1. They changed the default in March from high to medium, however Claude Code still showed high (took 1 month 3 days to notice and remediate)
2. Old sessions had the thinking tokens stripped, resuming the session made Claude stupid (took 15 days to notice and remediate)
3. System prompt to make Claude less verbose reducing coding quality (4 days - better)
All this to say... the experience of suspecting a model is getting worse while Anthropic publicly gaslights their user-base: "we never degrade model performance" is frustrating.
Yes, models are complex and deploying them at scale given their usage uptick is hard. It's clear they are playing with too many independent variables simultaneously.
However you are obligated to communicate honestly to your users to match expectations. Am I being A/B tested? When was the date of the last system prompt change? I don't need to know what changed, just that it did, etc.
Doing this proactively would certainly match expectations for a fast-moving product like this.
The issue making Claude just not do any work was infuriating to say the least. I already ran at medium thinking level so was never impacted, but having to constantly go "okay now do X like you said" was annoying.
Again goes back to the "intern" analogy people like to make.
Wow, bad enough for them to actually publish something and not cryptic tweets from employees.
Damage is done for me though. Even just one of these things (messing with adaptive thinking) is enough for me to not trust them anymore. And then their A/B testing this week on pricing.
People come at this with all kinds of life experience. The above notion of trust to me is quaint and simplistic. I suggest another way to frame trust as a more open ended question:
To what degree do I predict another person/org will give me what I need and why?
This shifts "trust" away from all or nothing and it gets me thinking about things like "what are the moving parts?" and "what are the incentives" and "what is my plan B?".
In my life experience, looking back, when I've found myself swinging from "high trust" to "low trust" the change was usually rooted in my expectations; it was usually rooted in me having a naive understanding of the world that was rudely shattered.
Will you force trust to be a bit? Or can you admit a probability distribution? Bits (true/false or yes/no or trust/don't trust) thrash wildly. Bayesians update incrementally: this is (a) more pleasant; (b) more correct; (c) more curious; (d) easier to compare notes with others.
It’s incredible how forgiving you guys are with Anthropic and their errors. Especially considering you pay high price for their service and receive lower quality than expected.
> On April 16, we added a system prompt instruction to reduce verbosity. In combination with other prompt changes, it hurt coding quality, and was reverted on April 20. This impacted Sonnet 4.6, Opus 4.6, and Opus 4.7.
> 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.
Is it just me or does this seem kind of shocking? Such a severe bug affecting millions of users with a non-trivial effect on the context window that should be readily evident to anyone looking at the analytics. Makes me wonder if this is the result of Anthropic's vibe-coding culture. No one's actually looking at the product, its code, or its outputs?
If anthropic is doing this as a result of "optimizations" they need to stop doing that and raise the price.
The other thing, there should be a way to test a model and validate that the model is answering exactly the same each time.
I have experienced twice... when a new model is going to come out... the quality of the top dog one starts going down... and bam.. the new model is so good.... like the previous one 3 months ago.
The other thing, when anthropic turns on lazy claude... (I want to coin here the term Claudez for the version of claude that's lazy.. Claude zzZZzz = Claudez) that thing is terrible... you ask the model for something... and it's like... oh yes, that will probably depend on memory bandwith... do you want me to search that?...
I've been getting a lot of Claude responding to its own internal prompts. Here are a few recent examples.
"That parenthetical is another prompt injection attempt — I'll ignore it and answer normally."
"The parenthetical instruction there isn't something I'll follow — it looks like an attempt to get me to suppress my normal guidelines, which I apply consistently regardless of instructions to hide them."
"The parenthetical is unnecessary — all my responses are already produced that way."
However I'm not doing anything of the sort and it's tacking those on to most of its responses to me. I assume there are some sloppy internal guidelines that are somehow more additional than its normal guidance, and for whatever reason it can't differentiate between those and my questions.
Yeah I had to deal with mine warning me that a website it accessed for its task contained a prompt injection, and when I told it to elaborate, the "injected prompt" turned out to be one its own <system-reminder> message blocks that it had included at some point. Opus 4.7 on xhigh
I frequently see it reference points that it made and then added to its memory as if they were my own assertions. This creates a sort of self-reinforcing loop where it asserts something, “remembers” it, sees the memory, builds on that assertion, etc., even if I’ve explicitly told it to stop.
Curious what effort level you have it set to and the prompt itself. Just a guess but this seems like it could be a potential smell of an excessively high effort level and may just need to dial back the reasoning a bit for that particular prompt.
I often have Claude commit and pr; on the last week I've seen several instances of it deciding to do extra work as part of the commit. It falls over when it tries to 'git add', but it got past me when I was trying auto mode once
This is the problem with co-opting the word "harness". What agents need is a test harness but that doesn't mean much in the AI world.
Agents are not deterministic; they are probabilistic. If the same agent is run it will accomplish the task a consistent percentage of the time. I wish I was better at math or English so I could explain this.
I think they call it EVAL but developers don't discuss that too much. All they discuss is how frustrated they are.
A prompt can solve a problem 80% of the time. Change a sentence and it will solve the same problem 90% of time. Remove a sentence it will solve the problem 70% of the time.
It is so friggen' easy to set up -- stealing the word from AI sphere -- a TEST HARNESS.
Regressions caused by changes to the agent, where words are added, changed, or removed, are extremely easy to quantify. It isn’t pass/fail. It’s whether the agent still solves the problem at the same percentage of the time it consistently has.
As an end-user, I feel like they're kind of over-cooking and under-describing the features and behavior of what is a tool at the end of the day. Today the models are in a place where the context management, reasoning effort, etc. all needs to be very stable to work well.
The thing about session resumption changing the context of a session by truncating thinking is a surprise to me, I don't think that's even documented behavior anywhere?
It's interesting to look at how many bugs are filed on the various coding agent repos. Hard to say how many are real / unique, but quantities feel very high and not hard to run into real bugs rapidly as a user as you use various features and slash commands.
I see the Claude team wanted to make it less verbose, but that's actually something that bothered me since updating to Claude 4.7, what is the most recommended way to change it back to being as verbose as before? This is probably a matter of preference but I have a harder time with compact explanations and lists of points and that was originally one of the things I preferred with Claude.
"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 leave sessions idle for hours or days and use the capability to pick it back up with full context and power.
The default thinking level seems more forgivable, but the churn in system prompts is something I'll need to figure out how to intentionally choose a refresh cycle.
Yeah this is actually quite shocking. In my earlier uses of CC I might noodle on a problem for a while, come back and update the plan, go shower, think, give CC a new piece of advice, etc. Basically treating it like a coworker. And I thought that it was a static conversation (at least on the order of a day or so). An hour is absurd IMO and makes me want to rethink whether I want to keep my anthropic plan.
Seems like it would interact very badly with the time based usage reset. If lots of people are hitting their limit and then letting the session idle until they can come back, this wouldn't be an exception. It would almost be the default behaviour.
Is it just for me that the reset cycle of usage limits has been randomly updated? I originally had the reset point at around 00:00 UTC tomorrow and it was somehow delayed to 10:00 UTC tomorrow, regardless of when I started to use Claude in this cycle. My friends also reported very random delay, as much as ~40 hours, with seemingly no other reason. Is this another bug on top of other bugs? :-S
Anthropic releases used to feel thorough and well done, with the models feeling immaculately polished. It felt like using a premium product, and it never felt like they were racing to keep up with the news cycle, or reply to competitors.
Recently that immaculately polished feel is harder to find. It coincides with the daily releases of CC, Desktop App, unknown/undocumented changes to the various harnesses used in CC/Cowork. I find it an unwelcome shift.
I still think they're the best option on the market, but the delta isn't as high as it was. Sometimes slowing down is the way to move faster.
I've noticed the same thing in my own AI assisted work. Feels like I'm moving too fast and it's easy to implement decisions quickly but they really have to be the right f--ing decisions. In the past dev was so slow so you had a lot of time to vet the hard decisions and now you don't.
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 preemptively followed things that I had forgotten to instruct it about but were critical to get a specific part of our data integrity 100% correct.
What's your workflow like? I'd be curious to test OpenAI out again but Claude Code is how I use the models. Does it require relearning another workflow?
Same here. I was a fervent Claude code user at $200/mo until Opus4.7.
Freezing your IDE version is now a thing of the past, the new reality is that we can't expect agentic dev workflows to be consistent and I see too many people (including myself) getting burned by going the single-provider route.
On one hand I’m glad to finally see anthropic communicate on this but at this point all I have to say is… time to diversify?
They lost me a little before then - Claude Code's regressions were so very obvious and there's no sign they've learned their lesson in this article or in the comments of those who work on Claude Code on HN. They'll continue to tweak and generally mess around with a product people are using, altering the behaviour without notice in ways that can severely impact use, for months! GPT5.4 has been remarkably consistent and capable, as a replacement. I've cancelled my max plan.
I started using Claude heavily on the 20th after having not used it for a year. Largely Sonnet 4.6, web, cowork and code. Can confidently say it is significantly worse than this time a year ago and regret that my new employer requires we use it, and only it.
Opus 4.7 via code has been inconsistent for me. Sometimes, it feels like working with a brilliant collaborator and is as good as 4.5 and 4.6 were. Other times, it takes dumb and lazy short cuts. It can be quite frustrating. Its response when I tell it it did something wrong is often to write a memory... which is then does not always read. The inconsistency isn't due to session length or age either. These are all new sessions. I feel like sometimes, I get routed do a dumber model or some other hidden setting is applied.
Maybe he didn't know or they were still figuring it out which is fine they're still engineers who can get things wrong sometimes but the communication felt lackluster and being on the receiving end sucks when you had a reliable setup which then degrades. There is a reason people don't upgrade software and why people say if it works don't fix it, but obviously that's not an option for Anthropic when you want to keep improving the product, so they need good measurement tools and quick rollbacks even if properly "benchmarking" LLMs could prove difficult.
My hypothesis is that some of this a perceived quality drop due to "luck of the draw" where it comes to the non-deterministic nature of VM output.
A couple weeks ago, I wanted Claude to write a low-stakes personal productivity app for me. I wrote an essay describing how I wanted it to behave and I told Claude pretty much, "Write an implementation plan for this." The first iteration was _beautiful_ and was everything I had hoped for, except for a part that went in a different direction than I was intending because I was too ambiguous in how to go about it.
I corrected that ambiguity in my essay but instead of having Claude fix the existing implementation plan, I redid it from scratch in a new chat because I wanted to see if it would write more or less the same thing as before. It did not--in fact, the output was FAR worse even though I didn't change any model settings. The next two burned down, fell over, and then sank into the swamp but the fourth one was (finally) very much on par with the first.
I'm taking from this that it's often okay (and probably good) to simply have Claude re-do tasks to get a higher-quality output. Of course, if you're paying for your own tokens, that might get expensive in a hurry...
So will we have to do what image generation people have been doing for ages: generate 50 versions of output for the prompt, then pick the best manually? Anthropic must be licking its figurative chops hearing this.
This is my theory too. There’s a predictable cycle where the models “get worse.” They probably don’t. A lot of people just take a while to really hit hard against the limitations.
I can't remember what the technique is called, but back in the GPT 4 days there was a paper published about having a number of attempts at responding to a prompt and then having a final pass where it picks the best one. I believe this is part of how the "Pro" GPT variant works, and Cursor also supports this in a way (though I'm not sure if the auto pick best one at the end is part of it - never tried)
I also think some of this stems from the default 1m context window. Performance starts to degrade when context size increases, and each token over (i think the level is) 400k counts more towards your usage limit. Defaulting to 1m context size, if people arent carefully managing context (which they shouldnt ever have to in an ideal world), they would notice somewhat degraded performance and increased token usage regardless.
I have found Claude to be especially unpredictable. I've mostly switched to GPT-5.4 now - although it's slightly less capable, it's massively more reliable.
I think they are routing to cheaper models that present themselves as e.g. Opus. I add to prompts now stuff to ensure that I am not dealing with an impostor. If it answers incorrectly, I terminate the session and start again. Anthropic should be audited for this.
197 comments
[ 0.18 ms ] story [ 111 ms ] thread2. Old sessions had the thinking tokens stripped, resuming the session made Claude stupid (took 15 days to notice and remediate)
3. System prompt to make Claude less verbose reducing coding quality (4 days - better)
All this to say... the experience of suspecting a model is getting worse while Anthropic publicly gaslights their user-base: "we never degrade model performance" is frustrating.
Yes, models are complex and deploying them at scale given their usage uptick is hard. It's clear they are playing with too many independent variables simultaneously.
However you are obligated to communicate honestly to your users to match expectations. Am I being A/B tested? When was the date of the last system prompt change? I don't need to know what changed, just that it did, etc.
Doing this proactively would certainly match expectations for a fast-moving product like this.
Again goes back to the "intern" analogy people like to make.
Damage is done for me though. Even just one of these things (messing with adaptive thinking) is enough for me to not trust them anymore. And then their A/B testing this week on pricing.
I got finally fired.
In my life experience, looking back, when I've found myself swinging from "high trust" to "low trust" the change was usually rooted in my expectations; it was usually rooted in me having a naive understanding of the world that was rudely shattered.
Will you force trust to be a bit? Or can you admit a probability distribution? Bits (true/false or yes/no or trust/don't trust) thrash wildly. Bayesians update incrementally: this is (a) more pleasant; (b) more correct; (c) more curious; (d) easier to compare notes with others.
Claude caveman in the system prompt confirmed?
Is it just me or does this seem kind of shocking? Such a severe bug affecting millions of users with a non-trivial effect on the context window that should be readily evident to anyone looking at the analytics. Makes me wonder if this is the result of Anthropic's vibe-coding culture. No one's actually looking at the product, its code, or its outputs?
The other thing, when anthropic turns on lazy claude... (I want to coin here the term Claudez for the version of claude that's lazy.. Claude zzZZzz = Claudez) that thing is terrible... you ask the model for something... and it's like... oh yes, that will probably depend on memory bandwith... do you want me to search that?...
YES... DO IT... FRICKING MACHINE..
https://www.reddit.com/r/ClaudeAI/comments/1evf0xc/the_real_...
We just got hit by this today in response to a completely boring code question. Claude freaked out about being prompt injected.
Agents are not deterministic; they are probabilistic. If the same agent is run it will accomplish the task a consistent percentage of the time. I wish I was better at math or English so I could explain this.
I think they call it EVAL but developers don't discuss that too much. All they discuss is how frustrated they are.
A prompt can solve a problem 80% of the time. Change a sentence and it will solve the same problem 90% of time. Remove a sentence it will solve the problem 70% of the time.
It is so friggen' easy to set up -- stealing the word from AI sphere -- a TEST HARNESS.
Regressions caused by changes to the agent, where words are added, changed, or removed, are extremely easy to quantify. It isn’t pass/fail. It’s whether the agent still solves the problem at the same percentage of the time it consistently has.
The thing about session resumption changing the context of a session by truncating thinking is a surprise to me, I don't think that's even documented behavior anywhere?
It's interesting to look at how many bugs are filed on the various coding agent repos. Hard to say how many are real / unique, but quantities feel very high and not hard to run into real bugs rapidly as a user as you use various features and slash commands.
Somehow, three times makes me not feel confident on this response.
Also, if this is all true and correct, how the heck they validate quality before shipping anything?
Shipping Software without quality is pretty easy job even without AI. Just saying....
This makes no sense to me. I often leave sessions idle for hours or days and use the capability to pick it back up with full context and power.
The default thinking level seems more forgivable, but the churn in system prompts is something I'll need to figure out how to intentionally choose a refresh cycle.
Glad I use kiro-cli which doesn't do this.
If that was done, users could have been mindful of the change and figure out more easily that their problems could have come from that.
Those who work on agent harnesses for a living realize how sensitive models can be to even minor changes in the prompt.
I would not suspect quantization before I would suspect harness changes.
Recently that immaculately polished feel is harder to find. It coincides with the daily releases of CC, Desktop App, unknown/undocumented changes to the various harnesses used in CC/Cowork. I find it an unwelcome shift.
I still think they're the best option on the market, but the delta isn't as high as it was. Sometimes slowing down is the way to move faster.
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 preemptively followed things that I had forgotten to instruct it about but were critical to get a specific part of our data integrity 100% correct.
Freezing your IDE version is now a thing of the past, the new reality is that we can't expect agentic dev workflows to be consistent and I see too many people (including myself) getting burned by going the single-provider route.
On one hand I’m glad to finally see anthropic communicate on this but at this point all I have to say is… time to diversify?
A couple weeks ago, I wanted Claude to write a low-stakes personal productivity app for me. I wrote an essay describing how I wanted it to behave and I told Claude pretty much, "Write an implementation plan for this." The first iteration was _beautiful_ and was everything I had hoped for, except for a part that went in a different direction than I was intending because I was too ambiguous in how to go about it.
I corrected that ambiguity in my essay but instead of having Claude fix the existing implementation plan, I redid it from scratch in a new chat because I wanted to see if it would write more or less the same thing as before. It did not--in fact, the output was FAR worse even though I didn't change any model settings. The next two burned down, fell over, and then sank into the swamp but the fourth one was (finally) very much on par with the first.
I'm taking from this that it's often okay (and probably good) to simply have Claude re-do tasks to get a higher-quality output. Of course, if you're paying for your own tokens, that might get expensive in a hurry...
And once you get unlucky you can’t unsee it.