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It is very difficult to see this move as anything other than Anthropic pulling the ladder up behind itself. They can dress it up in "safety" all they want, I find it hard to interpret this in a charitable way.

This reminds me of how dark-pattern common wisdom in Web 1.0 website development was to ban external links. Then how social apps prevented the export of data and actively worked to nerf significant interoperability through APIs.

But this is a tool, not just a data moat. Like a knife that degrades your ability to create knives. Or like a text editor that prevents you from implementing a text editor.

It is absolutely fine to distill the IP of everyone else, but you'd be violating the TOS to distill ours :)

It is as if Jetbrains told that "you can't use IntelliJ Idea to develop frontier IDE. We can introduce slight compilation errors if we detect you doing so".

"To effectively contain a civilization’s development and disarm it across such a long span of time, there is only one way: kill its science." - Cixin Liu, The Three-Body Problem

This immediately made me think of the Sophons silently manipulating the sensors of particle accelerators to prevent humanity from developing advanced knowledge of particle physics.

Given the high rate of false positives people are reporting for the non-silent cybersecurity, biological, etc., safeguards, there is a strong likelihood that you will encounter silently nerfed behavior even if you are _not_ violating their TOS.

Ultimately this will be evident in the way customers / external benchmarkers experience Fable. Hopefully competition will drive future models toward a lower false positive rate. Until that happens, Mythos and Fable users seem likely to have pretty divergent experiences.

This is a fun peek into the economic implications of RSI/ASI. Because it's so infinitely valuable that it basically destroys all markets, labs will eventually do stuff like stop releasing models completely and skipping out on contracted commitments because they'll have the power to just drive their competitors out of business before the legal battle gets expensive.

Cloud providers - at first smaller ones, then the hyperscalers - will follow suit, completely closing sales to anyone but the labs and demanding payment in equity/direct decision-making power rather than cash. There's no particular reason why the inference/training split has to be 80/20, and no amount of willingness to pay can help you in an event that turns your money worthless.

The moat looks deep today but it's going to become more shallow every year.

Training a new model from scratch takes serious resources. Post-training/fine-tuning an existing model, dramatically less. The knowledge for the process was esoteric two years ago, now you can ask a current model (one of several) to walk you through it, while building the tools to do it as you go. Several of my recent weekend projects have been exactly that sort of thing, just so I understand it better. "Let's make a LoRA", "let's generate a corpus of training data for fine-tuning a model for X task", "how can I put my face in a text-to-image model?" stuff like that. All of this is do-able on kinda modest local hardware (a couple of old GPUs or a Strix Halo or DGX Spark or big Mac Studio), or for a few bucks or a few hundred bucks or a few thousand bucks of cloud compute, depending on scale.

Scale that up to corporate or startup scale, with the money that's been flowing into AI for the past couple/few years, and it's obviously there's going to be a lot of competition just as the top model makers need to start ringing the cash register. That's a lot of opportunities for people to look at their ballooning Claude usage costs and find other ways to do the same thing for drastically less money. $100/month or $200/month is a no-brainer for Claude Code with probably the best model for coding, but they're pushing more users to usage-based billing which becomes cost-prohibitive real fast.

So, they desperately need to continue to be among the only ways to solve the hardest problems, and they need the alternatives to cost a similar amount. They can count on OpenAI and Google to ratchet up prices, too. They probably can't count on everybody, especially the vendors in China with different economics, to do it. And, they can't count on companies to look at their own usage and not ask, "Can we train a smaller specialist model that does this one thing we're using the Anthropic API most heavily for?"

I'm hoping they just mean stuff like using Claude for distillation by e.g. Chinese model makers, and not "how do I fine-tune Gemma 4 to write more like me?" or whatever.

I guess an uncharitable way to read this might be “the ML engineers/scientists want to automate all of the jobs except their own.”

They have a silent nerfing system for their models and say so openly. The obvious question is how much it is being used already.

Competitor companies being nerfed?

Non Americans getting worse code?

Punishing and rewarding users to maximize engagement, like online games do affecting victories through matchmaking?

"Claude can now be silently nerfed. Anthropic has decided it won't tell users when this happens." W T F!!

I spend a lot of time telling Opus 4.8 to search for security bugs in the code it wrote, and it spends a lot of time finding them, and then fixing them. Fable wont let me fix the security issues that Opus 4.8 created.

I don't understand how businesses could trust cloud LLMs going forward with this ongoing "safety" paranoia. Building dependence on them doesn't feel like a sane strategic decision for users.

It's a SaaS, when in the history of SaaS has it ever been a good idea to trust that the company won't ruin the product under you?

This makes Fable unusable for me. If I cannot tell whether I am paying for the whole service or just a partial one, because somehow their guardrails have decided my work silently broke their terms of service, then I prefer to go to older models or alternatives

I'm really uncomfortable with these changes, like everything Anthropic's doing as "frontier research" today will be regular product engineering in a year.

has dario (or sam tbh) ever been thoroughly asked about the hypocrisy of them claiming distillation to be „theft“ vs. them training on the copyright of others?

I’ve only seen him talk about one of those topics, but never together.

I just can’t see how you can talk yourself out of that hypocrisy, if BS answers are properly followed up on (journalism!)

Wow, this is like saying:

> If you buy a car from us, you agree not use it driving to and from work that involves automotive R&D that might compete with our product. And if our (heavily spying) car detects you are violating this, it will slow down to 20mph and cannot be made to go any faster, until we are sure the violation has ceased.

Or

> If you buy a laptop from us, you agree not to use it to study or acquire any knowledge that you may use to compete against us. If the laptop detects such a use, it degrades to one core and 4GB of memory, until the violation stops.

It was good while it lasted. Time for me to resume my migration to another provider. One that promotes an open ecosystem, even if I can't opt out of them using my data to train. Heck I'll actively GIVE them my data and do my part in promoting openness, tiny though it may be. DeepSeek and GLM looking damn fine for a start.

We need a benchmark that tests a models ability to do LLM research.

PSA: Treat these models like genius interns.

Aren't there immense security risks when the model is allowed to deceive even if it was for "good"?

Reminds me of an excerpt from Edward Fredkin's "The intelligent machine" [1]

https://noor.imx.sh/2017/09/30/when-they-communicate-they-co...

I'm fairly certain they were doing something similar already possibly with some quantizations and not for the good humanity but just trying to handle the increased usage. Not for API requests though, just subscription CLI usage.

The silently never telling you is so insidious on top of it being ridiculous given how they trained the model in the first place. We do distributed model training for embedder/reranker models and I'd deeply resonate that this article's message exactly for our company. We couldn't trust the model in the first place, but now the model is intentionally burning our money if we asked it the wrong question, on top of being deeply expensive in the first place. If we did find evidence of being incorrectly nerfed, we'd never be able to reach a human to let them know. Too many reverse incentives with Anthropic, maybe they're about AI security but that doesn't make them ethical to consumers (i.e. humans).

> If Claude gives me poor or incorrect advice while I’m working on an AI component, I have no way of knowing whether the model was confused, whether my problem is unsolvable, or if some invisible policy restriction quietly kicked in.

You should be able to know if your problem was solvable by using your own expertise and judgement, no? If you're relying on LLMs as a substitute for those, I wouldn't expect great results.

Can't you just switch the toggle that says "switch models when a message is flagged"? I turned mine off in case anything does get flagged I will know..

For now, I'm really not happy about this limited rollout and then turning off. That's probably the most egregious thing I think Anthropic has done recently

I am so happy that Anthropic has signaled the possibility that their UI moat for agentic AI is copyable by competitors. At least that's the way I read this. When companies try to lock something down it can be a signal of weakness.

If so, it's possible to built great user interfaces in Chatbots and more companies/people can have amazing agentic development workflows! We don't have to live in a world where only the market leader has the most enjoyable model.

There is a possibility this may not end at simply nerfing the model. The idea of manipulating the behavior of a model depending on the prompt given to it can extend to

1. Detecting if employees from competing companies are using it and sabatoge their work, even not LLM-training related

2. Direct users to outcomes that would justify higher compute spend. Deliberately coding a project to 95% completion but designed to be losing a critical step right before one's weekly rate limit is expended

3. Reduce the quality of writing when a person is writing an essay where the argument is against the interests of the model company, or steering the user using the model for brainstorming in a direction which causes them to waste time or abandon their train of reasoning

etc. etc. The possibilities are enormous. Many people use AI daily for their job, personal advice, companionship. A model company that steers the behavior of the model towards a deliberate outcome could develop a controlling interest in human behavior and productivity at large, even with subtle influence would compound enormously over its millions of users.

> we’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design).

Dig that moat son, we would want to automate our job away.

So this is what 'alignment' looks like to them.

I bet it's more a case of trying to cut down the competition so that there is not a large distillation just before they IPO.

Everything the large LLM providers do now, I view it through the lens of "how does this impact their IPO?"

I currently have Fable set on cleaning up the work of smaller models to bring my code up to standards I'd feel comfortable developing on manually. Y'know, for when they decide I don't get to use it anymore.

Has it finally come time that I have to be nice to Claude?

I suspect we'll get the same behavior from Codex, even if they don't openly say as much. Maybe they'll openly lie and say "noooo, we'd never do such a thing"

More efforts to get more data and processing power behind local models.

Will be funny when I can call the Office of Weights and Measures on Anthropic because they underweighted the model I was paying for and got pwned because the dumber one missed something.

It kind of sucks, but I get the silent change. If a user was trying to use the model for something untoward, having a rejected prompt would just give signal to train on how to eventually successfully bypass security measures.

Skeptical they’re even able to pull up a ladder there’s so many more models out there making great progress just behind them.

I don't know why anyone is surprised with this, it's their product it's going to behave on their terms. If anything it is surprising that they're admitting to it.

If these interventions create demand for a model with fewer safeguards surely a competitor will meet that demand.

“When you realize the goal is the path, the pursuit itself becomes the prize. Stones in the road are not obstacles blocking your path; they are the path”

now I understand distillation is much more important thank I thought

I'm a big fan of Anthropic. Just check my post history. I've been accused of working there. But this is complete bullshit and they need to get real. Silent sandbagging is not acceptable, especially given they've shown with this release their safety filters have HUGE amounts of false positives.

This kind of opacity is unacceptably user hostile. It's not okay to treat some amount of developers as acceptable casualties, without them even knowing, in order to help enforce a restriction that only serves Anthropic's interests. And if you want to tell me this is for managing the x-risk factor, I'm frankly unimpressed.

Linux killed proprietary UNIX; open source models will kill proprietary AI.

Disillusioned CEOs convincing themselves they have the mandate and right to define morality for everyone else. They get to decide what is right, wrong, permissible, or dangerous from the top, in the name of "safety". This is corporate nannying.

It seems we now have a new product category, HaaS, Hallucination as a Service.

No at least we know why they spent all that money on "safety research".

https://huggingface.co/Trilogix1/Hugston-Nex-N2-Pro-gguf

Governments need to stop contracting these companies and instead invest in public, fully open source models.

These companies are owned and operated by the darkest of dark triads our species has managed to evolve. I doubt Dario is self-aware enough to realize the hypocrisy in all of this safety theater.

Personally I don't even mind that they are anticompetitive and power-hungry (same as it ever was), but it's the cringe-worthy hypocrisy that grinds my gears. This new brand of self-righteous paternal savior overlords is just unbearable.

This is crazy and would be frustrating, I probably would just be using another model as authority and keep fable as reviewer only in this case.

I'm sure someone is gonna be able to jailbreak, abliterate, or equivalent, on this input moderation attempt they have going on.

New frontier in anti-competitive practices.

It’s very frustrating…

> If Claude gives me poor or incorrect advice while I’m working on an AI component, I have no way of knowing whether the model was confused, whether my problem is unsolvable, or if some invisible policy restriction quietly kicked in. Anthropic has explicitly chosen not to tell users when this is happening.

That's always been the case with corporate LLMs.

this is probably overstating their abilities at present - I am experimenting with Fable on a completely benign personal application and I am constantly hitting the "cybersecurity and biology topics" guardrail

I think this is a bit hyperbolic. Fable will fall back to Opus.

"Anthropic says these safeguards only affect 0.03% of developers. Maybe that's true today."

I don't think it's true today. It's like when schools mention "average class size", where that average is dominated by classes with like 2 students instead of classes with 100.

Much more honest would be the percentage of developers who previously used their models for the model development tasks they're targeting, but it actually looks like they're saying 100% of them are affected based on the language around it "always having been prohibited".

So awful.

That's what I observed with Opus. This is probably a lawsuit going to happen because you pay for tokens and you expect to get performance you pay for, instead you never know if the model suddenly become dumb and your whole session has to be started again.

Wow, this is horrible. Local LLMs are the future. Thanks, China! Seriously crazy that I’m saying that, but the American companies are being so anti-freedom they’re making the CCP look libertarian.

Also, Fable’s sensing is hypersensitive. Feels like they just have regex for phrases. No nuance. If I say I’m working on something using “GPUs to train” xyz then, will that trigger this sneaky silent screw-my-stuff-up mode?

I wonder if this would qualify as illegal anticompetitive behavior?

I tried today and it gave cybersecurity error on base64 implementation. It is so nerfed....

Intentionally and silently sabotaging work done with Claude whenever Anthropic decides it is appropriate is unacceptable behavior, and comically tone deaf given the state of open models. Why on earth would I ever pay for a malicious product?

Is there some consumer protection law around this?

Big Monsanto energy

We’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building ... distributed training infrastructure ...)

What an interesting thing to call out as a threat. Hmm.

The part that disturbs me most, is that the model won't reveal you've reached the threshold.

It's literally been designed to gaslight its users in these cases.

If I understand correctly, this is to protect against distillation Reverse Engineering like Deepseek vs OpenAI.

Reads like, permanently shadow ban.

Imagine if Github said "if we detect you're building a competitor to Github, we will silently degrade the results of your CI actions so that tests sometimes randomly fail"

At this point you're criminally incompetent if you still feed your proprietary data and code to AI labs.

They legally can steal it all and now you can't use the product of this theft to improve your own systems.

PRODUCT VIOLATION

https://www.youtube.com/watch?v=Tr3t1uZNbKo

DIRECTIVE 4: [Classified]

Any attempt to arrest a senior officer of OCP results in shutdown.

—

Putting aside my snark, is Anthropic actually anticipating some new expansion of ITAR? (Or a stipulation for the Trump administration taking/not taking a share?)

That is to say, do they expect to be told that they must have this mechanism, not just the terms?

I have never ever trusted "corporate ethics".

Theres no ethical framework. No axioms. Its a mixture of legal, political, and public-facing 'rules'. And what are the rules? Youre not permitted to know.

"We reserve the right to lie about the models we provide, silently downgrade you, and give you blatant misinformation cause you triggered our unstated rules... BUT we'll still use your token budget with lots of thinking and waste your money."

No, folks. Seriously, local LLMs are where its at. You can run the model YOU want, on your hardware, with no data exfiltration.

And with tools like Krasis that can synthesize nvidia ram and system ram as unified-ish memory, makes doing Local LLMs absolutely foable, now!

Imagine if code editors were created by greedy **** behaving as Anthropic, and it would not have been allowed to create other code editors using an existing code editor. Or even better, you couldn't use Bash, zsh, ... to create another cli prompt input tool like Claude Code...

No, this is their get out of jail free card if people start complaining about the model being dumb or forgetful or lying, they can just say, oh well, you must have been doing something that triggered its distillation prevention technique.

And, they can say that for anybody at any time, and you'll never know why, and there's no way to prove it.

Everyone needs a flight data recorder to prove... "here's what I was actually doing and why it was not distillation." And now you're having to prove your innocence instead of them having to prove you're guilty, and really at the end of the day, it's just the model being stupid that they're protecting themselves from.

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