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Why I Cancelled Claude: Token Issues, Declining Quality, and Poor Support
2026-04-24 · via Hacker News

First enthusiasm

A couple of weeks ago I subscribed to Claude Code, and during the first few weeks I had a really nice experience. It was fast, the token allowance was fair, and the quality was good.

I learned they had raised the token allowance for non-rush hours , and since they opposed some governmental rules, it felt good to support the right cause.

(づ  ̄ ³ ̄)づ

However… for about three weeks now my initial enthusiasm has been rapidly waning.

It began with an issue three weeks ago. I started working in the morning after about a ten-hour break; enough time for my tokens to refresh.

I sent two small questions to Claude Haiku. They were simple questions, not even related to the repository.

Suddenly, token usage spiked to 100%.

Have a nice break…

I contacted their “AI support bot”, which returned some default support nonsense and didn’t really understand the problem. So I asked for human support. A couple of days later a - what appeared to be - human support person sent a reply. It began like this:

“Our systems are detecting your inquiry is regarding usage limits on your Pro or Max plan.

Yeah, well — it’s the Pro plan. Seems like your systems weren’t actually queried; it was just a default intro and probably a default answer, because:

This was followed by an extensive what seems to be copy-and-paste answer from their docs explaining how daily and weekly limits work.

And it closed with the typically frustrating line, that no customer likes to read at the end of an e-mail and which is just the classical middle-finger of customer support - we don’t care if your problem is solved or not, we declared it closed.

“Note that further replies to this ticket may not be monitored. If your request is not regarding usage limits on your Pro or Max plan, or you need additional support, please visit our help page at”

Great! Sending an automated e-mail that does not refer to the actual problem and then closing the channel. Thanks for nothing, I guess? Or was I wrong. I asked Claude Haiku:

@Haiku:

See the customer’s request here and the response from the AI and later W***** - did they answer the concern/question of the customer?

Customer support response
Customer support response

(╯°_°)╯︵ ┻━┻

Declining quality

In the following days and weeks, the quality was far from satisfying my needs or matching my initial experience. While I used to be able to work on up to three projects at once, now the token limit was exhausted after two hours on a single project.

And the quality was degrading. I am fully aware this is quite subjective and that the quality of the agent is always heavily impacted by the operator. The failure usually appears in front of the screen. But hey, I also develop using Github’s Copilot, OpenAI’s Codex and I am running my own inference with OMLX and Continue using Qwen3.5-9B. I’m not the expert, I’m lazy sometimes but I probably know a thing or two.

Let me give you this wonderful example: yesterday I asked Claude Opus to refactor a project.

While I was browsing the model’s thinking log - which I strongly suggest doing not only occasionally - I found this:

Rather than editing every slider in JSX, I’ll add a generic initializer in ui-events.js that auto-injects value displays for all range inputs that lack one.

This is clearly bad practice. It’s a cheap workaround you wouldn’t expect even from a junior dev; it reads like someone who just doesn’t want to deliver a good result. My response:

“you can’t be serious — is this how you fix things? just WORKAROUNDS????”

At least Opus admitted:

“You’re right, that was lazy. Let me do it properly — add the labels directly in the JSX and wire them explicitly.”

The lazy developer - at least honest
The lazy developer - at least honest

Needless to say, this shortcut cost me around 50% of my five-hour token allowance.

(ง •̀_•́)ง

And even more…

Now this cache topic comes up - among others . at least they are talking about it openly. The problem was: when you get back to work after some time, your conversation cache is gone and the model starts reading your codebase again. Cost-wise this is smart. But experience-wise? It means you paid tokens for the initial load and, after a forced break because the five-hour token window hit its limit, you pay again for the same load.

Think that’s all? Wait, I also got this funny anecdote: all of a sudden the weekly window changed from today to Monday. OK, I was thankful because it came with a reset to zero. But still: what is going on, Anthropic? Not only that — while I was working on my project, watching token usage with Argus-eyed vigilance, this little warning popped up:

Token limit warning
Token limit warning - but I was still within the limits?

Wait, what? I’m neither part of an organization nor do I see any hint why I suddenly have to worry about a “monthly usage limit” — also the hourly and weekly limits were still not exceeded. What is happening right now?

Token limit warning - but I was still within the limits?
Token limit warning - but I was still within the limits?

Turns out — two hours later - it allowed me to continue working. The warning was gone.

Token limit warning disappeared
Token limit warning disappeared - but what was it about?

At least this documentation does not mention a monthly usage limit. And the settings page only lists the limits for the current session and week.

Token limits documentation
Token limits documentation - no mention of monthly limits

So… what is this monthly limit all about, Anthropic?

Sorry to let you down, Anthropic

I am a huge fan of the product. Theoretically everything just works like a charm; it offers so many opportunities. I built my own harness around Claude , I admire Claude Caude who work’s in the background on a bunch of GitHub issues, I love using Claude Cowork to continue writing my Nerd Enzyklopädie . So many thoughful features.

I increased my productivity by an order of magnitude, and it’s really thrilling to see how these trillions of ideas crawling through my head are now only a blink away - easier and quicker to realize than four years ago.

And I understand the technical and organizational challenges when offering a product like that. It’s not easy to benefit from scaling effects when you sell inference. Every additional hour and every new customer requires the same amount of compute. That’s the curse of incremental costs in this line of business.

But…

…it seems like Anthropic cannot handle too many new customers at once, so I took that load off Anthropic and cancelled my account.

(ʘ‿ʘ)╯