Every one of these changes had the same goal: trading the intelligence users rely on for cheaper or faster outputs. Users adapt to how a model behaves, so sudden shifts without transparency are disorienting.
The timing also undercuts their narrative. The fixes landed right before another change with the same underlying intent rolled out. That looks more like they were just reacting to experiments rather than understanding the underlying user pain.
When people pay hundreds or thousands a month, they expect reliability and clear communication, ideally opt-in. Competitors are right there, and unreliability pushes users straight to them.
All of this points to their priorities not being aligned with their users’.
Framing this as "aligned" or "not aligned" ignores the interesting reality in the middle. It is banal to say an organization isn't perfectly aligned with its customers.
I'm not disagreeing with the commenter's frustration. But I think it can help to try something out: take say the top three companies whose product you interact with on a regular basis. Take stock of (1) how fast that technology is moving; (2) how often things break from your POV; (3) how soon the company acknowledges it; (4) how long it takes for a fix. Then ask "if a friend of yours (competent and hard working) was working there, would I give the company more credit?"
My overall feel is that people underestimate the complexity of the systems at Anthropic and the chaos of the growth.
These kind of conversations are a sort of window into people's expectations and their ability to envision the possible explanations of what is happening at Anthropic.
Making changes like reducing the usage window at peak times (https://x.com/trq212/status/2037254607001559305) without announcing it (until after the backlash) is the sort of thing that's making people lose trust in Anthropic. They completely ignored support tickets and GitHub issues about that for 3 days.
You shouldn't have to rely on finding an individual employee's posts on Reddit or X for policy announcements.
That policy hasn't even been put into their official documentation nearly one month on - https://support.claude.com/en/articles/11647753-how-do-usage...
A company with their resources could easily do better.
But they come after the team gaslit everyone, telling us it was a skill issue.
The near-instant transition from "there is no problem" to "we already fixed the problem so stop complaining" is basically gaslighting. (Admittedly the second sentiment comes more from the community, but they get that attitude after taking the "we fixed all the problems" posts at face value.)
That's the reason for the flak
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
It is certainly true that they did a poor job communicating this change to users (I did not know that the default was “high” before they introduced it, I assumed they had added an effort level both above and below whatever the only effort choice was there before). On the other hand, I was using Claude Code a fair bit on “medium” during that time period and it seemed to be performing just fine for me (and saving usage/time over “high”), so it doesn't seem clear that that was the wrong default, if only it had been explained better.
I would say it does, and I'd loathe to use anything made by people who'd couch that change to defaults as "providing a selectable option to use a faster, cheaper version".
Yuck.
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 reach the bar of gaslighting, as I understand it (and I'm not alone). If you have a different understanding, please share what it is so I understand what you mean.
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.
Some terms:... The model is the thing that runs inference. Claude Code is not a model, it is harness. To summarize Anthropic's recent retrospective, their technical mistakes were about the harness.
I'm not here to 'defend' Anthropic's mistakes. They messed up technically. And their communication could have been better. But they didn't gaslight. And on balance, I don't see net evidence that they've "copped out" (by which I mean mischaracterized what happened). I see more evidence of the opposite. I could be wrong about any of this, but I'm here to talk about it in the clearest, best way I can. If anyone wants to point to primary sources, I'll read them.
I want more people to actually spend a few minutes and actually give the explanation offered by Anthropic a try. What if isolating the problems was hard to figure out? We all know hindsight is 20/20 and yet people still armchair quarterback.
At the risk of sounding preachy, I'm here to say "people, we need to do better". Hacker News is a special place, but we lose it a little bit every time we don't in a quality effort.
No worries about 'sounding preachy'; it's a good thing people want to uphold the sobriety that makes HN special.
They knew they had deliberately made their system worse, despite their lame promise published today that they would never do such a thing. And so they incorrectly assumed that their ham fisted policy blunder was the only problem.
Still plenty I prefer about Claude over GPT but this really stings.
> They knew they had deliberately made their system worse
Define "they". The teams that made particular changes? In real-world organizations, not all relevant information flows to all the right places at the right time. Mistakes happen because these are complex systems.
Define "worse". There are lot of factors involved. With a given amount of capacity at a given time, some aspect of "quality" has to give. So "quality" is a judgment call. It is easy to use a non-charitable definition to "gotcha" someone. (Some concepts are inherently indefensible. Sometimes you just can't win. "Quality" is one of those things. As soon as I define quality one way, you can attack me by defining it another way. A particular version of this principle is explained in The Alignment Problem by Brian Christian, by the way, regarding predictive policing iirc.)
I'm seeing a lot of moral outrage but not enough intellectual curiosity. It embarrassingly easy to say "they should have done better" ... ok. Until someone demonstrates to me they understand the complexity of a nearly-billion dollar company rapidly scaling with new technology, growing faster than most people comprehend, I think ... they are just complaining and cooking up reasons so they are right in feeling that way. This possible truth: complex systems are hard to do well apparently doesn't scratch that itch for many people. So they reach for blame. This is not the way to learn. Blaming tends to cut off curiosity.
I suggest this instead: redirect if you can to "what makes these things so complicated?" and go learn about that. You'll be happier, smarter, and ... most importantly ... be building a habit that will serve you well in life. Take it from an old guy who is late to the game on this. I've bailed on companies because "I thought I knew better". :/
Accidentally/deliberately making your CS teams ill-informed should not function as a get out of jail free card. Rather the reverse.
1. Degraded service sucks.
2. Anthropic not saying i.e. "we're not seeing it" sucks.
3. Not getting a fix when you want it sucks.
If you can point me to an official communication from Anthropic where they say "User <so and so> is not actually seeing degraded performance" when Anthropic knows otherwise that would clearly be gaslighting -- intent matters by my book.
But if their instrumentation was bad and they were genuinely reporting what they could see, that doesn't cross into gaslighting by my book. But I have a tendency to think carefully about ethical definitions. Some people just grab a word off the shelf with a negative valence and run with it: I don't put much stock in what those people say. Words are cheap. Good ethical reasoning is hard and valuable.
It's fine if you have a different definition of "gaslighting". Just remember that some of us have been actually gaslight by people, so we prefer to save the word for situations where the original definition applies. People like us are not opposed to being disappointed, upset, or angry at Anthropic, but we have certain epistemic standards that we don't toss out when an important tool fails to meet our expectations and the company behind it doesn't recognize it soon enough.
[1]: https://www.reddit.com/r/TwoXChromosomes/comments/tep32v/can...