alt Hacker NewsI Cancelled Claude: Token Issues, Declining Quality, and Poor Support
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I feel like I'm using Claude Opus pretty effectively and I'm honestly not running up against limits in my mid-tier subscriptions. My workflow is more "copilot" than "autopilot", in that I craft prompts for contained tasks and review nearly everything, so it's pretty light compared to people doing vibe coding.
The market-leading technology is pretty close to "good enough" for how I'm using it. I look forward to the day when LLM-assisted coding is commoditized. I could really go for an open source model based on properly licensed code.
This is what worries me. People become dependent on these GenAI products that are proprietary, not transparant, and need a subscription. People build on it like it is a solid foundation. But all of a sudden the owner just pulls the foundation from under your building.
Claude with Sonnet medium effort just used 100% of my session limit, some extra dollars, thought for 53 minutes, and said:
API Error: Claude's response exceeded the 32000 output token maximum. To configure this behavior, set the CLAUDE_CODE_MAX_OUTPUT_TOKENS environment variable.
Me and so many coworkers have been struggling with a big cognitive decline in Claude over the last two months. 4.5 was useful and 4.6 was great. I had my own little benchmark and 4.5 could just about keep track of a two way pointer merge loop whereas 4.6 managed a 3 way and the 1M context managed k-way. And this ability to track braids directly helped it understand real production code and make changes and be useful etc.
but then two months ago 4.6 started getting forgetful and making very dumb decisions and so on. Everyone started comparing notes and realising it wasn’t “just them”. And 4.7 isn’t much better and the last few weeks we keep having to battle the auto level of effort downgrade and so on. So much friction as you think “that was dumb” and have to go check the settings again and see there has been some silent downgrade.
We all miss the early days of 4.6, which just show you can have a good useful model. LLMs can be really powerful but in delivering it to the mass market Anthropic throttle and downgrade it to not useful.
My thinking is that soon deepseek reaches the more-than-good-enough 4.6+ level and everyone can get off the Claude pay-more-for-less trajectory. We don’t need much more than we’ve already had a glimpse of and now know is possible. We just need it in our control and provisioned not metered so we can depend upon it.
That's bad for him, because he already had a cheap plan. Now he wont get it back that easy.
Pro is gone. OpenAI plans are more expensive. He can only buy a Kimi plan, which is at least better than Sonnet. But frontier for cheap is gone. Even copilot business plans are getting very expensive soon, also switching to API usage only.
After the fixes in Claude Code, Opus 4.6/4.7 have been performing well.
Before the fixes, they were complete trash and I was ready to cancel this month.
Now, I'm feeling like the AI wars are back -- GPT 5.5 and Opus 4.7 are both really good. I'm no longer feeling like we're using nerfed models (knock on wood)!
My max20 sub is sitting unused since april mostly now, codex with 5.4 (and now 5.5) even with fast mode (= double token costs) is night and day. Opus is doing convincing failures and either forgets half the important details or decides to do "pragmatic" (read: technical debt bandaids or worse) silently and claims success even with everything crashing and burning after the changes. and point out the errors it will make even more messes. Opus works really well for oneshotting greenfield scopes, but iterating on it later or doing complex integrations its just unusable and even harmfully bad.
GPT 5.4+ takes its time and considers even edgecases unprovoked that in fact are correct and saves me subsequent error hunting turns and finally delivers. Plus no "this doesn't look like malware" or "actually wait" thinking loops for minutes over a oneliner script change.
AI services are only minorly incentivized to reduce token usage. They want high token usage, it makes you pay more. They are going to continually test where the limit is, what is the max token usage before you get angry. All AI companies will continue to trade places for token use and cost as cost increases. We are in tepid water pretending it is a bath pretending we aren’t about to be boiled frogs.
Yesterday was a realization point for me. I gave a simple extraction task to Claude code with a local LLM and it "whirred" and "purred" for 10 minutes. Then I submitted the same data and prompt directly to model via llama_cpp chat UI and the model single-shotted it in under a minute. So obviously something wrong with coding agent or the way it is talking to LLM.
Now I'm looking for an extremely simple open-source coding agent. Nanocoder doesn't seem install on my Mac and it brings node-modules bloat, so no. Opencode seems not quite open-source. For now, I'm doing the work of coding agent and using llama_cpp web UI. Chugging it along fine.
I’ve definitely encountered a drop in Claude quality.
Even a simple prompt focused on two files I told Claude to do a thing to file A and not change file B (we were using it as a reference).
Claude’s plan was to not touch file B.
First thing it did was alter file B. Astonishing simple task and total failure.
It was all of one prompt, simple task, it failed outright.
I also had it declare that some function did not have a default value and then explain what the fun does and how it defaults to a specific value….
Fundamentally absurd failures that have seriously impacted my level of trust with Claude.
I think there’s a clear split amongst GenAI developers.
One group is consistently trying to play whack-a-mole with different models/tools and prompt engineering and has shown a sine-wave of success.
The other group, seemingly made up of architects and Domain-Driven Design adherents has had a straight-line of high productivity and generating clean code, regardless of model and tooling.
I have consistently advised all GenAI developers to align with that second group, but it’s clear many developers insist on the whack-a-mole mentality.
I have even wrapped my advice in https://devarch.ai/ which has codified how I extract a high level of quality code and an ability to manage a complex application.
Anthropic has done some goofy things recently, but they cleaned it up because we all reported issues immediately. I think it’s in their best interests to keep developers happy.
My two cents.
I've noticed that sometimes the same Claude model will make logical errors sometimes but not other times. Claude's performance is highly temporal. There's even a graph! https://marginlab.ai/trackers/claude-code/
I haven't seen anyone mention this publicly, but I've noticed that the same model will give wildly different results depending on the quantization. 4-bit is not the same as 8-bit and so on in compute requirements and output quality. https://newsletter.maartengrootendorst.com/p/a-visual-guide-...
I'm aware that frontier models don't work in the same way, but I've often wondered if there's a fidelity dial somewhere that's being used to change the amount of memory / resources each model takes during peak hours v. off hours. Does anyone know if that's the case?
I have a simple rule: I won't pay for that stuff. First they steal all my work to feed into those models, afterwards I shall pay for it? No way!
I use AI, but only what is free-of-charge, and if that doesn't cut it, I just do it like in the good old times, by using my own brain.
I've been a fan since the launch of the first Sonnet model and big props for standing up to the government, but you can sure lose that good faith fast when you piss off your paying customers with bad communication, shaky model quality and lowered usage limits.
I feel like Opus 4.5 was the peak in Claude Code usefulness. It was smart, it was interactive, it was precise. In 4.6 and 4.7, it spends a long time thinking and I don't know what's happening, often hits a dead-end and just continues. For a while I was setting Opus 4.5 in Claude Code, but it got reset often. I just canceled my Max plan, don't know where to look for alternatives.
My experience is Claude and others are good at writing methods and smaller because you can dictate what it should do in less tokens and easily read the code. This closes the feadback loop for me.
I occasionally ask AI to write lots of code such as a whole feature (>= medium shirt size) or sometimes even bigger components of said feature and I often just revert what it generated. It's not good for all the reasons mentioned.
Other times I accept its output as a rough draft and then tell it how to refactor its code from mid to senior level.
I'm sure it will get better but this is my trust level with it. It saves me time within these confines.
Edit: it is a valuable code reviewer for me, especially as a solo stealth startup.
Shameless self plug but also worried about the silent quality regressions, I started building a tool to track coding agent performance over time.. https://github.com/s1liconcow/repogauge
Here is a sample report that tries out the cheaper models + the newest Kimi2.6 model against the 5.4 'gold' testcases from the repo: https://repogauge.org/sample_report.
The timeline doesn't make any sense. How can you subscribe a couple weeks ago and the problem start 3 weeks ago and yet things also went well for the first few weeks. was this written by GPT 5.5?
for all the drama, its pretty clear both openai, google, and anthropic have had to degrade some of their products because of a lack of supply.
There's really no immediate solution to this other than letting the price float or limiting users as capacity is built out this gets better.
I'm on max x5. No limit problems, but I am definetly feeling the decline. Early stopping and being hellbent on taking shortcuts being the main culprits, closely followed by over optimistic (stale) caching (audit your hooks!).
All mostly mitigatable by rigorous audits and steering, but man, it should not have to be.
Looking at Anthropic's new products I think they understand they don't really have a cutting edge other than the brand.
I tried Kimi 2.6 and it's almost comparable to Opus. Anthropic lost the ball. I hope this is a sign the we are moving towards a future where model usage is a commodity with heavy competition on price/performance
The discussion about Claude always omit the important context - which language/platform you’re using it for. It is best trained for web languages and has most up to date knowledge for that. If you use it for Swift it is trained on whole landfill of code and that gives you strong bias towards pre-Swift 6 coding output. Imagine you would give Claude a requirements for a web app, and it implements it all in JQuery. That’s what happens with other platforms.
They can't afford to care about individual customers because enterprise demand exploded and they're short on compute
Doesn't "poor support" implies that there is some sort of support? Shouldnt it be "no support"
I also cancelled my subscription.The $20 Pro plan has become completely unusable for any real work. What is especially frustrating is that Claude Chat and Claude Code now share the exact same usage limits — it makes zero sense from a product standpoint when the workflows are so different. Even the $200 Max plan got heavily nerfed. What used to easily last me a full week (or more) of solid daily use now burns out in just a few days. Combined with the quality drop and unpredictable token consumption, it simply stopped being worth it.
Biggest issue i see is, models are not getting efficient. This is no where going to get commoditised. There will be a limit at which you can burn money at subsidised cost.
Funny. I thought I was the only one. Then I found more people and now you wrote about that. Just this week I also wrote about Claude Opus 4.7 and how I came back to Codex after that: https://thoughts.jock.pl/p/opus-4-7-codex-comeback-2026
Same, after being a long-time proponent too.
First was the CC adaptive thinking change, then 4.7. Even with `/effort max` and keeping under 20% of 1M context, the quality degradation is obvious.
I don't understand their strategy here.
My recent frustration with Claude has been it feels like I'm waiting on responses more. I don't have historical latency to compare this with, but I feel like it has been getting slower. I may be wrong, and maybe its just spending more time thinking than it used to. My guess is Anthropic is having capacity issues. I hope I'm wrong because I don't want to switch.
I’ve noticed most of the complaints are about the Pro plan. Anecdotally I pay for the $200 Max plan and haven’t noticed anything radically different re: tokens or thinking time (availability is still a crapshoot)
I am certainly not saying people should “spend more money,” more like the Claude Code access in the Pro plan seems kind of like false advertising. Since it’s technically usable, but not really.
The timeline of the first few sentences doesn't add up. how can you subscribe 2 weeks ago when the problem started 3 weeks ago.
I can agree. ChatGPT 5.5 made this a no-brainer choice. Anthropic are idiots removing Claude Code from the Pro plan. They need to ask Claude if what they did was a natural intelligence bug! Greed kills companies, too!
I feel like almost everyone using AI for support systems is utterly failing at the same incredibly obvious place.
The first job of any support system—both in terms of importance and chronologically—is triage. This is not a research issue and it's not an interaction issue. It's at root a classification problem and should be trained and implemented as such.
There are three broad categories of interaction: cranks, grandmas, and wtfs.
Cranks are the people opening a support chat to tell you they have vital missing information about the Kennedy Assassintion or they want your help suing the government for their exposure to Agent Orange when they were stationed at Minot. "Unfortunately I can't help with that. We are a website that sells wholesale frozen lemonade. Good luck!"
Grandma questions are the people who can't navigate your website. (This isn't meant to be derogatory, just vivid; I have grandma questions often enough myself.) They need to be pointed toward some resource: a help page, a kb article, a settings page, whatever. These are good tasks for a human or LLM agent with a script or guideline and excellent knowledge/training on the support knowledge base.
WTFs are everything else. Every weird undocumented behavior, every emergent circumstance, every invalid state, etc. These are your best customers and they should be escalated to a real human, preferably a smart one, as soon as realistically possible. They're your best customers because (a) they are investing time into fixing something that actually went wrong; (b) they will walk you through it in greater detail than a bug report, live, and help you figure it out; and (c) they are invested, which means you have an opportunity for real loyalty and word-of-mouth gains.
What most AI systems (whether LLMs or scripts) do wrong is that they treat WTFs like they're grandmas. They're spending significant money on building these systems just to destroy the value they get from the most intelligent and passionate people in their customer base doing in-depth production QC/QA.
I've been very happy using Codex in the VScode extension. Very high quality coding and generous token limits. I've been running Claude in the CLI over the last couple of months to compare and overall I prefer Codex, but would be happy with either.
Same. I think one of the issues is that Claude reached a treshold where I could just rely on it being good and having to manually fix it up less and less and other models hadn't reached that point yet so I was aware of that and knew I had to fix things up or do a second pass or more. Other providers also move you to a worse model after you run out which is key in setting expectation as well. Developers knew that that was the trade-off.
I think even with the worse limits people still hated it but when you start to either on purpose or inadvertently make the model dumber that's when there's really no purpose to keep using Claude anymore.
anyone remember the whole “delete uber” thing from 2017ish? good times
It's bad, really bad.
The filesystem tool cannot edit xml files with <name></name> elements in it
I feel like Anthropic is forcing their new model (Opus 4.7) to do much less guess work when making architectural choices, instead it prefers to defer back decisions to the user. This is likely done to mine sessions for Reinforcement-Learning signals which is then used to make their future models even smarter.
I've see a post like this every week for the last 2 years. Are these models actually getting worse? Or do folks start noticing the cracks as they use them more and more?
They won't even reset usage for me: https://news.ycombinator.com/item?id=47892445
And by crikey do I empathise with the poor support in this article. Nothing has soured me on Anthropic more than their attitude.
Great AI engineers. Questionable command line engineers (but highly successful.) Downright awful to their customers.
Wait, weren't there posts in the not too distant past where everyone was signing the praises for Claude and wondering how OpenAI will catch up?
Oh no, the unreliable product people pretend is the next coming of Jesus turned out to be thoroughly unreliable. Who coulda thunk it.
If someone wants to move off Claude what are the alternatives? More importantly can another system pick up from where Claude left off or is there some internal knowledge Claude keeps in their configuration that I need to extract before canceling?
I have to say, this has been the opposite of my experience. If anything, I have moved over more work from ChatGPT to Claude.
Switched to local models after quality dropped off a cliff and token consumption seemed to double. Having some success with Qwen+Crush and have been more productive.
I'm torn because I use it in my spare time, so I've missed some of these issues, I don't use it 9 to 5, but I've built some amazing things, when 1 Million tokens dropped, that was peak Claude Code for me, it was also when I suspect their issues started. I've built up some things I've been drafting in my head for ages but never had time for, and I can review the code and refine it until it looks good.
I'm debating trying out Codex, from some people I hear its "uncapped" from others I hear they reached limits in short spans of time.
There's also the really obnoxious "trust me bro" documentation update from OpenClaw where they claim Anthropic is allowing OpenClaw usage again, but no official statement?
Dear Anthropic:
I would love to build a custom harness that just uses my Claude Code subscription, I promise I wont leave it running 24/7, 365, can you please tell me how I can do this? I don't want to see some obscure tweet, make official blog posts or documentation pages to reflect policies.
Can I get whitelisted for "sane use" of my Claude Code subscription? I would love this. I am not dropping $2400 in credits for something I do for fun in my free time.
I use Claude Code with GLM, Kimi and MiniMax models. :)
I was worried about Anthropic models quality varying and about Anthropic jacking up prices.
I don't think Claude Code is the best agent orchestrator and harness in existence but it's most widely supported by plugins and skills.
I used Opus via Copilot until December and then largely switched over to Claude Code. I'm not sure what the difference is but I haven't seen any of these issues in daily use.
I write detailed specs. Multifile with example code. In markdown.
Then hand over to Claude Sonnet.
With hard requirements listed, I found out that the generated code missed requirements, had duplicate code or even unnecessary code wrangling data (mapping objects into new objects of narrower types when won't be needed) along with tests that fake and work around to pass.
So turns out that I'm not writing code but I'm reading lots of code.
The fact that I know first hand prior to Gen AI is that writing code is way easier. It is reading the code, understanding it and making a mental model that's way more labour intensive.
Therefore I need more time and effort with Gen AI than I needed before because I need to read a lot of code, understand it and ensure it adheres to what mental model I have.
Hence Gen AI at this price point which Anthropic offers is a net negative for me because I am not vibe coding, I'm building real software that real humans depend upon and my users deserve better attention and focus from me hence I'll be cancelling my subscription shortly.