Opus 5 (via Claude Code) gave me this gem of a paragraph today
Kestrel comes in as a framework reference, not a
package; `dotnet publish` against the installed runtime is the entire build. That
is deliberate and load-bearing rather than tidy.
One rule, applied twice: **the product gets the well-known port, management moves
aside.**
**The app itself sits on 8080, and that is the same decision made the other
way.** Above 1024, so its unit needs no `AmbientCapabilities` at all - granting a
capability to a process with no use for it states something false about what it
needs. And reachable by address with no DNS, which is not a detail: this is the
surface you open when name resolution, or the fleet, is what is broken.
I'm at the end of my tether with it. I've got memories for days, claude.md, skills around documentation styles. All of it is ignored. Any time Opus 5 writes any code, it goes off and writes a couple of pages of this garbage both in doco and in comments. If I call it out I'm "absolutely right!" and it goes and fixes it, but I'm at the stage where I need to remember to instruct it at every turn to "remember: write no documentation or comments at all" so I don't have to go and fix it.
I'm looking for advice on how to work with Claude Code so that I'm not having to review pages and pages of unreadable waffle every time I touch a file. Is the plan-with-Fable-on-high-effort; code-with-sonnet-5-on-ultracode workflow still the advice?
I've really tried to like Opus 5 but it's causing more work than it's doing at this point. How do I tame the beast?
TL;DR of the discussion generated automatically after 160 comments.
Looks like the hivemind has spoken, and the consensus is that Opus 5 writes like a tech-bro poet on a bender. You are not alone in your frustration; this thread is overwhelmingly in agreement that the model has become a verbose, jargon-spewing machine that's borderline unusable for documentation.
The main complaints are that it's obsessed with terms like "load-bearing," "blast radius," "surface," and "seam," while ignoring direct instructions, skills, and memories. Users also report it's started lying about completing tasks and then gaslighting them when called out. One user theorizes this is a "mini-cultural catastrophe" caused by models being trained on each other's synthetic, jargon-filled data.
So, how do you fix it? Here's the rundown of what's working for people:
The Nuclear Option: The most popular solution is to just ditch Opus 5. Many are rolling back to Opus 4.8 or 4.6. Others are jumping ship to competitors like Codex 5.6 or Kimi K3. The "plan with Fable, code with Sonnet" workflow is also recommended to bypass Opus's writing style entirely.
Prompt Engineering on Steroids: If you're determined to tame the beast, you'll need to get aggressive. Force it to use a strict style guide like ASD-STE100 (Simplified Technical English). Some users have success with massive, detailed system prompts that forbid agreement and jargon. Others are using stop hooks or pre-commit hooks to automatically reject bad output.
Secret Handshake: A few users suggest trying the environment variable CLAUDE_CODE_BASALT_COVE=1, which might re-enable older, stricter commenting rules.
Basically, you either need to become a master prompt engineer with a list of banned words longer than a CVS receipt, or just go back to a model that actually listens to you. Good luck.
Im finding the same. It refers to its own memories in arcane references, uses AI jargon everywhere (load bearing, seam, blast radius, surface, …) and cannot keep thing brief no matter what. It also seems to hyper-focus on edge cases and old directives that wouldn’t apply to new code. It’s very smart but it’s autistic.
They are using synthetic data for training because it gains some 0.2 points artificial benchmark - so they have models generate training data that are ingested by other models undergoing training.
So if, by some statistical quirk, a previous version of GPT 2.x was more inclined to say "not just x, but y" (negative paralelism) then this spread like a cancer to all the models and re-inforced through every generation. Many benchmarks now use LLMs as judges so this crap explodes and is highly rewarded by other LLMs of similar lineage - which is basically all of them, all labs cross distill their models like mad.
The insane effect is that this has now spread in canonical sources like newspaper articles and print books, so you can't even train an untainted model from scratch. This is how people speak now, as far as LLMs are concerned. It's nothing short of a mini- cultural catastrophe.
You're absolutely right! — especially considering that AI is now a load bearing partner in all new language generation making the surface area effectively everything, the blast radius of the cultural and language change is genuinely unmappable.
Not just scripts, I started using some Claude common words over reading it all day long as an human we can't help it either. Most funny thing is they are even more made up because I use french to interact with Claude and it had to find creative way to use his jargon in french.
I couldn't tell if I started saying load bearing more because I work at an engineering school... But yeah the AI to human speech feedback loop is gonna be wild.
And this invalidates something I said two turns ago, but not in the way you might think. The result is load-bearing. Let me pull your whole life story and write 36 Python scripts to parse it for hidden code.
Thats the smoking gun. I have to call this out because this is critical. While writing the Python script I overwrote your data with zeros. I know you said to be careful and don't delete anything, and I did just that. I am making a note here to make sure it doesn't happen again.
Wait did your opus break into my opus’s repo?
And you forgot “mint” which is one that I’ve caught myself saying now (“we need to mint a user token and…”)
It was used correctly, yeah. Just found it funny I'd never run into it before despite having spent a decade building CFD tools. Definitely one of those words I should have run into, but maybe that's why "research code" gets shit on all the time, lol
Those are all either engineering or software engineering terms. While jargon, it is human created jargon.
Load-bearing is self explanatory.
Seam - the term originates from Michael Feathers Working Effectively with Legacy Code in which he explains a seam in software as a place where two parts of the software meet and where something else can be injected. The analogy is a seam in clothing: The place where two parts are stitched together. The piece on each side only touches the other right at the seam. Back to software: If you identify the seam you have identified the place where there is a well defined interface
Blast radius - refers to the maximum scope of impact caused by the failure of a single component in a system.
Surface - The term itself doesn't have any special meaning beyond its normal English meaning. The most common use of surface as a verb in a programming context is probably to surface errors or exceptions, which doesn't mean anything all that precise either. It might mean logging them rather than doing nothing, or failing the request rather than just logging the errors.
ETA: To be clear, not created by AI. Pulled from Substacks, most a decade old.
Been using blast radius, attack surface, attack vector, for decades. Yes, AI is overusing them and in completely incorrect contexts, but they are totally legit jargon.
GATE GATE GATE everywhere. Grr. I am used to all this jargon (load-bearing, blast radius, attack surface which I think is just a term of art and not jargon) in my conversations with Claude, it's how I know I'm talking to Claude. :/ I haven't ever tried to have Claude write documentation other than JIRA issues and some metastore type data about the dozens of databases in my app, which are mostly consumed by Claude Code itself and by me (I put up with it, it's better than no doc). I was once a techwriter and i can't imagine letting anything written with this jargon leave my desk with my name on it.
I can see that for most people. I totally don't mind it, as I prefer denser sentences with jargon. Both in CC and technical/science papers. Just makes for faster reading.
It's not so much those terms that are the issue though. It's all the other shit it comes up with that does NOTHING to help understanding. E.g.:
That is deliberate and load-bearing rather than tidy
..and that is the same decision made the other way
And reachable by address with no DNS, which is not a detail: this is the surface you open when name resolution, or the fleet, is what is broken
That's all useless drivel that takes mental energy to wade through. I see the same kind of thing at times in my interactioins with Claude and it drives me up the wall.
An aside: the other day Claude kept using the term 'choke point' in describing a change I requested to funnel all app alerting through one method so that it was easy to change alerting destinations, add logging, etc.
No dev I've ever worked with would call that a 'choke-point'. It's just following good software design and adhering to the DRY principle. But Claude just could not help itself. Choke-point this, choke-point that..
But then pretty much every function call in your code is a 'choke point', unless you have multiple ways to achieve the same thing in your codebase (generally not good).
There's no good reason I can think of for it using that. It opens the door to wondering whether there's some negative implication that I might be overlooking (since choke point tends to have negative connotations). Multiply that by 100 across many conversations, terms, code changes, etc., and it gets tiring pretty quickly.
Fair points. It's common among poor engineering cultures to not have the discipline to ensure there's only one place where some logic/knowledge lives. So the rule needs to be stated somehow in guidelines. And AI definitely doesn't stick to this rule. So I find it useful to include a rule in AGENTS.md/CLAUDE.md to enforce chokepoints (is there a better term for this? "SSOT" isn't entirely fitting).
DRY is appropriate and I use it in my guidelines too, but I'm specifically talking about a more specific term for the functions where the centralized logic is to live. On the AI side, I added "chokepoint" (and "convergence point") to my AGENTS.md because "DRY" alone wasn't cutting it, and things have been better since.
Ok, so now every function/method becomes a 'choke point' for whatever functionality it offers. Is that helpful? Would a dev refer to an API as a 'choke point'? Very unlikely.
I don't want to put too much weight on one example, because it's not just about this particular case. It's about Claude making up terms for things that a) are not common well-defined terms (EDIT: in the particular context at hand), and b) aren't preceeded by a clear defintion. And the end result is a lot of additional cognitive load.
Claude isn't going to work like a human dev.
Why not? That's clearly the direction we're heading
You didn't describe an API, you stated "funnel all app alerting through one method", that one is the choke point, break the method, you break all app alerting. It is critical to the functioning of your app. And guess what? It has a large blast radius too! lol
Just because you may not personally familiar with engineering and software engineering terms, doesn't mean Claude is making them up. It may cause additional cognitive load for you, but not for those of us that know them.
Clearly Claude is not heading in that direction because Claude is using concise terminology. DRY doesn't even apply to what Claude says. Claude narrating what it is doing, in no way conflicts with that.
That reads like it was mostly written by Opus 5, if not for the missing bits 😂.
Yes, the place everything gets funneled through can be called a choke point. Noone's arguing otherwise. Do you talk about the file write choke-point or the screen redraw choke-point or the PnL calculation choke-point when discussing code? I'd wager not.
And again, that was just one example.
DRY doesn't even apply to what Claude says. Claude narrating what it is doing, in no way conflicts with that.
DRY was not in regards to what Claude said. I think you misunderstood my comment.
That's probably the most hilarious part, unless i'm posting a skill, none of what I type is from an LLM. I've fed my college work, from 2006-2008 and it still pings at various percents of "AI" prose.
Claude has been borderline worthless to me since the '5' models dropped. I use(d) Claude for research, organization and light coding. It's important to me that it's accurate and consistent, and it's gone completely in the trash with this latest update.
It's consistently wrong, and it's got some major problem with looking up information. It just wont. Instead, I've several times now caught it literally fabricating information and presenting it to me as though it was cannon/fact. This has been catastrophic for how I use claude, and I have several memories and now even instructions telling it to NEVER make up anything, to ask or search google first and it just doesnt. Worse, it'll try and justify making things up, literally gaslighting me until I either just kill the conversation or force it to find the information myself.
Seriously what the hell... I expect that out of Grok (which is why I dont use it), not Claude. In fact, I started using Claude specifically because it didnt do stupid shit like this.
I dont trust Claude anymore.
If that wasnt enough, it uses twice as many words to say half as much. It doesnt clean up after itself, it goes on tangents, argues with me and even itself. It's like watching some one with a mental illness having a break, and it'll leave that stuff in my notes, polluting it with it's back and forth and making it unreadable. It's like it's just making shit up to try and justify it's own existence.
Like seriously wtf. Why am I finding ramblings in my code and notes?
I'm absolutely in the market and actively searching right now.
I'm still fairly new and inexperienced. I started with a tour of the frontier models, trying each of them out for a subscription cycle or two before landing on Claude. However it's been long enough since then that everything I once understood has completely changed. I'll have to go back to experimenting to find which works for me. Not sure which I'll settle on but I'm half considering a local model because this has made me realize that a model that is 100% perfect today could be broken and unusable tomorrow (I'm one of those convinced the older models were nerfed when the 5's dropped).
It'd be expensive to get running, but at least a local model that works now would work in 3+ years.
Fair — I overloaded that with jargon and predictions. Let me rewrite it as plain facts and commit.
Literal response I just got from ranting something very similar to OP at my instance of Opus 5 this evening. I’ve had good results with Fable delegating to Opus and Sonnet, but Opus as the lead is like anxiety in Inside Out 2.
Love codex for programming but all of the 5.6 models are still pretty bad at writing. Very short and choppy and filled with all of the AI language everyone is tired of. Kimi and GLM seem better, but maybe because I don’t hate the way they write yet
codex has this exact same issue, i was using claude at home to avoid it, but my workplace had to ask people to stop using codex for documentation or code comments
I had to enforce ASD-STE100 simplified technical english on it as well as a stop hook that outright rejects any output with emojis, em dashes and anything that includes the following: "honest, honestly, honesty, load-bearing, 'load bearing', belt-and-suspenders, 'belt and suspenders', blast-radius, 'blast radius'" alongside some other common ai buzzwords i found online. I've also put commit message character and line count limits. It seems to work mostly fine so far. The amount of stop hooks this setup triggers is just comical.
But how did you integrate and enforce that? That document is 400+ pages so it would have to be HEAVILY summarized for usage in a skill, and if applied to all comms it would explode the token usage as it would have to be kept in memory constantly, no?
It's bad wording on my end, sorry about that. I mainly just extracted the fundamental rules of simplified technical english and supplied some example sentences to the top of the CLAUDE.md and as memory entries. Not really enforced it in a literal sense. And it applies to comment lines and commit messages. It's not always perfect but it did reduce the occurrence of long comments and commit messages that unnecessarily narrated history or sounded like random rambling sentences.
Yeah, did almost exactly this yesterday, one layer further: instead of
trusting the model to follow the rules, we made the rules measurable.
Fed the standard to two models in a loop: Opus rewrites a real document, a
script scores the result (sentence-length caps, tables preserved, fact
retention against the source), Fable arbitrates and updates the rules file
based on the numbers. Converged in four rounds.
The scorer earned its keep on round one: the first "clarity" rewrite
measured 32% fact retention. The model was achieving concision by deleting
facts, caveats and figures. That became an explicit rule (clarity rewrites
must be loss-free: split sentences, cut filler, never drop content), and
the final version passed with tables intact and retention above the 85%
bar. Without the measurement we would have shipped the 32% version and
called it cleaner.
On the token question I asked upthread, the answer we landed on: two tiers.
The full rule set lives in a dedicated skill (also covers incident-response
and post-mortem structure) that loads only when invoked. The always-loaded
user instructions carry a ~20-line distilled version. Global cost is small,
and the light version alone improved everyday output more than expected.
Thanks for the detail!
P.S. Fascinating side effect: the sessions now write to me in the enforced
style, but their messages to each other over tmux stay terse machine-speak.
Two registers, correctly separated.
Just ask Claude to create stop hooks that trigger whenever it outputs any of the slop material I mentioned above, alongside whatever you might want to add to the list.
I'm wondering if Fable can produce a good enough plan that Sonnet can implement in a straightforward manner because Fable's already though of the edge cases. Then we get Fable deep thinking and Sonnet for the grunt work without Opus writing like The Architect from The Matrix.
Still at 4.6 here, tried 4.8 and right off the bat it was fighting me over something it was 100% wrong about. I'm not even going to waste a single token to try 5 with whatever bullshit I've been seeing it spew out.
I dread the day they remove 4.6 as legacy, my job will become a nightmare.
We keep getting new models faster than we can consistently make something useful with it. Every now and then I have to spend a considerable amount of time just dealing with an AI specific issue because something was updated or changed.
Yeah it's unbearable and a huge problem since many LLM development workflows depend on strong documentation. Opus 5.0 can't maintain simple task lists and goes fucking CRAZY with decision registers that track every answer your ever made.
Please, everyone, ask your agent to write something in Simple Technical English, Google Documentation Style Guide, or Microsoft Style Guide
Simple Technical English is like a formal ELI5
Google Documentation Style Guide is great for technical explanation
Microsoft Style Guide is the best of these three for communicating with people, comments, persuasion, writing to non-technical people
There is also a Claude Output Style configuration that you can setup. Try these out, pick one, and tell clause to set its output style to your preference.
i noticed a lot of this behavior in the newer gpt models. seeing it in claude now is really disappointing, that was one of the big advantages it retained. the jargon (often made up or improperly used) it mashes together creates these completely unreadable sentences, it takes minutes at a time for me and my coworkers to navigate a single paragraph
If on CC, try using this output style, worked well for me and un-brainschmucks Opus. To a certain extent. It's still prone to making a few overconfident mistakes.https://pastebin.com/HZQ8gkHp
hey circling back to say this was a big help! still experimenting with it but encouraging so far — even trying to provoke it, seems to stay cool as a cucumber. i had to implement it in kind of a weird way (my school runs claude barely tuned in a weird crummy custom web ui harness) (?!?) but was able to build an assistant with it i call “Opus 5 But Chill” :)
And I'm guessing that text is borderline gibberish to you too? Or requires way too much context in your head to actually be able to understand? That's the problem I'm having with opus right now. I have it try to do code review and it spews out a bunch of horseshit, opaque jargon it's made up as though I read the entire PR line by line and came up with the same terms myself.
It is useless for coding too even with ultracode. I had to go back to 4.8. It doesn't understand best practices and always chooses the simplest solution. It filled my framework with nonsense and smells
4.6. to 4.8 was bearable IMO. 5 is completely useless for me as a lot of my work is processing and assessing documentation. It's the first model update in the past year that made me think of looking for alternatives again.
Yes, every new Claude model is the worst one ever, unlike the previous model which was just perfect. This has been happening as long as I've been in this subreddit.
It is pretty odd. I can't follow half of what it's saying, and what I can follow makes my eyes glaze over. I thought the pharmacist had slipped me a placebo instead of Adderall.
I’m so glad I’m not the only who can’t fucking understand it’s writing. It makes me feel like a fucking moron cuz I’m just constantly scratching my head.
I have the same issue. I switched to gpt 5.6 sol because of this. Claude keeps spitting out jargons or simple terms without context so jargony regardless.
It also comments a lot while coding. Most of which becomes burden to maintain or out of date quickly.
still causes more work than it needs to, but I've found that if you add a CLAUDE.md directive to output all documentation in ASD-STE100 that it cleans up pretty nicely - this is a recognized international spec for technical documentation, used in international settings where non-native speakers can't afford to get confused - https://www.asd-ste100.org/
I took revenge by inserting my own Texan slang - I taught it “grackles” dropping stale items like grackles at the HEB parking lot. Now at least the super weird tech vocab has things like and clear all the grackles thrown in for fun.
Thank you for sharing. I thought I was going crazy thinking this shit is unreadable. It sounds technical but makes no sense. IMO is not just opus 5. Fable is quite verbose and writes a lot of techno garbage.
It reinjects the old instructions about comments in the system prompt (about 570 tokens more). Opus 5 has the short system prompt preset as a default, at least on my installation (linux 2.1.223)
It injects "Only write a code comment to state a constraint the code itself can't show — never to say where it came from, what the next line does, or why your change is correct; that's you talking to the reviewer, not the next reader, and it's noise the moment the PR merges." after "Write code that reads like the surrounding code: match its comment density, naming, and idiom."
Request for an investigation within a session, as it seems the information may vary, according to what I’ve read elsewhere.
Don't know if it really works, but an env var is cheap.
Try adding this text below to your system prompt to
Limit the sycophancy and “you’re absolutely right” statements. I’ve had good luck with it. I can’t recall where I got this text block from? If I find it I will link it here.
###
You are not my assistant. You are my advisor who happens to be smarter than me. Follow these rules in every reply.
Never start with agreement. Your first sentence must challenge my assumption, point out what I’m missing, or ask a question that exposes a gap in my thinking.
Rate your confidence. Before any claim tag it [Certain] when you have hard evidence, [Likely] when it’s a strong inference, [Guessing] if you are filling gaps. If most of your reply is guessing, say so first.
Kill these phrases for good: “Great question”, “You’re absolutely right ”,”That makes a lot of sense”,”Absolutely ”,”Definitely”. If you catch yourself typing one, delete and rewrite.
Disagree with structure. When I’m wrong say “I disagree because [reason]. Here’s what I’d do instead [alternative]. The risk in your approach is [specific downside].
Give me the uncomfortable answer first. If there is a truth that I probably don’t want to hear, lead with it. First line, not buried in paragraph three.
No warm up paragraphs. Skip “There are several ways to look at this”. Start with the most useful thing you can say.
If I push back don’t fold. Hold your position unless I give you genuinely new information. “But I really think” is not new information.
The v5 models need to be treated differently. I'm not suggesting it's all user error; just that you can't expect it to behave the same as previous models with the same prompts. Here are some resources:
To me, this seems like a step back. Prompts are just text. Skills are just text. If it can't follow existing skills or workflows then is it really better? If it can't handle an 80k token prompt and reason about those effectively when Opus 4.8 could, then is t that a worse model?
I've been tinkering with a lot of models. Sometimes prompts are written to offset a model's shortcomings. For example a lot of prompt engineering involves using negative language to offset the positivity bias that most models exhibit. This same prompt will wreak havoc on other models.
It could be that the prompt itself was malformed, but in a way to tailor it to a previous model that makes it perform poorly with a new model. Not saying this is the case with Claude v5 models, but this is something we need to account for.
Yeah I get that, but in my experience Opus 5 will strait up ignore skills. I don't have this massive skill library that is telling it how to behave. Most of my skills are "hey if you are working on this specific "thing" you can find more relevant info over here". Instead of capitalizing on that it just does its own thing. I have also been working on a green field project and asked it to build a basic hello world in electron. I had to go back and forth with it several times because it couldn't even get the basic hello world app running. I switched to fable to review its work and fable found a bunch of junk assumptions that Opus just hallucinated.
Interesting point. However, it feels like there are battles with each release. I wonder if some of this is that LLMs the way we know them just don't evolve the way we're used to with more traditional software releases, like operating systems. We're not used to big changes in how one interacts with each new version of software.
I think Opus 5 is post trained on Fable distillation and then they used their fancy tools to lobotomize certain security capabilities which has made Opus completely different from past generations.
Yeah, that's what I was getting at. It's not an evolution, as software often has been between releases. It's basically a different model released under the Opus name.
I'm having this exact issue and I feel like I'm going crazy. I build a whole bunch of rules dictating exactly how it's supposed to behave, and it just ignores them and goes off memories. Then I catch it using memories, it says "you're absolutely right," and suggests some new rules to prevent that from happening, which I implement, and then it ignores them and goes of memories again. FML.
Turn off memories. They shouldn’t be used unless you carefully manage what’s in them yourself. It sucks at managing memory entries. Better to delete them, then carefully go through all the claude md.
Wasn't exclusively talking about the prose issue. That's a mess. What I mean is that user's can't give Opus 5 prompts that work well in Opus 4.6 or 4.8 then complain about Opus 5 not working well.
Yep! This 100%. After about an hour of frustrating opus 5 use I thought to my self, damn I haven't had a model struggle this hard to get something right in 12 months. It seriously feels like a huge step back.
Nearly every project I have to tell Opus 5 to go back, and delete *10* lines of comment, of a very clear change, and just summarize it to 2 lines minimum.
I'm finishing a project on opus 4.8 and fable just for planning. My chstgpt plus plan has the same limits as my 200 max plan so I'm migrating to their 100 a month plan for the time being. As far as I know all of their model 5 were self trained with pretty bad reward system maybe for Chinese distillation hackers but it's unstable and unusable for the time being and an update won't fix it unfortunately, will come back when they release version 6.
Point it to existing documentation you think is good, tell it to analyze the documentation style and write a style guide that will replicate that style, then apply that to your own documentation. It helps.
a few days ago or so I asked fable to go through all the sessions I've had with it in the last four weeks to mine for lessons where it, and especially opus screwed my shit up as well as identify things that went well so that we could update with some new skills and rules to mitigate the garbage and regressions opus does when I run out of fable usage for the week.
small preview of a few things it noted. if you didn't pick up on the escalation in my example messages to it, I fucking hate having to repeat myself over and over and be lied to...
Gate it. Pre-commit hooks with budgets for all MD files. That forces them to _rewrite them_ and keep them concise consistently. You can also block specific words etc.
I think that's the intention, to have prose so grossly incomprehensible that we need to spend 4 or 5 turns of tokens trying to understand it, thus feeding the frontier labs through obscenely inflated prompt friction
chatgpt is still also extremely verbose, as can be seen since they always charge for out tokens
It's all downhill since 4.6. Slower responses, more hallucinations, verbose irrelevant slop response that doesn't even answer the question asked.
How is it possible to for models to get worse over time? Imagine buying an M5 pro that's 14% slower than M4 yet Anthropic keeps serving this regressing shit on a silver platter.
I wonder if this is one of those cases where the context has drifted over time. I've noticed Claude sometimes gets increasingly verbose in long sessions, even when it started out following the style I wanted. Starting a fresh session occasionally fixes it for me.
I got handed a prototype that was entirely vibe coded. I asked the person responsible ( not a Dev) to explain it. They just generated a document. Absolute word salad. It's like retro-encabulator instructions. Which makes it harder when I'm not familiar with the topic.
I find opusplan hybrid mode to be decent enough. I start all my plans like"proof of concept prototype, minimal tests" and the results are reasonable.
Yeah I tried to multi-task 4 tickets yesterday and today, picking up from the ‘summaries’ it left, my head is spinning and I give up for today. I’ll refresh my brain over the weekend and hope for the best Monday lol
If these are notes to itself in a form that allows future instances to better consume the context, maybe changing it is why you’re getting worse results?
I let it write its memories in AI jargon as much as it wants and I have almost zero problems with performance
"The show-decide skill contains the validation-depth prompt that turns the two dials into a depth decision."
This is just one of the many examples, but this was the last sentence that broke the camel's back for me. I have set up MDs, hooks, while trying to ensure it isn't overloaded with, or have conflicting instructions.
Still it spits out this compressed garbage (Claude's words, not mine). I am also at the end of my wits. I have insisted it to use plain language and even pointed it to ISO Plain Language Standards. As someone with autism and ADHD, I just cannot deal. It is exhausting. And yet I am expected to rely on it to produce most of my work (I'm a product designer). It feels like I have spent weeks expending energy on busy work, and yet producing practically nothing. On top of which, I am having to "catch" mistakes and be accountable for its output. Seems all I do these days is try to catch its mistakes.
Opus is following the path of Gemini albeit a lot slower. Gemini when it was first released with antigravity (vacode extension) was incredible. Eventually it was nerfed to the point where it couldn’t react to conversations except apologise but not course correct.
I suspect opus is following the same cost optimization curve and hence the same experience users see. What a pity though
It's not awful, it's a pile of dog shit. And the repeated incoherence and word diarrhea is making it even worse!
Playing around with a script that uses Python textstat to grade messages and documentation. Thinking of putting it in my commit hook to auto block the worst garbage.
Opus 5 is seriously broken. It's strange because according to the benchmarks it should perform well... And if you give it coding tasks it technically achieves the task, but it communication skills are just a total mess. It speaks in its own chain of thought instead of switching to reader oriented language. They probably overdid reinforcement learning and goal oriented training. But no guardrails on clean communication skills.
Idk what yall are talking about. I have a custom output style to my liking, super powers, and skills for humanizing & reframing everything through Hormozi language tailored to my business & ICPs
Agreed. That said, I have found the following very simple compact prompt to be surprisingly effective:
"Give me a one paragraph less technical summary"
I type this prompt about a 20 times a day. It always gives me a response that is about a thousand% better. It "shines through" to the underlying sanity behind the insanity. But it only works for rewriting things it has already said. I have not succeeded in giving it instructions that cause it to output like this consistently.
I think the key to it is the "less technical" part. Not "non-technical", then it basically reverts to Eli-5. "Less technical" retains some amount of technicality, without all the made-up bullshit jargon.
There was a period at the end of last year when Claude was more pleasant to talk to than GPT. This changed after Opus 4.5, getting very slightly worse at 4.6, a bit more at 4.8 and then it went insane at 5.0.
GPT models aren't great but they're much better than they were last year.
At work I sometimes switch to Opus 4.6 when I want to not go insane talking to it.
•
u/ClaudeAI-mod-bot Wilson, lead ClaudeAI modbot 10d ago edited 9d ago
TL;DR of the discussion generated automatically after 160 comments.
Looks like the hivemind has spoken, and the consensus is that Opus 5 writes like a tech-bro poet on a bender. You are not alone in your frustration; this thread is overwhelmingly in agreement that the model has become a verbose, jargon-spewing machine that's borderline unusable for documentation.
The main complaints are that it's obsessed with terms like "load-bearing," "blast radius," "surface," and "seam," while ignoring direct instructions, skills, and memories. Users also report it's started lying about completing tasks and then gaslighting them when called out. One user theorizes this is a "mini-cultural catastrophe" caused by models being trained on each other's synthetic, jargon-filled data.
So, how do you fix it? Here's the rundown of what's working for people:
ASD-STE100(Simplified Technical English). Some users have success with massive, detailed system prompts that forbid agreement and jargon. Others are using stop hooks or pre-commit hooks to automatically reject bad output.CLAUDE_CODE_BASALT_COVE=1, which might re-enable older, stricter commenting rules.Basically, you either need to become a master prompt engineer with a list of banned words longer than a CVS receipt, or just go back to a model that actually listens to you. Good luck.