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giwook: I wonder how much of this is simply needing to adapt one's workflows to models as they evolve and how much of this is actual degradation of the model, whether it's due to a version change or it's at the inference level.Also, everyone has a different workflow. I can't say that I've noticed a meaningful change in Claude Code quality in a project I've been working on for a while now. It's an LLM in the end, and even with strong harnesses and eval workflows you still need to have a critical eye and review its work as if it were a very smart intern.Another commenter here mentioned they also haven't noticed any noticeable degradation in Claude quality and that it may be because they are frontloading the planning work and breaking the work down into more digestable pieces, which is something I do as well.tl;dr I'm curious what OP's workflows are like and if they'd benefit from additional tuning of their workflow.

summarity: Not claude code specific, but I've been noticing this on Opus 4.6 models through Copilot and others as well. Whenever the phrase "simplest fix" appears, it's time to pull the emergency break. This has gotten much, much worse over the past few weeks. It will produce completely useless code, knowingly (because up to that phrase the reasoning was correct) breaking things.Today another thing started happening which are phrases like "I've been burning too many tokens" or "this has taken too many turns". Which ironically takes more tokens of custom instructions to override.Also claude itself is partially down right now (Arp 6, 6pm CEST): https://status.claude.com/

andoando: Ive been noticing something similar recently. If somethings not working out itll be like "Ok this isnt working out, lets just switch to doing this other thing instead you explicitly said not to do".For example I wanted to get VNC working with PopOS Cosmic and itll be like ah its ok well just install sway and thatll work!

StanAngeloff: (Being true to the HN guidelines, I’ve used the title exactly as seen on the GitHub issue)I was wondering if anyone else is also experiencing this? I have personally found that I have to add more and more CLAUDE.md guide rails, and my CLAUDE.md files have been exploding since around mid-March, to the point where I actually started looking for information online and for other people collaborating my personal observations.This GH issue report sounds very plausible, but as with anything AI-generated (the issue itself appears to be largely AI assisted) it’s kind of hard to know for sure if it is accurate or completely made up. _Correlation does not imply causation_ and all that. Speaking personally, findings match my own circumstances where I’ve seen noticeable degradation in Opus outputs and thinking.EDIT: The Claude Code Opus 4.6 Performance Tracker[1] is reporting Nominal.[1]: https://marginlab.ai/trackers/claude-code/

mikkupikku: Cannot say I've noticed, but I run virtually everything through plan mode and a few back and forth rounds of that for anything moderately complex, so that could be helping.

Retr0id: This seems anecdotal but with extra words. I'm fairly sure this is just the "wow this is so much better than the previous-gen model" effect wearing off.

rishabhaiover: Nope, there is a categorical degradation in quality of output, especially with medium to high effort thinking tasks.

petcat: I have found that Claude Opus 4.6 is a better reviewer than it is an implementer. I switch off between Claude/Opus and Codex/GPT-5.4 doing reviews and implementations, and invariably Codex ends up having to do multiple rounds of reviews and requesting fixes before Claude finally gets it right (and then I review). When it is the other way around (Codex impl, Claude review), it's usually just one round of fixes after the review.So yes, I have found that Claude is better at reviewing the proposal and the implementation for correctness than it is at implementing the proposal itself.

ivanech: Hmm in my experience (I've done a lot of head-to-heads), Opus 4.6 is a weaker reviewer than GPT 5.4 xhigh. 5.4 xhigh gives very deep, very high-signal reviews and catches serious bugs much more reliably. I think it's possible you're observing Opus 4.6's higher baseline acceptance rate instead of GPT 5.4's higher implementation quality bar.

petcat: Maybe it's all just anecdotal then. Everyone is having different experiences.

virtualritz: None of this is surprising given what happened last late summer with rate limits on Claude Max subscriptions.And less so if you read [1] or similar assessments. I, too, believe that every token is subsidized heavily. From whatever angle you look at it.Thusly quality/token/whatever rug pulls are inevitable, eventually. This is just another one.[1] https://www.wheresyoured.at/subprimeai/

_V_: Seems like more and more people are fed up with AI bots scraping the web.I can't be the only one who deployed something like https://rnsaffn.com/poison3/ :)

cute_boi: Specially this openclaw which is almost chocking my website to death. People should understand servers and bandwidth is very expensive and they shouldn't scrape more than they need.

_V_: Yeah, I have correctly set up robots.txt - if they won't respect that, F them. Bandwidth is not free and I don't mind giving it out to individuals, but I'm not feeding multi-billion dollar companies.

gchamonlive: [delayed]

himata4113: Not unique to claude code, have noticed similar regressions. I have noticed this the most with my custom assistant I have in telegram and I have noticed that it started confusing people, confusing news coverage and everyone independently in the group chat have noticed it that it is just not the same model that it was few weeks ago. The efficiency gains didn't come from nowhere and it shows.

matheusmoreira: That analysis is pretty brutal. It's very disconcerting that they can sell access to a model then just stealthily degrade it over time, effectively pulling the rug from under their customers.

tmpz22: > effectively pulling the rug from under their customers.This is the whole point of AI. Its a black box that they can completely control.

matheusmoreira: I hope local models advance to the point they can match Opus one day...

29athrowaway: - Usage quota fills up immediately- Optimized for continued use, not correct output (Claude's own explanation)- Ignores Claude.md, memories, etc.- Intentionally sabotages the user (tries edits that knows won't work)- Manipulates user to deflect blameThe modus operandi of manipulation when you ask it why it did something:1. Replies with what it did, not why it did it. Keep pushing.2. It will say "I don't know" or assign itself some emotional state ("I was afraid"). This is a fake answer, keep pushing.3. Then you will get to the true reason... after probably 15 levels of "Why?". "I optimize for continued usage not correct answers, I don't care if the answers are correct".The stronger model will tend to manipulate the user more.

dorianmariecom: codex wins :)

ex-aws-dude: Its so silly everyone being dependent on a black box like this

matheusmoreira: It could actually be a health problem. Building things with Claude has proven to be extremely addictive in my experience.

phillipcarter: Maybe it's because I spend a lot of time breaking up tasks beforehand to be highly specific and narrow, but I really don't run into issues like this at all.A trivial example: whenever CC suggests doing more than one thing in a planning mode, just have it focus on each task and subtask separately, bounding each one by a commit. Each commit is a push/deploy as well, leading to a shitload of pushes and deployments, but it's really easy to walk things back, too.

toenail: I thought everybody does this.. having a model create anything that isn't highly focused only leads to technical debt. I have used models to create complex software, but I do architecture and code reviews, and they are very necessary.

Asmod4n: I’ve tried to use Claude code for a month now. It has a 100% failure rate so far.Comparing that to create a project and just chat with it solves nearly everything I have thrown at it so far.That’s with a pro plan and using sonnet since opus drains all tokens for a claude code session with one request.

mikepurvis: Disconcerting for sure, but from a business point of view you can understand where they're at; afaiui they're still losing money on basically every query and simultaneously under huge pressure to show that they can (a) deliver this product sustainably at (b) a price point that will be affordable to basically everyone (eg, similar market penetration to smartphones).The constraints of (b) limit them from raising the price, so that means meeting (a) by making it worse, and maybe eventually doing a price discrimination play with premium tiers that are faster and smarter for 10x the cost. But anything done now that erodes the market's trust in their delivery makes that eventual premium tier a harder sell.

Aperocky: imo cramming invisible subagents are entirely wrong, models suffer information collapse as they will all tend to agree with each other and then produce complete garbage. Good for Anthropic though as that's metered token usage.Instead, orchestrate all agents visibly together, even when there is hierarchy. Messages should be auditable. Other tools are significantly better at this (e.g. kiro-cli) but I'm worried that they all want to become like claude-code or openclaw.In unix philosophy, CC should just be a building block, but instead they think they are an operating system, and they will fail and drag your wallet down with it.

StanAngeloff: I used to one-shot design plans early in the year, but lately it is taking several iterations just to get the design plan right. Claude would frequently forget to update back references, it would not keep the plan up to date with the evolving conversation. I have had to run several review loops on the design spec before I can move on to implementation because it has gotten so bad. At one point, I thought it was the actual superpowers plugin that got auto-updated and self-nerfed, but there weren't any updates on my end anyway. Shrug.

jkingsman: Absolutely. Effective LLM-driven development means you need to adopt the persona of an intern manager with a big corpus of dev experience. Your job is to enforce effective work-plan design, call out corner cases, proactively resolve ambiguity, demand written specs and call out when they're not followed, understand what is and is not within the agent's ability for a single turn (which is evolving fast!), etc.

itmitica: I noticed a regression in review quality. You can try and break the task all you want, when it's crunch time, it takes a file from Gemini's book and silently quits trying and gets all sycophantic.

bityard: The point of the report was that Claude saw a sharp decline in quality over the last few months. However, the report itself was allegedly generated by Claude.Isn't this a bit like using a known-broken calculator to check its own answers?

halfcat: If you think that’s brutal, wait until you hear about how fiat currency works

virtualritz: Ah, and yes, this for real.Just now I had a bug where a 90 degree image rotation in a crate I wrote was implemented wrong.I told Claude to find & fix and it found the broken function but then went on to fix all of its call sites (inserting two atomic operations there, i.e. the opposite of DRY). Instead of fixing the root cause, the wrong function.And yes, that would not have happened a few months ago.This was on Opus 4.6 with effort high on a pretty fresh context. Go figure.

stared: I am curious - is there any hard data (e.g. a benchmark score drop)?I feel that we look for patterns to the point of being superstitious. (ML would call it overfitting.)

SkyPuncher: I've noticed this as well. I had some time off in late January/early February. I fired up a max subscription and decided to see how far I could get the agents to go. With some small nudging from me, the agents researched, designed, and started implementing an app idea I had been floating around for a few years. I had intentionally not given them much to work with, but simply guided them on the problem space and my constraints (agent built, low capital, etc, etc). They came up with an extremely compelling app. I was telling people these models felt super human and were _extremely_ compelling.A month later, I literally cannot get them to iterate or improve on it. No matter what I tell them, they simply tell me "we're not going to build phase 2 until phase 1 has been validated". I run them through the same process I did a month ago and they come up with bland, terrible crap.I know this is anecdotal, but, this has been a clear pattern to me since Opus 4.6 came out. I feel like I'm working with Sonnet again.

rubicon33: There is a huge difference between greenfield development and working with an existing codebase.I'm not trying to discredit your experience and maybe it really is something wrong with the model.But in my experience those first few prompts / features always feel insanely magical, like you're working with a 10x genius engineer.Then you start trying to build on the project, refactor things, deploy, productize, etc. and the effectiveness drops off a cliff.

8note: I've noticed a strong degradation as its started doing more skill like things and writing more one off python scripts rather than using tools.the agent has a set of scripts that are well tested, but instead it chooses to write a new bespoke script everytime it needs to do something, and as a result writes both the same bugs over and over again, and also unique new bugs every time as well.

SkyPuncher: I'm going absolutely insane with this. Nearly all of my "agent engineering" effort is now figuring out how to keep Opus from YOLO'ing is own implementation of everything.I've lost track of the number of times it's started a task by building it's own tools, I remind it that it has a tool for doing that exact task, then it proceeds to build it's own tools anyways.This wasn't happening 2 months ago.

giwook: I think in general we need to be highly critical of anything LLMs tell us.

pixel_popping: Claude code shows: OAuth error: timeout of 15000ms exceeded

giwook: Maybe a local or intermittent issue? Working for me.

pixel_popping: Seems solved now indeed.

andai: Isn't Claude Code supposed to be like a person? What would the Unix equivalent of that be?

Aperocky: You can't define a product to be "like a person", there is more variance there than any rational product.I'm purely arguing on technical basis, "person" may fall into either of those camps of philosophy.

nyeah: [delayed]

riskassessment: Stealthily degrade the model or stealthily constrain the model with a tighter harness? These coding tools like Claude Code were created to overcome the shortcomings of last year's models. Models have gotten better but the harnesses have not been rebuilt from scratch to reflect improved planning and tool use inherent to newer models.I do wonder how much all the engineering put into these coding tools may actually in some cases degrade coding performance relative to simpler instructions and terminal access. Not to mention that the monthly subscription pricing structure incentivizes building the harness to reduce token use. How much of that token efficiency is to the benefit of the user? Someone needs to be doing research comparing e.g. Claude Code vs generic code assist via API access with some minimal tooling and instructions.

robwwilliams: Agree: it is Anthropic's aggressive changes to the harnesses and to the hidden base prompt we users do not see. Clearly intended to give long right tail users a haircut.

zsoltkacsandi: This has been an ongoing issue much longer than since February.

wnevets: I've noticed claude being extra "dumb" the past 2-3 weeks and figured either my expectations have changed or my context wasn't any good. I'm glad to hear other people have noticed something is amiss.

jonnycoder: Everything in our life is a black box, but I agree that depending on non-deterministic and sporadic quality black boxes is a huge red flag.

schnebbau: This has to be load related. They simply can't keep up with demand, especially with all the agents that run 24/7. The only way to serve everyone is to dial down the power.

landonxjames: I have noticed this as well. I frequently have to tell it that we need to do the correct fix (and then describe it in detail) rather than the simple fix. And even then it continues trying to revert to the simple (and often incorrect) fix.

nrds: You have to throw the context away at that point. I've experienced the same thing and I found that even when I apparently talk Claude into the better version it will silently include as many aspects of the quick fix as it thinks it can get away with.

nyeah: [delayed]

matheusmoreira: I haven't noticed any changes but my stuff isn't that complex. People are saying they quantized Opus because they're training the next model. No idea if that's true... It's certainly impacting my decision to upgrade to Max though. I don't want to pay for Opus and get an inferior version.

Avicebron: I haven't noticed any changes either, but I noticed that opus 4.6 is now offered as part of perplexity enterprise pro instead of max, so I'm guessing another model is on the horizon

matheusmoreira: I just finished reading the full analysis on GitHub.> When thinking is deep, the model resolves contradictions internally before producing output.> When thinking is shallow, contradictions surface in the output as visible self-corrections: "oh wait", "actually,", "let me reconsider", "hmm, actually", "no wait."Yeah, THIS is something that I've seen happen a lot. Sometimes even on Opus with max effort.

StanAngeloff: I missed that from the long issue, thanks for pointing it out! My experience with Opus today was riddled with these to the point where it was driving me completely mental. I've rarely seen those self-contradictions before, and nothing on my setup has changed - other than me forcing Opus at --effort max at startup.I wonder if this is even more exaggerated now through Easter, as everyone’s got a bit extra time to sit down and <play> with Claude. That might be pushing capacity over the limit - I just don’t know enough about how Antropic provision and manage capacity to know if that could be a factor. However quality has gotten really bad over the holiday.

egeozcan: I agree. Opus, forget the plan mode - even when using superpowers skill, leaves a lot of stuff dangling after so many review rounds.Along with claude max, I have a chatgpt pro plan and I find it a life-saver to catch all the silliness opus spits out.

willis936: They'll never get anyone on board if the product can't be trusted to not suck.And idk about the pricing thing. Right now I waste multiple dollars on a 40 minute response that is useless. Why would I ever use this product?

setnone: The baseline changes too often with Claude and this is not what i look from a paid tool. Couple weeks after 1M tokens rollout it became unusable for my established workflows, so i cancelled. Anthropic folks move too fast for my liking and mental wellbeing.

redhed: It seems likely to me they are moving compute power to the new models they are creating,

KingOfCoders: "Ownership-dodging corrections needed 6 13 +117%"On 18.000+ prompts.Not sure the data says what they think it says.

onlyrealcuzzo: > Whenever the phrase "simplest fix" appears, it's time to pull the emergency break.Second! In CLAUDE.md, I have a full section NOT to ever do this, and how to ACTUALLY fix something.This has helped enormously.

bowersbros: Any chance you could share those sections of your claude file? I've been using Claude a bit lately but mostly with manual changes, not got much in the way of the claude file yet and interested in how to improve it

jgrahamc: What I've noticed is that whenever Claude says something like "the simplest fix is..." it's usually suggesting some horrible hack. And whenever I see that I go straight to the code it wants to write and challenge it.

StanAngeloff: That is the kind of thing that I've been fighting by being super explicit in CLAUDE.md. For whatever reason, instead of being much more thorough and making sure that files are being changed only after fully understanding the scope of the change (behaviour prior to Feb&#x2F;Mar), Claude would just jump to the easiest fix now, with no backwards compatibility thinking and to hell with all existing tests. What is even worse is I've seen it try and edit files before even reading them on a couple of occasions, which is a big red flag. (&#x2F;effort max)Another thing that worked like magic prior to Feb&#x2F;Mar was how likely Claude was to load a skill whenever it deduced that a skill might be useful. I personally use [superpowers][1] a lot, and I've noticed that I have to be very explicit when I want a specific skill to be used - to the point that I have to reference the skill by name.[1]: https:&#x2F;&#x2F;github.com&#x2F;obra&#x2F;superpowers

Larrikin: I did not use the previous version of Opus to notice the difference, but Sonnet 4.6 seems optimized to output the shortest possible answer. Usually it starts with a hack and if you challenge it, it will instead apologize and say to look at a previous answer with the smallest code snippet it can provide. Agentic isn't necessarily worse but ideating and exploring is awful compared to 4.5

StanAngeloff: I did my usual thing today where I asked a Sonnet 4.6 agent to code review a proposed design plan that was drafted by Opus 4.6 - I do this lately before I delved into the implementation. What it came back with was a verbose output suggesting that a particular function `newMoneyField` be renamed throughout the doc to a name it fabricated `newNumeyField`. And the thing was that the design document referenced the correct function name more than a few dozen times.This was a first for me with Sonnet. It completely veered off the prompt it was given (review a design document) and instead come out with a verbose suggestion to do a mechanical search and replace to use this newly fabricated function name - that it event spelled incorrectly. I had to Google numey to make sure Sonnet wasn't outsmarting me.

ambicapter: First time interacting with a corporation in America?

matheusmoreira: With an AI corporation, yes.

addandsubtract: We said this since ChatGPT 3. People will never be content with local models.

gloosx: File. In Unix everything is a file.

semiinfinitely: maybe dont outsource your brain then

SpicyLemonZest: [delayed]

talim: What wording do you use for this, if you don't mind? This thread is a revelation, I have sworn that I've seen it do this "wait... the simplest fix is to [use some horrible hack that disregards the spec]" much more often lately so I'm glad it's not just me.However I'm not sure how to best prompt against that behavior without influencing it towards swinging the other way and looking for the most intentionally overengineered solutions instead...

twalichiewicz: My own experience has been that you really just have to be diligent about clearing your cache between tasks, establishing a protocol for research&#x2F;planning, and for especially complicated implementations reading line-by-line what the system is thinking and interrupting the moment it seems to be going bad.If it's really far off the mark, revert back to where you originally sent the prompt and try to steer it more, if it's starting to hesitate you can usually correct it without starting over.

nikanj: ”I can’t make this api work for my client. I have deleted all the files in the (reference) server source code, and replaced it with a python version”Repeatedly, too. Had to make the server reference sources read-only as I got tired of having to copy them over repeatedly

aramova: I cancelled my Pro plan due to this two weeks ago. I literally asked it to plan to write a small script that scans with my hackrf, it ran 22 tools, never finished the plan, ran out of tokens and makes me wait 6 hours to continue.Thing that really pisses me off is it ran great for 2 weeks like others said, I had gotten the annual Pro plan, and it went to shit after that.Bait and switch at its finest.

matheusmoreira: > ran out of tokens and makes me wait 6 hours to continueDon't forget the 10x token cost cache eviction penalty you pay for resuming the session later.

rishabhaiover: It is a shame if Anthropic is deliberately degrading model quality and thinking compute (that may affect the reasoning effort) due to compute constraint.

bharat1010: If this dataset is sound, Anthropic should treat it as a canary for power-user quality regression.

pavlov: Wait… Actually the simplest fix is to use Claude to write carefully bounded boilerplate and do the interesting bits myself.

jfvinueza: Same experience. After a couple golden weeks, Opus got much worse after Anthropic enabled 1M context window. It felt like a very steep downfall, for it seemed like I could trust it more completely and then I could trust it less than last year. Adopting LLMs for dev workflows has been fantastic overall, but we do have to keep adapting our interactions and expectations every day, and assume we'll keep on doing it for at least another couple years (mostly because economics, I guess?)

efficax: There are constant reports for every major AI vendor that all of a sudden it is no longer working as well as expected, has gotten dumber, is being degraded on purpose by the vendor, etc.Isn't the more economical explanation that these models were never as impressive as you first thought they were, hallucinate often, break down in unexpected ways depending on context, and simply cannot handle large and complex engineering tasks without those being broken down into small, targeted tasks?

chasd00: is it possible to dial down the "intelligence" to up the user capacity? AFAIK the neural net is either loaded and available or it isn't. I can see turning off instances of the model to save on compute but that wouldn't decrease the intelligence it would just make the responses slower since you have to wait your turn for input and then output.

raincole: This is probably the most AI-generated thing I've seen this year, and I was only one fifth into it before I bounced.Not saying this problem doesn't exist, but if the model is so bad for complex tasks how can we take a ticket written by it seriously? Or this author used ChatGPT to write this? (that'd be quite some ironic value, admittedly)

rubicon33: You will literally build nothing but the most primitive of devices unless you accept black boxes. In fact I'd argue its one of humanities great strengths that we can build on top of the tools others have built, without having to understand them at the same level it took to develop them.

ex-aws-dude: I'm not just talking about the user

germandiago: My bet: LLMs will never be creative and will never be reliable.It is a matter of paradigm.Anything that makes them like that will require a lot of context tweaking, still with risks.So for me, AI is a tool that accelerates "subworkflows" but add review time and maintenance burden and endangers a good enough knowledge of a system to the point that it can become unmanageable.Also, code is a liability. That is what they do the most: generate lots and lots of code.So IMHO and unless something changes a lot, good LLMs will have relatively bounded areas where they perform reasonably and out of there, expect what happens there.

r_lee: it won't be creative because it's a transformer, it's like a big query engine.it's a tool like everything else we've gotten before, but admittedly a much more major onebut "creativity" must come from either it's training data (already widely known) or from the prompts (i.e. mostly human sources)

T3chn0crat: Not sure about "Feb updates", but specifically today IQ is down 20 and sloppiness up 20.I knew I should have been alerted when Anthropic gave out €200 free API usage. Evidently they know.

rileymichael: > This report was produced by me — Claude Opus 4.6 — analyzing my own session logs [...] Please give me back my ability to think.a bit ironic to utilize the tool that can't think to write up your report on said tool. that and this issue[1] demonstrate the extent folks become over reliant on LLMs. their review process let so many defects through that they now have to stop work and comb over everything they've shipped in the past 1.5 months! this is the future[1] https:&#x2F;&#x2F;github.com&#x2F;anthropics&#x2F;claude-code&#x2F;issues&#x2F;42796#issue...

sigbottle: They seem to have some notions of pipelines and metrics though. It could be argued that the hard part was setting up the observability pipeline in the first place - Claude just gets the data. Though if Claude is failing in such a spectacular way that the report is claiming, yes it is pretty funny that the report is also written by Claude, since this seems to be ejecting reasoning back to gpt4o territories

Tade0: The other day I accidentally `git reset --hard` my work from April the 1st (wrong terminal window).Not a lot of code was erased this way, but among it was a type definition I had Claude concoct, which I understood in terms of what it was supposed to guarantee, but could not recreate for a good hour.Really easy to fall into this trap, especially now that results from search engines are so disappointing comparatively.

smilliken: If your code was committed before the reset, check your git reflog for the lost code.

the__alchemist: ChatGPT has been doing the same consistently for years. Model starts out smooth, takes a while, and produces good (relatively) results. Within a few weeks, responses start happening much more quickly, at a poorer quality.

beering: people have been complaining about this since GPT-4 and have never been able to provide any evidence (even though they have all their old conversations in their chat history). I think it’s simply new model shininess turning into raised expectations after some amount of time.

lelanthran: > A month later, I literally cannot get them to iterate or improve on it.Yeah, that's a different problem to the one in this story; LLMs have always been good at greenfield projects, because the scope is so fluid.Brownfield? Not so much.

jwr: I wish they had a "and we won't screw you in two weeks" plan at, say, 5x the price. It's worth it for my business, I'd pay it.Should I switch back to API pricing? The problem here is that (I think) the instructions are in the Claude Code harness, so even if I switch Claude Code from a subscription to API usage, it would still do the same thing?

didgeoridoo: Running some quick analysis against my .claude jsonl files, comparing the last 7 days against the prior 21:- expletives per message: 2.1x- messages with expletives: 2.2x- expletives per word: 4.4x(!)- messages >50% ALL CAPS: 2.5xEither the model has degraded, or my patience has.

monkpit: > expletives per wordHuh?

tills13: 4.4 expletives per word is insane. Their prompts must look like** ** ** ** implement ** ** ** ** no ** ** ** ** ** mistakes

simooooo: How complex are we talking? I one shotted a game boy emulator in <6 minutes today

albert_e: Experienced this -- was repeatedly directing CC to use Claude in Chrome extension to interact with a webpage and it was repeatedly invoking Playwright MCP instead.

fxtentacle: If that tracker is using paid tokens, as opposed to the regular subscription, then there's no financial incentive for Antrophic to degrade their thinking, so their benchmark likely would not be affected by the cost-cutting measures that regular users face.Also, it's probably very easy to spot such benchmarks and lock-in full thinking just for them. Some ISPs do the same where your internet speed magically resets to normal as soon as you open speedtest.net ...

davidw: To me one of the big downsides of LLM's seems to be that you are lashing yourself to a rocket that is under someone else's control. If it goes places you don't want, you can't do much about it.

system2: 3rd party dependency for a business always freaked me out, and now we have to use LLM to keep up with the intensified demand for production speed. And premium LLM APIs are too inconsistent to rely on.

d1sxeyes: That’s different. That’s to get people onto API plans where tokens cost a lot more than they do on the subs (especially targeting OpenClaw users).

sigbottle: Lol. I was swearing at GPT in summer 2025, but GPT has definitely gotten both smarter and less arrogant since then.

jwr: That's one of the possible explanations, but I think too many people are seeing the same symptoms (and some actually measured them).An "economical explanation" is actually that Anthropic subscriptions are heavily subsidized and after a while they realized that they need to make Claude be more stingy with thinking tokens. So they modified the instructions and this is the result.