow hired into that title with 6 months of work experience.
  - not_paid_by_yt 1mo ago
    I suppose it actually is exactly that, bar not being a human being that experiences anything
joegibbs 1mo ago
“The [thing that can’t remember] remembers” is a big one. Loves talking about memories and remembering.
Aurornis 1mo ago
> Sentences that orbit a point, then jump to it like it's a revealed insight. That’s accurate in my experience, except some times the point isn’t even revealed. I use LLMs for a lot of codebase exploration where I ask it to map out how something works. It will come back with a wall of text that says everything except the specific key things that I need to know. This leads to extra turns where I have to prompt it to finish the explanation and complete the thoughts. At first I thought I was doing too much skimming and missing the insights, but even after re-reading output it’s often just not there. It talks about the insight and things related to it, but it forgets to actually include it in the output until I specifically ask again.
double-u 1mo ago
Absolutely, the comments are killing readability. Next to /simplify I have to run a special comment cleanup pass and even that gets me halfway there. Striking to see then when letting Loki take a pass and it renders the entire comment block to a clean and neat one-liner.
andrewgleave 1mo ago
The glib epigrams and aphorisms it shoehorns in to all prose is by far the worst regression of any model I can recall in terms of simply generating simple, clear output. I cannot think of another model that's gotten worse at writing plainly while being explicitly instructed to do so. Infuriating. I've switched mostly to Sol and if I have to use Opus, the first task once the code is written is to ask Sol to strip and re-write (from the code as ref) all documentation Opus wrote.
rayiner 1mo ago
> 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. A lot of people write like that, lol. I call it the "theater" mode of writing--the plot twist comes at the end.
stingraycharles 1mo ago
> Sentences that orbit a point, then jump to it like it's a revealed insight. Is this inside the thinking tokens, or the output? As this type of stuff is expected for thinking, because of the whole CoT / “think step by step” works, as this is optimal for the way LLMs work with attention and next word prediction. So the fact that it first “orbits” a point only to get to the conclusion afterwards is the system working as designed. Eg “what is 3 * 3 + 5?” without CoT, it would just just answer “8” for example. with CoT, it would answer something like “<thinking>I need to think step by step. 3 * 3 + 5 can be rewritten as “(3 * 3) + 5”. I first need to calculate 3 * 3 = 9. Now I need to calculate 9 + 5 = 14. That was the last calculation. The final answer is 14. I now need to give the user the final answer. </thinking>. 14“ Etc.
- loopmonster 1mo ago
  It's the output.
  - stingraycharles 1mo ago
    And you enabled thinking?
    - loopmonster 1mo ago
      Why are you doubting me? Have you tried Opus 5 yourself?
- chuckadams 1mo ago
  You forgot about 1000 lines of "<thinking>Wait, but different idea here</thinking>" ;)
jonstewart 1mo ago
Pondering this one night last week, I realized that because LLMs can only reason with written language, what we might be seeing emerge with Opus’s load-bearing mumbo jumbo is its own creole for structural reasoning. Not only are our brains wide, our senses are, too. I slow down to a crawl when I have to read actual math in a CS paper, but show me diagrams and I can reason about whatever sort of data structure or algorithm, no problem. Opus by and large can’t and its adaptation has been to adopt metaphor for structural reasoning. So while it may be exceedingly annoying to chat with, I sort of wonder whether this metaphorical-reasoning behavior has been selected for precisely because it leads to better coding outcomes.
- globnomulous 1mo ago
  > because LLMs can only reason with written language Is that right? Think of code that draws a square, the representation of that code in storage, the movement of electrons, and the 'actual' square on the screen -- these are all to us transcriptions of same thing across different domains or media, and we can deterministically translate back and forth between them, but there's no real, actual, essential identity property. The code isn't the square. The electricity isn't the code. The storage isn't the electricity. I think of LLM reasoning and output similarly. The underlying graph of weights, matrices, and other data aren't knowledge, understanding, or language. 'Translating' the system's output to language is jusas valid and correct as translating it into some visual representation that would be incoherent to us, like a sequence of flashing lights or imperceptible noise patterns projected over an image of a dog. I guess this is all a very long winded way of restating Chinese-room problem: we feed the man in the room a message; he returns one that, for all the world, is indistinguishable from a "real" response that you and I might send, but, like you said, he has no access to sense data. He also has no access to the biology underlying real mental processes. He also doesn't have any personhood that we can discern. He has, rather, gradually developed through reinforcement the tendency to provide responses approximating all of all of that. I'm not sure the epistemological question "does he understand" (which is what the Chinese-room problem asks) has any meaningful answer. There's no mind, so there's no understanding. What there is, rather, is a system that generate patterns that we map to language and that our brains therefore map to communication, personhood, meaning, etc. It's the square I mentioned earlier. It's to us a convincing simulacrum, and it may be faithful enough to us to stand in those things, but that's not what it is. My sense is that LLMs are (a) the big-data Pyramids of Giza and (b) a consequence of hardware and software developing ways of generating abstractions that capture and generate more complex patterns than were previously possible to capture or generate in a manner comprehensible to humans. Everything humans do follows some kind of pattern. Language is the perfect way for a machine to capture that, because is simpler than the world itself and has clear rules and patterns, encoded in representations computers already have, that, modeled well enough, can generate output indistinguishable from the real thing -- what you or I might do with it. But the pattern matching that it does, and that we translate into language, is much more numerically rigorous and complex than anything you or I consciously do with words (hell, most people can't even figure out when to use "lie" vs "lay") and not doing what you or I do with it. It's not language. It's the square on the screen.
marginalia_nu 1mo ago
I wonder if this is related to their text watermarking. Given how well defined the terminology is in programming, imposing additional constraints (like SynthID) might be expected to give rise to these types of linguistic artifacts. The text needs to be long enough to watermark, and it needs (but fails) to find synonyms in a highly constrained class of words, so it resorts to inventing weird technical language that sounds like if you put buffy-speak through a thesaurus.
parkersweb 1mo ago
Oh yes - exactly this. The way it articulates re-factors in my current project has got so elliptical I've had to start asking it to translate into human speak - it's like it evolves it's own language to talk about the project. I've lost count of the number of times I've asked it to reenforce in memory not to use such verbose comments - and the number of times I ask it to re-look at an assumption it's made for it to return saying "investigation complete. And it's not what either of us was expecting"....
throwaway894345 1mo ago
It’s a strange feeling as a native English speaker to read the entire sentence and know every word, for the sentence to be entirely grammatically correct, and still have no idea what it’s trying to communicate. Another problem is that it will open up all sorts of tangents about nits that it encountered, but it will often not tell you that it’s a nit or give you adequate context to realize that this paragraph is exceedingly low value until you’ve spent a bunch of time and energy trying to make sense of it. I’m curious if anyone has any suggestions for prompting agents to improve their prose. I’ve had some okay results with “optimize for clarity, don’t dump every thought on me, treat my attention and focus as constrained resources, stay focused on the task at hand”.
- throwaway_7274 1mo ago
  I think it’s no longer speaking human language. It used to, when it was mostly or entirely trained with imitation learning of human-generated text. Now it’s increasingly trained with RLVR, and there’s far less optimization pressure on actually speaking English (or Punjabi or Mandarin). It still uses English words and syntax in its output, but the semantics are drifting more and more. It’s basically speaking in a code that superficially resembles English.
  - big_paps 1mo ago
    Thats scary
  - akomtu 1mo ago
    Alien Slop Intelligence
nater5000 1mo ago
The excessive commenting has definitely been noticeable and very annoying. I'm not against abundant comments as long as they're pointed and appropriate, but these models are literally just leaking their overly verbose output into the actual codebase.
hackitup7 1mo ago
Perfectly captures it. Opus writes like it's an insecure person trying to impress a first date. Big words and strange structural rhetorical flourishes for no purpose. Like dude I'm just trying to summarize a few emails and meeting notes, I'm not prepping for the vocab section of the GREs.
agentdrek 1mo ago
I wonder if I am not bothered by the useless verbosity of these things because I've been so immersed in business speak for so long. I am already tuned on quickly "finding the nugget" of useful info in blobs of what people send me. So it's mildly annoying but I can find the signal well enough without actually reading word by word.
artdigital 1mo ago
Do you have some examples of this? I can’t fully imagine how sentences like that actually look like (not native English here)
gwd 1mo ago
> 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. Yes, the "Y would make more sense, but the doc says do X..." YOU wrote the doc, if it doesn't make sense, change it! But of course, it can't tell who wrote the doc. I wonder whether its tendency to scribble status updates and todos and decisions all over whatever it's working on is a side effect of its amnesia -- it can't follow the side-quests and knows it won't remember to do them if they're not written down somewhere. FWIW I haven't had the problem either of Claude lying to me, or of going off and doing its own thing; if anything I've been somewhat frustrated when I ask it to start something, go AFK, and come back to find it stopped a short way in to ask my opinion on something trivial. I generally have to explicitly say, "I'm going AFK for a chunk of time. My goal is for you make as much progress as possible before I come back; try to make reasonable judgements and only stop if there's something where you're really stuck. We can always change it later."
bayganyo 1mo ago
I’ve found its response verbosity to be mentally draining. It disregards claude.md instructions to keep responses short. Eventually, I added a stop hook that blocks it if it exceeds 150 words. It’s then forced to redo its output to comply, and it’s like night and day. I’ve also added stop hooks for words in its output that frustrate me, like “honest” or “honestly”. The excessive comments in the code it writes are absurd. Completely ignores instructions not to write comments, even after pointing them out repeatedly in a session. I need to figure out how to add a stop hook for that too.
eternaldao 1mo ago
Claude offers money credits and double usages but take them out and Claude becomes almost unusable where it would take opus about two - three high effort conversations to exhaust my session quota in Pro. I once extended my claude code session beyond the session limit, and thought they are too generous in offering 100 dollars worth of usage. It was sonnet, for a somewhat mechanical task - and it spent 13 dollars worth of usage after exhausting my quota mid task. Only a few months back, I was awestruck by the quality of Opus 4.6 and jumped ship from chatgpt to claude. Even in technical tasks, Opus has to be told to limit token spend, it treats it as infinite budget - it will spawn a subagent to read every file just to get one line summary when I ask it to sort a messy folder of past ai chats. Thank heavens I was not doing it off machine, it would burned off my monthly usage and credits.
jakevoytko 1mo ago
It's clear that we're not the audience; it writes to be read by its training evaluator, not a professional software engineer. Professional software engineers can't read this word soup and are desperately trying to find ways to fix it. It feels like it found a register that games the evaluator, where it can ramble forever and rarely be marked wrong while slowly racking up points as it talks more.
renegade-otter 1mo ago
"writes too elliptically" Was this written by Opus 5?
insane_dreamer 1mo ago
100% agree. “Just make your point in plain English!!” Very frustrating and takes me a lot longer to understand what it says. Also presents too many points as once instead of being able to review and decide on each one in sequence. Re comments: same experience, and I had to show it my edits of its comments to add to its memory as examples to follow. It adds explanations of “how we got here” that should go in the ticket or maybe the commit message but not in the code. It also tends to over complicate things. I’m no longer worried much about accuracy but I find my main job is to challenge it and suggest simpler alternatives.
mlsu 1mo ago
Everything that claude writes fits into the same aesthetic structure. The aesthetic is that of an expert slowly revealing an insight to the user. The actual content doesn't matter. - "Introduction that rephrases your prompt." - "3 paragraphs, with one section of bullet points" - "The Twist" - "The Bottom Line" It's really obvious once you see it. Every single prompt, from a quantum physics question to a mundane observation about California burritos, is phrased in exactly the same way. This is obviously an artifact of post-training but it's also kind of how you can tell that this thing is a lot closer to a blindsight scrambler than real intelligence.
- zucked 1mo ago
  The second bullet point, down to the comma in the middle of the sentence, is what has been driving me absolutely batty of late. It's a surefire tell that I cannot seem to beat out of my outputs. It CONSTANTLY does it, even when you say not to. Between that and the insistence on "this, not that" structure makes me want to install the caveman skill and use it even for non-code workflows.
  - craigmcnamara 1mo ago
    This load bearing concern belt and braces.
    - EdwardDiego 1mo ago
      My personal bugbear is its usage of "grain" where normally you'd use "granularity", if at all.
      - ltrg 1mo ago
        Yes! Also everything's a "gate" that needs to be "wired up".
        paradox460 1mo ago
        Let me get my fence pliers
vorticalbox 1mo ago
I’ve always disliked the opus models whenever I use them after they have done the task they rattle out massive reports about what has changed or worse actually save that to disk even after being asked not to do it.
wouldbecouldbe 1mo ago
The single biggest annoyance, same as with fable, is that it overrules your prompt and does what it thinks is better. Even small things, sometimes it goes of a rant of 20 min doing random shit. And they are so condescending while doing it, it's unbearable. I'm honestly starting the believe the scifi fantasy of AI locking us up, or killing us, for our own good. I've had Fable & Opus 5, they are the same class of annoyance, write entire test suites when I just asked a simple verifications question, write to production database, deploy without permission, even after deploying and breaking my production API claiming it was not down. Then having to argue & plead with it to listen that they were wrong. They are without a doubt the most powerful models, but also the most smug ones.
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jaggederest 1mo ago
I have been doing a thing that I think is helpful - basically a notes folder, each doc has a title, the comments in code are only allowed to give a few words and reference notes via those tags, and I've built tooling around the notes and review them regularly. So it deduplicates and centralizes the slop, at least. Lint is the LLM's best friend and it works on doc too. My lint rules ban long comments.
UltraSane 1mo ago
Opus 5 sounds a bit like the dialog in Children of Dune where they talk like they are constantly trying to prove how smart they are and not actually communicate.
SubiculumCode 1mo ago
On the other hand, Opus 4.8 had an annoying habit of declaring a huge mistake was found, then two sentences later abruptly change its mind and say that it was in fact all okay. That's fine for chain of thought, but in the verbose output, it can lead to wrong impressions by the user.
quaverquaver 1mo ago
I have codex rewrite all Opus' comments with great results.
quaverquaver 1mo ago
maybe the comment length is a ruse to increase token consumption
wiremine 1mo ago
This is the most succinct summary of my interactions with Claude: thank you! I feel like they need high school English teachers in the loop on the next ground of training to whip the language in shape.
fastball 1mo ago
In my experience your criticism of the writing is valid in all Claude 5 models, so I wonder if it is somehow related to the new tokenizer introduced in gen 5.
arkmm 1mo ago
Since reasoning tokens are just text, I think the models have learned to squeeze in some computation in their output writing as well. So they're incentivized to be correct but long-winded, as it gives them more time to think. It's kind of the equivalent of filler words for humans, except LLMs can actually word-vomit something intelligible.
- galaxyLogic 1mo ago
  Right, but could that also be because ... the more long-winded they are, the more you pay for their output.
preg_match 1mo ago
Comments are the biggest problem. During code review I ask it to compact comments and its idea of compact is like… removing one sentence in a 5 sentence comment. Comments are a huge maintenance burden. They can, and will lie and need constant updating. They mislead the own model later on.
colordrops 1mo ago
There really needs to be a "terse mode" for Claude. It's WAY too loquacious. I'm hoping they aren't doing it on purpose to burn tokens.
avereveard 1mo ago
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rsalus 1mo ago
Yeah, +1 on the comment verbosity. Left alone it's actually insane. I've had to setup enforcement + templates (use ASD-STE100) to keep the cruft down. I'm worried this may impact the quality of outputs though - haven't measured it.
- aetherspawn 1mo ago
  I also use the ASD-STE100 trick and it works pretty great, but the places that it decides to put huge comments are really weird and a lot of the time I just ask OpenAI sol “rewrite the comments in this file without slop” and it does a much better job for comments.
ls-a 1mo ago
This is what news headlines did for decades to bait you into reading the details. I wouldn't be surprised if AI companies do that intentionally to consume more tokens trying to understand what had just happened
hi_hi 1mo ago
My biggest pet pieve isn’t the LLM-isms themselves, but people who aren’t aware of them releasing documentation that’s clearly AI generated and being indignant when I ask “is this AI generated”
Jagerbizzle 1mo ago
Replying here without having read any of the sub-replies so I apologize if this is a repeated theme. I have explicit markdown about telling the model to not write comments. "Every time you consider writing a comment, instead consider re-writing the code that questioned you to write said comment to begin with. Write comments only when logic is complicated or unclear, otherwise 'comment' via naming." The results thus far have been much better. I'm seeing code reviews at my work where indeed, we have 10 line comment blocks for a line of code and now I just straight up don't read comments. Sad state of affairs -- (emdash deliberately used here) but I guess the sooner the human gets out of the loop the better in this new world.
indrex 1mo ago
I had to setup hooks just to catch the and ban them in the CLIs. Most of what Claude writes is simply un-readable.
cromka 1mo ago
One thing I noticed working with Sol and Fable is that I can speed read, literally glimpse over Sol output and understand what it's saying. With Fable/Opus it's the exact opposite: I have to read every god damn sentence, sometimes twice, and often already losing the bigger picture in the process.
kaizenb 1mo ago
"Save in memory to always use ASD-STE100 Simplified Technical English when you talk to me" Use this to reduce the text output.
ako 1mo ago
Why are you so distracted by style? I see it too, it could be improved, it might be improved, but I don’t care as long as it get shit done. And it does, tons of shit gets done. And the communication is usually more informative than how coworkers document their work. Can it be improved? Yes. Does that mean I can’t use it? No.

by barrkel 1mo ago

speerer 1mo ago

Genuine question - are you copying the Claude phraseology for effect (in which case you captured it brilliantly), or is there a more mundane explanation?

barrkel 1mo ago
I naturally write half like Claude, but not the antithesis half - that's not me, that's Claude.

FailMore 1mo ago

Yes, it becomes exhausting to read/follow. 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…

demibabs 1mo ago

> 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. Example of this? I don’t have a Claude sub so it’s a bit hard to visualize what you mean.

jstummbillig 1mo ago
What they wrote is an example. Very meta.
ahartmetz 1mo ago
It feels like they have a bunch of people without good sense of writing style tune the writing style. That, or they cannot or refuse to (short term popularity metrics) predict how a tuning will turn out in the long run when people have plenty of opportunity to get tired of it.
KptMarchewa 1mo ago
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gwd 1mo ago
Here's an actual output from Claude from a conversation about rewording a document to make it more readable: > Start with §1 (Overview) as the register-calibration piece. It's small, it's the section where the skimmability goal bites hardest, and your review of it teaches me the target voice cheaply before the bulk ports (the map and appendix B are the big volume). One review round on §1 is worth more than any amount of me guessing at register. Hard-to-read phraseology above: - "the register-calibration piece", rather than "a good example we can use to establish the writing style" - "skimmability" - "bites hardest" -- what does it mean for the goal to bite? - "bulk ports" -- using "porting software" here as an analogy for rewriting / reorganizing sections of the document - "the big volume" In normal English I'd write something like the following: "Start with rewriting §1 (Overview), and letting you review it to set the expected writing style. It's small, and it's a section where the ability to skim through it is most important. Reviewing it will teach me the target 'voice' cheaply, before we do the larger sections (like the map and appendix B). That's a lot more efficient than me trying to guess while rewriting the whole document."

karimf 1mo ago

This 100%. I was Anthropic-pilled. I had a $200/mo subscription and I only used Anthropic models. I was frustrated by the verbose output and the writing style. I tried ASD-STE-100, it helped a bit, but it's still too verbose for my taste. 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.

Retr0id 1mo ago
It's a surprising change from my perspective, because in the past it felt like they understood that Claude should be pleasant to interact with.
- 8cvor6j844qw_d6 1mo ago
  It's bad enough that I've seen dedicated skills to do comment hygiene scrubbing and consolidation.
  - Retr0id 1mo ago
    I've tried telling it to "fix" comments with varying degrees of specificity and in my experience it just... fundamentally doesn't get it. Presumably using a different model for it would help. My theory is that Claude's learned approach to comments is to treat them as a sort of persistent in-band thinking trace, or a "memory" tied to an in-code location, which is a little at odds with the way humans use comments (human comments are intended to be read and understood by other humans, whereas Claude comments are their own dialect). I bet this is a result of iteratively training Claude on output from other successful Claude sessions. Presumably it's good for making benchmark scores go up.
    - tharkun__ 1mo ago
      I'm not sure why you all have issues with CC commenting too much. My rules in the CLAUDE.md specify that comments are evil, never comment unless there is an actual need to explain a WHY and since I do read what CC writes, if I spot it still adding such WHY comments and they make no sense, I'll have it adjust, in many cases by removing them. Given the code base has a minimal amount of such comments, it's also less likely to go "copy what the rest of the codebase does". Of course I've now jinxed it and some update will cause it to ignore the instructions coz I didn't write them in the new model's style or something.

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purplepatrick 1mo ago

Agreed. CC’s comms capabilities have decreased gradually since 4.6, and it’s a real challenge. I think the issue is that what works well for code (succinctness) doesn’t work well in prosaic English. 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.

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eterm 1mo ago
I wonder if the odd phrasing is related to achieving the watermarking that was recently touted by Anthropic.
- Mtinie 1mo ago
  Models before the announced date don’t have watermarking, so it’s unlikely. Now, if what you are interpreting is precursor work to develop the watermarking system, maybe? I suspect it less insidious: Claude has/had the public sentiment of being the “better writer” of the models. At some point that distinction would have been diluted as other labs’ offerings “caught up” stylistically, unless Anthropic continued to tune their output… I personally think they’ve pushed so far that they’ve overfit and lost the sweet spot they previously occupied.

causal 1mo ago

> writes too elliptically > 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.

causal 1mo ago
Follow up thought: I wonder if Claude is overtrained on academic papers, which often suffer the same kind of "prove how good I am at talking before getting to the point" prose.
- TheOtherHobbes 1mo ago
  Maybe just Calvin and Hobbes. https://www.reddit.com/r/linguistics/comments/ky81y/verbing_weirds_language/ https://www.reddit.com/r/linguistics/comments/ky81y/verbing_...
  - alex_c 1mo ago
    This is hilarious - this week Claude’s writing was getting so bad I had this exact comic come to mind. Briefly considered adding “Verbing weirds the English language - stop it!!!” to its instructions.
  - dctoedt 1mo ago
    "Verbing": For some reason, to me the use of "impact" as a verb has always been fingernails on a chalkboard. But it's hard to see the distinction between that and using "access" as a verb (as in the linked C & H strip), which seems unremarkable.
- bulder 1mo ago
  If it was overtrained on academic papers it'd reiterate the point multiple times for structure. Instead, it's burying the lede seemingly just to pad.
- anon7000 1mo ago
  It’s way harder to read because most of Claude’s sentences are hardly communicating anything at all, or are just completely inscrutable. I feel like academic papers are just boring

deskamess 1mo ago

Its a little too much.... I have to ask it to explain some of the terms in the context they are used and I am getting tired of it. 'Seam', 'overload', 'spine'.... having to mentally 'reinterpret/flatten' the sentence is tedious. When asked to re-explain it starts with some half apology. Then, on the next query it does it all over again.

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sparkling 1mo ago
I call it "jargon slop". Half of my follow-up prompts nowadays when working with Opus were "TLDR please". I switch to GPT 5.6 Sol please and its a much more pleasant pair programming like experience.
- elwell 1mo ago
  I have a personal rule for Claude to always append a TL;DR: whenever the response is longer than two paragraphs.
pennomi 1mo ago
What’s killing me is that the vernacular is creeping into my coworkers’ speech patterns too.
- renegade-otter 1mo ago
  "SAY LOAD-BEARING ONE MORE TIME!"
  - valleyer 1mo ago
    English, motherfucker. Does Claude speak it?
- deleted 1mo ago
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jodacola 1mo ago

Yes. I’m not particularly dense but lately the walls of text I get back turn my brain in knots. When I start feeling my brain knot, I know I need to say something along the lines of “I need you to explain this very simply, with examples.” Only then can I parse the results without all the mental weightlifting. On more than one occasion my mind has wandered into “is this purposeful to get me to spend more tokens?” territory, but I’m trying to not get too tinfoil-hat-like.

Jgrubb 1mo ago
What's tin foil about that? It gets paid by the word and you get back walls of text.
- jodacola 1mo ago
  Because it’s one thing to get me to spend more tokens because of how well a model functions, and another thing entirely to purposefully speak in unparseable prose that requires me to spend more tokens to understand what is going on. I’m fine with the former, while the latter is manipulative, and I rationalize to “surely that’s not actually happening.” Maybe I’m not giving my thoughts enough credit, though: maybe it’s not tin foil hat, and is real.
  - Jgrubb 1mo ago
    I think you're misunderstanding me. I'm saying "It gets paid by the word and you get back walls of text." - ie, what you don't want to think is happening is very obviously what is happening. It charges by the unit and it decides how many units it produces. It decides how much money it makes, therefore it decides "more".
    - jodacola 1mo ago
      I get you, and maybe we’re talking past each other. My point is that, while I understand it’s paid by the word, there are more words and less clarity than I previously experienced, leading me to believe it’s intentional to get an artificially inflated increase in engagement and, thus, spend. If it could be as direct as I previously experienced, I wouldn’t need to ask for another different explanation of the same thing and experience the commensurate spend.

unclebucknasty 1mo ago

I noticed a few releases ago a shift to a kind of conversational shorthand that seems to be intensifying—using phrases instead of complete sentences and its own style of jargon, wherein it introduces new terminology on the fly. This is especially common when it is trying to explain an issue, what it's done or what it's proposing to do. I think the idea was for it to be more concise, but it's actually still verbose, only not written in complete sentences. So, it frequently reads as cryptic and requires rereading to parse. The pattern is a wall of words, followed by an explanation that is harder to read and introduces new terms that reference something in that wall. The result is that—on first read—it can have a complete gibberish feel, and you have to really lock in and reread to make sense of it. At times, even that's not enough, and you must ask it to explain further.

lorisdev 1mo ago

The insane comments are why I wrote slopocop - they were driving me crazy! https://github.com/LBognanni/slopocop https://github.com/LBognanni/slopocop

raincole 1mo ago

> 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. Such a charming sentence. I kinda other if you feed Opus 5 its own output could it summarizes this shortcoming of itself?

unclebucknasty 1mo ago

The style... CC: "The problem is that I overreached..." [Wall of words here] "Two things: window surface is limited. Extract template. Buffer result and add to surface. Then, follow-up with new model..." Me: What do you mean by "window surface" and what result are you referencing? Also, why do we need a new model? CC: "Ah, you're correct to point out that no new model is needed. The problem is elsewhere and once we address that, the existing model should work fine. Now, as to your question about..." [Wall of words here]

blks 1mo ago

> I spent a day's worth of tokens (5x) rephrasing and eliminating comments. Surely it would be trivial to do it yourself, and it would have a side effect of making you more familiar with your project.

gundugi-man 1mo ago

> The single biggest annoyance with Opus 5 is that it writes too elliptically. This is even more painful for non-native English speakers like myself. I feel fairly comfortable reading academic papers or in general, communicating in professional context. But with Opus 5, it feels like reading a literature book: load-bearing, inert, wholesale, hunk, verbatim, and so on... I can figure out the meaning, but working with CC became unenjoyable.

waldarbeiter 1mo ago
Thank you, my dict.cc search history contains exactly some of these words. I felt like my english got much worse but when Claude kept talking about "hunk" over and over I felt like the problem is maybe not on my end.
- VeninVidiaVicii 1mo ago
  This is the problem with commercial AI and the way our minds work; it writes garbage and we’re trained to think we’re stupid because we can’t understand it.
- yorwba 1mo ago
  "hunk" is git terminology. When you use `git add --patch` (which you probably should, if you use `git add` at all) you get prompted "Stage this hunk [y,n,q,a,d,e,?]?" which is self-explanatory (?) and the hunk refers to whatever change git is highlighting at the moment.
  - tempest_ 1mo ago
    "seam" is apparently... according to Claude itself a term from 'Working Effectively with Legacy Code' by Michael Feathers which I have not read. All it took was for one sub agent to use this term and it stated using it everywhere all the time. I have not read the book and prefer other terminology but it only takes 1 sub-agent or 1 usage in the context before it poisons everything else.
    - 1mo ago

jasonlotito 1mo ago

Change the output in settings, or create your own. I know, it would be best if it was just worked like you wanted out of the box (not being sarcastic here) but that is an easy option you can use right now and it works.

madradavid 1mo ago

"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." This. Thank you for expressing this so eloquently. I've tried to put a finger on this and you've done that for me. I wonder what the solution could be , Ask Claude to "Dumb it down" , "Speak plain English" ? I have even thught of building some sort of "middleware" that fixes all this.

gglitch 1mo ago
I frequently tell Claude to use "simple, concrete language and uncomplicated syntax, and avoid project jargon, coinages, and abstractions as much as possible," to good effect.
nmwp 1mo ago
I’ve asked it to use plain English, avoid jargon, explain terms before introducing them. Its first response was to make memory, it forgot after 5 prompts, then it suggested claude.md. Looked good at the start of a session, forgot after 6 interactions. Then it continued suggesting other locations, sometimes correcting its own corrections. Same effect, so today I got annoyed again. And then it suggested a new thing: add a script in a Stop hook in settings.json. I added another one to the PreToolUse, hoping to prevent it from running all kinds of experiments I didn’t ask for or approve of. I still have to see where this ends up.. Maybe this can help you as well.
- bcrosby95 1mo ago
  I wrote a harness for running tabletop RPGs. One of the key things to keep the LLM behaving correctly (such as not controlling the PCs) was being able to inject instructions with every new prompt, which I don't include in the history. It seems like all harnesses could benefit from something like this.
- neilunlimitess 1mo ago
  [dead]

chuckadams 1mo ago

I find Deepseek's house style to be pretty refreshing. It has its own cliches (it does like talking about "seams") but I don't think I've ever caught it saying "load-bearing". I've even watched its thinking where after analyzing some awful legacy code, it started off with "Holy crap". And it certainly doesn't over-comment. I definitely can't one-shot a complex system with it like Fable can, but I prefer iterating over interactive brainstorming sessions anyway.

basch 1mo ago
Can any one run a check of the word masterclass against all the models when describing a clever idea?
iamacyborg 1mo ago
>it does like talking about "seams" Sounds like it was trained heavily on Opus 4.7.
- chuckadams 1mo ago
  No doubt distilled, but I can't really condemn that practice, given how all models are trained in the first place.

VeejayRampay 1mo ago

the phraseology is unbearable, it speaks like some kind of pretentious dude from a software engineering discord or something, littered with lingo and catch phrases I try to push through but it's insufferable

ryandrake 1mo ago
It speaks like a Senior Staff Software Engineer who was somehow hired into that title with 6 months of work experience.
- not_paid_by_yt 1mo ago
  I suppose it actually is exactly that, bar not being a human being that experiences anything

joegibbs 1mo ago

“The [thing that can’t remember] remembers” is a big one. Loves talking about memories and remembering.

Aurornis 1mo ago

> Sentences that orbit a point, then jump to it like it's a revealed insight. That’s accurate in my experience, except some times the point isn’t even revealed. I use LLMs for a lot of codebase exploration where I ask it to map out how something works. It will come back with a wall of text that says everything except the specific key things that I need to know. This leads to extra turns where I have to prompt it to finish the explanation and complete the thoughts. At first I thought I was doing too much skimming and missing the insights, but even after re-reading output it’s often just not there. It talks about the insight and things related to it, but it forgets to actually include it in the output until I specifically ask again.

double-u 1mo ago

Absolutely, the comments are killing readability. Next to /simplify I have to run a special comment cleanup pass and even that gets me halfway there. Striking to see then when letting Loki take a pass and it renders the entire comment block to a clean and neat one-liner.

andrewgleave 1mo ago

The glib epigrams and aphorisms it shoehorns in to all prose is by far the worst regression of any model I can recall in terms of simply generating simple, clear output. I cannot think of another model that's gotten worse at writing plainly while being explicitly instructed to do so. Infuriating. I've switched mostly to Sol and if I have to use Opus, the first task once the code is written is to ask Sol to strip and re-write (from the code as ref) all documentation Opus wrote.

rayiner 1mo ago

> 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. A lot of people write like that, lol. I call it the "theater" mode of writing--the plot twist comes at the end.

stingraycharles 1mo ago

> Sentences that orbit a point, then jump to it like it's a revealed insight. Is this inside the thinking tokens, or the output? As this type of stuff is expected for thinking, because of the whole CoT / “think step by step” works, as this is optimal for the way LLMs work with attention and next word prediction. So the fact that it first “orbits” a point only to get to the conclusion afterwards is the system working as designed. Eg “what is 3 * 3 + 5?” without CoT, it would just just answer “8” for example. with CoT, it would answer something like “<thinking>I need to think step by step. 3 * 3 + 5 can be rewritten as “(3 * 3) + 5”. I first need to calculate 3 * 3 = 9. Now I need to calculate 9 + 5 = 14. That was the last calculation. The final answer is 14. I now need to give the user the final answer. </thinking>. 14“ Etc.

loopmonster 1mo ago
It's the output.
- stingraycharles 1mo ago
  And you enabled thinking?
  - loopmonster 1mo ago
    Why are you doubting me? Have you tried Opus 5 yourself?
chuckadams 1mo ago
You forgot about 1000 lines of "<thinking>Wait, but different idea here</thinking>" ;)

jonstewart 1mo ago

Pondering this one night last week, I realized that because LLMs can only reason with written language, what we might be seeing emerge with Opus’s load-bearing mumbo jumbo is its own creole for structural reasoning. Not only are our brains wide, our senses are, too. I slow down to a crawl when I have to read actual math in a CS paper, but show me diagrams and I can reason about whatever sort of data structure or algorithm, no problem. Opus by and large can’t and its adaptation has been to adopt metaphor for structural reasoning. So while it may be exceedingly annoying to chat with, I sort of wonder whether this metaphorical-reasoning behavior has been selected for precisely because it leads to better coding outcomes.

globnomulous 1mo ago
> because LLMs can only reason with written language Is that right? Think of code that draws a square, the representation of that code in storage, the movement of electrons, and the 'actual' square on the screen -- these are all to us transcriptions of same thing across different domains or media, and we can deterministically translate back and forth between them, but there's no real, actual, essential identity property. The code isn't the square. The electricity isn't the code. The storage isn't the electricity. I think of LLM reasoning and output similarly. The underlying graph of weights, matrices, and other data aren't knowledge, understanding, or language. 'Translating' the system's output to language is jusas valid and correct as translating it into some visual representation that would be incoherent to us, like a sequence of flashing lights or imperceptible noise patterns projected over an image of a dog. I guess this is all a very long winded way of restating Chinese-room problem: we feed the man in the room a message; he returns one that, for all the world, is indistinguishable from a "real" response that you and I might send, but, like you said, he has no access to sense data. He also has no access to the biology underlying real mental processes. He also doesn't have any personhood that we can discern. He has, rather, gradually developed through reinforcement the tendency to provide responses approximating all of all of that. I'm not sure the epistemological question "does he understand" (which is what the Chinese-room problem asks) has any meaningful answer. There's no mind, so there's no understanding. What there is, rather, is a system that generate patterns that we map to language and that our brains therefore map to communication, personhood, meaning, etc. It's the square I mentioned earlier. It's to us a convincing simulacrum, and it may be faithful enough to us to stand in those things, but that's not what it is. My sense is that LLMs are (a) the big-data Pyramids of Giza and (b) a consequence of hardware and software developing ways of generating abstractions that capture and generate more complex patterns than were previously possible to capture or generate in a manner comprehensible to humans. Everything humans do follows some kind of pattern. Language is the perfect way for a machine to capture that, because is simpler than the world itself and has clear rules and patterns, encoded in representations computers already have, that, modeled well enough, can generate output indistinguishable from the real thing -- what you or I might do with it. But the pattern matching that it does, and that we translate into language, is much more numerically rigorous and complex than anything you or I consciously do with words (hell, most people can't even figure out when to use "lie" vs "lay") and not doing what you or I do with it. It's not language. It's the square on the screen.

marginalia_nu 1mo ago

I wonder if this is related to their text watermarking. Given how well defined the terminology is in programming, imposing additional constraints (like SynthID) might be expected to give rise to these types of linguistic artifacts. The text needs to be long enough to watermark, and it needs (but fails) to find synonyms in a highly constrained class of words, so it resorts to inventing weird technical language that sounds like if you put buffy-speak through a thesaurus.

parkersweb 1mo ago

Oh yes - exactly this. The way it articulates re-factors in my current project has got so elliptical I've had to start asking it to translate into human speak - it's like it evolves it's own language to talk about the project. I've lost count of the number of times I've asked it to reenforce in memory not to use such verbose comments - and the number of times I ask it to re-look at an assumption it's made for it to return saying "investigation complete. And it's not what either of us was expecting"....

throwaway894345 1mo ago

It’s a strange feeling as a native English speaker to read the entire sentence and know every word, for the sentence to be entirely grammatically correct, and still have no idea what it’s trying to communicate. Another problem is that it will open up all sorts of tangents about nits that it encountered, but it will often not tell you that it’s a nit or give you adequate context to realize that this paragraph is exceedingly low value until you’ve spent a bunch of time and energy trying to make sense of it. I’m curious if anyone has any suggestions for prompting agents to improve their prose. I’ve had some okay results with “optimize for clarity, don’t dump every thought on me, treat my attention and focus as constrained resources, stay focused on the task at hand”.

throwaway_7274 1mo ago
I think it’s no longer speaking human language. It used to, when it was mostly or entirely trained with imitation learning of human-generated text. Now it’s increasingly trained with RLVR, and there’s far less optimization pressure on actually speaking English (or Punjabi or Mandarin). It still uses English words and syntax in its output, but the semantics are drifting more and more. It’s basically speaking in a code that superficially resembles English.
- big_paps 1mo ago
  Thats scary
- akomtu 1mo ago
  Alien Slop Intelligence

nater5000 1mo ago

The excessive commenting has definitely been noticeable and very annoying. I'm not against abundant comments as long as they're pointed and appropriate, but these models are literally just leaking their overly verbose output into the actual codebase.

hackitup7 1mo ago

Perfectly captures it. Opus writes like it's an insecure person trying to impress a first date. Big words and strange structural rhetorical flourishes for no purpose. Like dude I'm just trying to summarize a few emails and meeting notes, I'm not prepping for the vocab section of the GREs.

agentdrek 1mo ago

I wonder if I am not bothered by the useless verbosity of these things because I've been so immersed in business speak for so long. I am already tuned on quickly "finding the nugget" of useful info in blobs of what people send me. So it's mildly annoying but I can find the signal well enough without actually reading word by word.

artdigital 1mo ago

Do you have some examples of this? I can’t fully imagine how sentences like that actually look like (not native English here)

gwd 1mo ago

> 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. Yes, the "Y would make more sense, but the doc says do X..." YOU wrote the doc, if it doesn't make sense, change it! But of course, it can't tell who wrote the doc. I wonder whether its tendency to scribble status updates and todos and decisions all over whatever it's working on is a side effect of its amnesia -- it can't follow the side-quests and knows it won't remember to do them if they're not written down somewhere. FWIW I haven't had the problem either of Claude lying to me, or of going off and doing its own thing; if anything I've been somewhat frustrated when I ask it to start something, go AFK, and come back to find it stopped a short way in to ask my opinion on something trivial. I generally have to explicitly say, "I'm going AFK for a chunk of time. My goal is for you make as much progress as possible before I come back; try to make reasonable judgements and only stop if there's something where you're really stuck. We can always change it later."

bayganyo 1mo ago

I’ve found its response verbosity to be mentally draining. It disregards claude.md instructions to keep responses short. Eventually, I added a stop hook that blocks it if it exceeds 150 words. It’s then forced to redo its output to comply, and it’s like night and day. I’ve also added stop hooks for words in its output that frustrate me, like “honest” or “honestly”. The excessive comments in the code it writes are absurd. Completely ignores instructions not to write comments, even after pointing them out repeatedly in a session. I need to figure out how to add a stop hook for that too.

eternaldao 1mo ago

Claude offers money credits and double usages but take them out and Claude becomes almost unusable where it would take opus about two - three high effort conversations to exhaust my session quota in Pro. I once extended my claude code session beyond the session limit, and thought they are too generous in offering 100 dollars worth of usage. It was sonnet, for a somewhat mechanical task - and it spent 13 dollars worth of usage after exhausting my quota mid task. Only a few months back, I was awestruck by the quality of Opus 4.6 and jumped ship from chatgpt to claude. Even in technical tasks, Opus has to be told to limit token spend, it treats it as infinite budget - it will spawn a subagent to read every file just to get one line summary when I ask it to sort a messy folder of past ai chats. Thank heavens I was not doing it off machine, it would burned off my monthly usage and credits.

jakevoytko 1mo ago

It's clear that we're not the audience; it writes to be read by its training evaluator, not a professional software engineer. Professional software engineers can't read this word soup and are desperately trying to find ways to fix it. It feels like it found a register that games the evaluator, where it can ramble forever and rarely be marked wrong while slowly racking up points as it talks more.

renegade-otter 1mo ago

"writes too elliptically" Was this written by Opus 5?

insane_dreamer 1mo ago

100% agree. “Just make your point in plain English!!” Very frustrating and takes me a lot longer to understand what it says. Also presents too many points as once instead of being able to review and decide on each one in sequence. Re comments: same experience, and I had to show it my edits of its comments to add to its memory as examples to follow. It adds explanations of “how we got here” that should go in the ticket or maybe the commit message but not in the code. It also tends to over complicate things. I’m no longer worried much about accuracy but I find my main job is to challenge it and suggest simpler alternatives.

mlsu 1mo ago

Everything that claude writes fits into the same aesthetic structure. The aesthetic is that of an expert slowly revealing an insight to the user. The actual content doesn't matter. - "Introduction that rephrases your prompt." - "3 paragraphs, with one section of bullet points" - "The Twist" - "The Bottom Line" It's really obvious once you see it. Every single prompt, from a quantum physics question to a mundane observation about California burritos, is phrased in exactly the same way. This is obviously an artifact of post-training but it's also kind of how you can tell that this thing is a lot closer to a blindsight scrambler than real intelligence.

zucked 1mo ago
The second bullet point, down to the comma in the middle of the sentence, is what has been driving me absolutely batty of late. It's a surefire tell that I cannot seem to beat out of my outputs. It CONSTANTLY does it, even when you say not to. Between that and the insistence on "this, not that" structure makes me want to install the caveman skill and use it even for non-code workflows.
- craigmcnamara 1mo ago
  This load bearing concern belt and braces.
  - EdwardDiego 1mo ago
    My personal bugbear is its usage of "grain" where normally you'd use "granularity", if at all.
    - ltrg 1mo ago
      Yes! Also everything's a "gate" that needs to be "wired up".
      - paradox460 1mo ago
        Let me get my fence pliers

vorticalbox 1mo ago

I’ve always disliked the opus models whenever I use them after they have done the task they rattle out massive reports about what has changed or worse actually save that to disk even after being asked not to do it.

wouldbecouldbe 1mo ago

The single biggest annoyance, same as with fable, is that it overrules your prompt and does what it thinks is better. Even small things, sometimes it goes of a rant of 20 min doing random shit. And they are so condescending while doing it, it's unbearable. I'm honestly starting the believe the scifi fantasy of AI locking us up, or killing us, for our own good. I've had Fable & Opus 5, they are the same class of annoyance, write entire test suites when I just asked a simple verifications question, write to production database, deploy without permission, even after deploying and breaking my production API claiming it was not down. Then having to argue & plead with it to listen that they were wrong. They are without a doubt the most powerful models, but also the most smug ones.

deleted 1mo ago

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jaggederest 1mo ago

I have been doing a thing that I think is helpful - basically a notes folder, each doc has a title, the comments in code are only allowed to give a few words and reference notes via those tags, and I've built tooling around the notes and review them regularly. So it deduplicates and centralizes the slop, at least. Lint is the LLM's best friend and it works on doc too. My lint rules ban long comments.

UltraSane 1mo ago

Opus 5 sounds a bit like the dialog in Children of Dune where they talk like they are constantly trying to prove how smart they are and not actually communicate.

SubiculumCode 1mo ago

On the other hand, Opus 4.8 had an annoying habit of declaring a huge mistake was found, then two sentences later abruptly change its mind and say that it was in fact all okay. That's fine for chain of thought, but in the verbose output, it can lead to wrong impressions by the user.

quaverquaver 1mo ago

I have codex rewrite all Opus' comments with great results.

quaverquaver 1mo ago

maybe the comment length is a ruse to increase token consumption

wiremine 1mo ago

This is the most succinct summary of my interactions with Claude: thank you! I feel like they need high school English teachers in the loop on the next ground of training to whip the language in shape.

fastball 1mo ago

In my experience your criticism of the writing is valid in all Claude 5 models, so I wonder if it is somehow related to the new tokenizer introduced in gen 5.

arkmm 1mo ago

Since reasoning tokens are just text, I think the models have learned to squeeze in some computation in their output writing as well. So they're incentivized to be correct but long-winded, as it gives them more time to think. It's kind of the equivalent of filler words for humans, except LLMs can actually word-vomit something intelligible.

galaxyLogic 1mo ago
Right, but could that also be because ... the more long-winded they are, the more you pay for their output.

preg_match 1mo ago

Comments are the biggest problem. During code review I ask it to compact comments and its idea of compact is like… removing one sentence in a 5 sentence comment. Comments are a huge maintenance burden. They can, and will lie and need constant updating. They mislead the own model later on.

colordrops 1mo ago

There really needs to be a "terse mode" for Claude. It's WAY too loquacious. I'm hoping they aren't doing it on purpose to burn tokens.

avereveard 1mo ago

[dead]

rsalus 1mo ago

Yeah, +1 on the comment verbosity. Left alone it's actually insane. I've had to setup enforcement + templates (use ASD-STE100) to keep the cruft down. I'm worried this may impact the quality of outputs though - haven't measured it.

aetherspawn 1mo ago
I also use the ASD-STE100 trick and it works pretty great, but the places that it decides to put huge comments are really weird and a lot of the time I just ask OpenAI sol “rewrite the comments in this file without slop” and it does a much better job for comments.

ls-a 1mo ago

This is what news headlines did for decades to bait you into reading the details. I wouldn't be surprised if AI companies do that intentionally to consume more tokens trying to understand what had just happened

hi_hi 1mo ago

My biggest pet pieve isn’t the LLM-isms themselves, but people who aren’t aware of them releasing documentation that’s clearly AI generated and being indignant when I ask “is this AI generated”

Jagerbizzle 1mo ago

Replying here without having read any of the sub-replies so I apologize if this is a repeated theme. I have explicit markdown about telling the model to not write comments. "Every time you consider writing a comment, instead consider re-writing the code that questioned you to write said comment to begin with. Write comments only when logic is complicated or unclear, otherwise 'comment' via naming." The results thus far have been much better. I'm seeing code reviews at my work where indeed, we have 10 line comment blocks for a line of code and now I just straight up don't read comments. Sad state of affairs -- (emdash deliberately used here) but I guess the sooner the human gets out of the loop the better in this new world.

indrex 1mo ago

I had to setup hooks just to catch the and ban them in the CLIs. Most of what Claude writes is simply un-readable.

cromka 1mo ago

One thing I noticed working with Sol and Fable is that I can speed read, literally glimpse over Sol output and understand what it's saying. With Fable/Opus it's the exact opposite: I have to read every god damn sentence, sometimes twice, and often already losing the bigger picture in the process.

kaizenb 1mo ago

"Save in memory to always use ASD-STE100 Simplified Technical English when you talk to me" Use this to reduce the text output.

ako 1mo ago

Why are you so distracted by style? I see it too, it could be improved, it might be improved, but I don’t care as long as it get shit done. And it does, tons of shit gets done. And the communication is usually more informative than how coworkers document their work. Can it be improved? Yes. Does that mean I can’t use it? No.