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An update on recent Claude Code quality reports

anthropic.com

471–480 of 778 posts

Re: An update on recent Claude Code quality reports

#471
post #456

Earlier quoted context omitted.

And still are gaslighting: We take reports about degradation very seriously. We never intentionally degrade our models [...] On March 4, we changed Claude Code's default reasoning effort from high to medium Anthropic is the best company of its kind, but that is badly worded PR.

To my eye, gaslighting is a serious accusation. Wikipedia's first line matches how I think of it: "Gaslighting is the manipulation of someone into questioning their perception of reality." Did I miss something? I'm only looking at primary sources to start. Not Reddit. Not The Register. Official company communications. Did Anthropic tell users i.e. "you are wrong, your experience is not worse."? If so, that would reac…

I'd rather not speak too poorly of Anthropic, because - to the extent I can bring myself to like a tech company - I like Anthropic.

That said, the copy uses "we never intentionally degrade our models" to mean something like "we never degrade one facet of our models unless it improves some other facet of our models". This is a cop out, because it is what users suspected and complained about. What users want - regardless of whether it is realistic to expect - is for Anthropic to buy even more compute than Anthropic already does, so that the models remain equally smart even if the service demand increases.

Re: An update on recent Claude Code quality reports

#472

Earlier quoted context omitted.

> I was never under the impression that gaps in conversations would increase costs nor reduce quality. Both are surprising and disappointing. You didn't do your due diligence on an expensive API. A naïve implementation of an LLM chat is going to have O(N^2) costs from prompting with the entire context every time. Caching is needed to bring that down to O(N), but the cache itself takes resources, so evictions have to…

How do you do "due diligence" on an API that frequently makes undocumented changes and only publishes acknowledgement of change after users complain? You're also talking about internal technical implementations of a chat bot. 99.99% of users won't even understand the words that are being used.

What is being discussed is KV caching [0], which is used across every LLM model to reduce inference compute from O(n^2) to O(n). This is not specific to Claude nor Anthropic.

[0]: https://huggingface.co/blog/not-lain/kv-caching

Re: An update on recent Claude Code quality reports

#473

"On March 26, we shipped a change to clear Claude's older thinking from sessions that had been idle for over an hour, to reduce latency when users resumed those sessions. A bug caused this to keep happening every turn for the rest of the session instead of just once, which made Claude seem forgetful and repetitive. We fixed it on April 10. This affected Sonnet 4.6 and Opus 4.6" This makes no sense to me. I often leav…

[deleted]

Re: An update on recent Claude Code quality reports

#474
post #77

They lost me at Opus 4.7 Anecdotally OpenAI is trying to get into our enterprise tooth and nail, and have offered unlimited tokens until summer. Gave GPT5.4 a try because of this and honestly I don’t know if we are getting some extra treatment, but running it at extra high effort the last 30 days I’ve barely see it make any mistakes. At some points even the reasoning traces brought a smile to my face as it preemptive…

extra high burns tokens i find. ( run 5.4 on medium for 90% of the tasks and high if i see medium struggling and its very focused and make minimum changes.

Not a problem if they're offering unlimited, lol

Re: An update on recent Claude Code quality reports

#475
post #261

Earlier quoted context omitted.

> I was never under the impression that gaps in conversations would increase costs nor reduce quality. Both are surprising and disappointing. You didn't do your due diligence on an expensive API. A naïve implementation of an LLM chat is going to have O(N^2) costs from prompting with the entire context every time. Caching is needed to bring that down to O(N), but the cache itself takes resources, so evictions have to…

How big this cached data is? Wouldn't it be possible to download it after idling a few minutes "to suspend the session", and upload and restore it when the user starts their next interaction?

> upload and restore it when the user starts their next interaction

The data is the conversation (along with the thinking tokens).

There is no download - you already have it.

The issue is that it gets expunged from the (very expensive, very limited) GPU cache and to reload the cache you have to reprocess the whole conversation.

That is doable, but as Boris notes it costs lots of tokens.

Re: An update on recent Claude Code quality reports

#476
Last I tried 4.7, it was bad. Like ChatGPT bad: changed stuff it wasn’t supposed to, hallucinated code, forgot information, missed simple things, didn’t catch mistakes. And it burned through tokens like crazy.

I’ll stay on 4.6 for awhile. Seems to be better. What’s frustrating, though you cannot rely on these tools. They are constantly tinkering and changing with things and there’s no option to opt out.

Re: An update on recent Claude Code quality reports

#478

Earlier quoted context omitted.

> I was never under the impression that gaps in conversations would increase costs nor reduce quality. Both are surprising and disappointing. You didn't do your due diligence on an expensive API. A naïve implementation of an LLM chat is going to have O(N^2) costs from prompting with the entire context every time. Caching is needed to bring that down to O(N), but the cache itself takes resources, so evictions have to…

How do you do "due diligence" on an API that frequently makes undocumented changes and only publishes acknowledgement of change after users complain? You're also talking about internal technical implementations of a chat bot. 99.99% of users won't even understand the words that are being used.

> How do you do "due diligence" on an API that frequently makes undocumented changes and only publishes acknowledgement of change after users complain?

1. Compute scaling with the length of the sequence is applicable to transformer models in general, i.e. every frontier LLM since ChatGPT's initial release.

2. As undocumented changes happen frequently, users should be even more incentivized to at least try to have a basic understanding of the product's cost structure.

> You're also talking about internal technical implementations of a chat bot. 99.99% of users won't even understand the words that are being used.

I think "internal technical implementation" is a stretch. Users don't need to know what a "transformer" is to understand the trade-off. It's not trivial but it's not something incomprehensible to laypersons.

Re: An update on recent Claude Code quality reports

#479
post #461
post #382

Earlier quoted context omitted.

That doesn’t make sense to pay more for cache warming. Your session for the most part is already persisted. Why would it be reasonable to pay again to continue where you left off at any time in the future?

Genuine question: is the cost to keep a persistent warmed cache for sessions idling for hours/days not significant when done for hundreds of thousands of users? Wouldn’t it pose a resource constraint on Anthropic at some point?

[dead]

Re: An update on recent Claude Code quality reports

#480

"On March 26, we shipped a change to clear Claude's older thinking from sessions that had been idle for over an hour, to reduce latency when users resumed those sessions. A bug caused this to keep happening every turn for the rest of the session instead of just once, which made Claude seem forgetful and repetitive. We fixed it on April 10. This affected Sonnet 4.6 and Opus 4.6" This makes no sense to me. I often leav…

Wow, I always thought the context is always stored locally and this is something I have control over.

Glad I use kiro-cli which doesn't do this.

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