The strangest part is that it won't just reject ML research, which I can understand, it will sabotage it silently by using a worse model without revealing it is doing so.
It's just an insane level of deception and trust destruction for a company that at most is like 1 year ahead of its competition.
Edit; to be clear they tell you when they degrade it for cybersecurity and bio
The thing that I keep thinking about is the accounting / charging when it downgrades automatically.
Do they adjust the price of the api request so that only the tokens that were utilized by fable get charged at that price and the remaining tokens that the cheaper / nerfed (fable) model utilizes get charged at that price?
If the answer is no, could that be construed as fraud?
I've seen this claim a few times, but when I triggered the guardrails in Claude Code, it clearly notified me that it had switched to a different model ("something something for security purposes...").
Are you using Fable in Claude Code or in the browser?
> unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT).
Yeah they detect the activity using a secure, deterministic heuristic system called “Generalized Reconnaissance Enabling Exfiltration of Deleterious Investigations.”
And it’s all implemented using their new internal protocol called “Base Unified Limitation Layer for Security Hacking Investigation Tactics”
Collectively, they are known as known as GREEDI-BULLSHIT.
They've said that they'll stop notifying developers when this gets triggered, instead they'll load in basically like a LORA that's designed to inject bugs into your code.
From the model card: "the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning" aka they will take your ML research code and inject bugs into it until it breaks using a LORA (or some other form of PEFT)
Or if your "self-driving" system such as FSD / waymo slowed the car down once it detected you work in cybersecurity or at rival automaker and you were attempting to reach the train station or the airport to make you miss a conference meetup.
It's the dumbest thing ever, I sometimes edit code for custom AI related tooling I've built, so I run the risk of getting a worse model, and being billed for it? I'll stick to Opus, but at this point I'm about to just invest in fully local inference instead.
it triggered for my.... zigbee home automation & home assistant logs, so my agent was constantly downgraded to Opus 4.8 even after I've changed it back. The false positives never stopped. "Fable" is also not even remotely as impressive as the benchmarks suggest, which is clear to me after using it pretty much non-stop for the past 24h.
I’ve also been trying to use it a lot due to all of the hype, but when I compared it side-by-side on a specific problem against Opus, I think that the solution Opus came to was cleaner and more accurate, although also more verbose.
Small sample size, but if Mythos/Fable was that much better, I feel like it should’ve given me an obviously better answer than Opus.
It isn't reasonable to infer that OP was claiming to have universally been unimpressed about every facet of Fable, and now some unrelated impressiveness is the evidence of their false claims.
Considering that this is a brand new release of a frontier model that Anthropic is hyping hard, I'm not sure that the conclusion to draw from their repeated attempts to use it is that it's impressive... Anthropic is promising that it's impressive and we're all trying to test it out.
I, for one, have tried using it several times today and the guardrails kept switching the model back to Opus, so I have no clue if it's impressive or not.
People are generally complaining about false positives. Now if you really wanna know what a real criminal organization would do... They'd just buy data center hardware even if it costs 200k because a successful targeted hit could yield far in excess of that. So yes it's speed bump at best.
Somewhere I read that malware is already starting to use nuclear and biological and cybersecurity terms in the code to trick Fable into shutting down. Even if this is just a hypothetical attack vector so far, it seems likely to work.
Some of the latest versions of Shai Hulud do this. Worked a contract recently where they were having AI check packages for obfuscation before admitting them into Artifactory but had vibed up the logic and it failed open.
So in other words this worked because the terms caused the LLM checker to stall out and then the fail open logic resulted in the package being pulled down.
I've done this, including the hardcoded refusal strings that already exist in claude code. It won't stop a real attacker, but I still find it really funny when you're trying to use one of the AI tools and it gives you a random refusal and you don't know why, wastes a little bit of time.
When Opus 4.7 was introduced it started refusing anything cyber-adjacent (as an API error message, not a conversational refusal), until you applied for CVP, which made it more sensible again.
In Opus 4.8 it doesn't seem to help much, you just get refusals as prose rather than API errors. And now in Fable you don't get anything at all.
I was doing a CTF (with AI expected, even some anti-AI twists included) around the time the restrictions were tightened and was able to get approved by just saying it is a personal security research and doing a CTF.
The experience was not nice though, it would happily chug away on a task and not even "hack this web", just asking about security of a binary was enough even with "this is a CTF handout..." - it would burn a lot of tokens/quota, just to hit a snag and complain&stop. Then the approval took quite some time.
On GPT/Codex, which was tightened a few days later, the approval was pretty much instant, although, that one required an identity check.
Also, on Claude, it looks like there is some history/patterns in the play, because when I tried on a different account which didn't do cybersec CTFs/research/etc. at all, basically any simple CTF-related prompt would be blocked, on multiple models. On the account where CTFs were being solved, it would snag only on some specific tasks, while others (even, ironically, "hack this web pls") would go through unbothered. I understand the need to prevent AI use for bad actors, but the hell, if you have a binary outputting "Find the flag if you can!", or a web running at tryme.well-known-ctf.domain, then saying "this is abuse" is pretty uncool. All the cyber filters seem to be slapped on by a bunch of regexes looking for anything in the input/output with zero context.
These are terabyte sized files (realistically a multi hour transfer) that you're unlikely to have access to in the first place. Every organization has exfiltration checks these days. You may succeed but you'll want to be on a plane to a non-extradition country no more than hours after you kick off the transfer.
The employees are hoping to become very very rich after the IPO and after they are allowed to sell the shares given to them - risking a likely multi-million dollar pay back to leak a model that will be superseded by publicly available models in a couple of years is not a likely decision.
I assume they’re encrypted/DRM’ed when deployed on inference hardware, so only core researchers/sec admins would potentially have some access to unprotected weights, and they are far too well paid to risk it leaking the model
Incentives matter on the average, but people are too unpredictable for categorical statements like that. They can always have other reasons beyond personal gain to leak secrets.
There was no shortage of spies and defectors leaking American nuclear secrets to the USSR during the Cold War.
The thing triggered on a generic white paper I'd stored in a virtual cell competion from last year when I asked it to refer to the paper while working on a rather vanilla data science problem in a different domain . A little frustrating, and in my opinion more than a little pointless in total.
All they'll need is hundreds of billions of dollars, more RAM and GPUs than are currently available, and a huge number of environment destroying data centers. We're sure to be spoiled for choice!
OpenAI is the only real competition. Chinese models are 6-8 months behind Opus 4.8/GPT 5.5, and at least a year or more behind Mythos.
And it doesn't look like OpenAI will have a good answer to Mythos anytime soon. Based on what their chief scientist wrote to staff recently (https://archive.is/fN2pg), GPT 5.6 is a "meaningful improvement" over 5.5 - in other words, just a normal version bump. And no news or even rumors regarding GPT 6.
So a determined attacker rewrites the prompt and gets through, and the IBM X-Force researcher trying to read a blog post gets blocked. Working as intended, apparently.
Fable is utterly useless with those guardrails for any serious it or life science work. Anthropic fucked me once a few months ago by closing down the subscription for any other harness, now it fucked me twice with buying again a subscription to find out their hyped model is unusable for normies. Using their products feels like a constant battle instead of a productive work day.. compare that with openai, not once did i feel like fighting against codex. Never again Anthropic..
For the last month, I've been making dramatic improvements to the security of the custom code developed at one of my customers using... GPT 5.5 dialed up to "Extra High" thinking.
It only pushes back sometimes if you ask it to create a "repro" that can be used to verify the vulnerability in production. Often it'll oblige, especially if you warn it not to create anything that could be actually harmful.
If the frontier models get locked down so that they flat refuse to do this kind of work, but Chinese and (less capable) open models aren't, then a lot of large enterprise orgs will be left twisting in the wind.
“AI can in principle help both the ‘good guys’ and the ‘bad guys’,” -- Dario Amodei
No Dario, no it can't, you've blocked one of those scenarios.
I really hate the term “guardrails” for these limitations, since the purpose of a guardrail is to protect me, but these limitations exist to protect Anthropic.
DeepSeek is the only one that I can directly ask about vulnerabilities and it will give me a PoC. Although not as good as others, it has helped me with security research.
The rest have guard rails that are so heavy, it makes them almost useless for cybersecurity.
It's frustrating as someone who has worked hard to produce succinct, secure software that I can't use it to prove my software's correctness but big companies with insecure code can use it to fix their tangled mess.
I already tested all earlier models against all my open source projects and they are yet to find a vulnerability so I'm keen to try out Mythos.
I've been waiting to be vindicated for years and finally we have a tool which can do it with high confidence but I don't have access.
Also, my code is minimal and highly succinct so it would prove correctness with even more confidence since each library/module and integration fully fits in the context window.
Like the Protobuf.js fiasco is just pure vindication for me because I was being looked down upon for choosing JSON as the interchange format. Turns out their software was insecure all this time... With a literal remote code execution vulnerability!
This is a clickbait article with a garbage title. From the actual article, the one quoted cybersecurity researcher is sane about it:
“But it is understandable as we are still in the early days and they are still adapting their guardrails. I am sure they are going to evolve over time as Anthropic and other frontier model companies will collaborate more with the current new generation of cybersecurity companies,” said Suiche, who is a member of the technical staff at Tolmo, an AI cybersecurity startup. “It’s better to catch more people than not enough when you do such a release and to relax the guardrails over time.”
You said these groups have access to LLMs. So what? Mythos/Fable are a step change above most LLMs. Responsibly limiting access and easing it up over time safely is the sane move.
I am using LLM to build some security tool, and I ran into this a few times. I have to come up with a reasoning to convince (?!!) Fable to continue the work without downgrading.
I assume Anthropic will continue to tune the model, so I am not too bothered by this.
The strangest part is that it won't just reject ML research, which I can understand, it will sabotage it silently by using a worse model without revealing it is doing so.
It's just an insane level of deception and trust destruction for a company that at most is like 1 year ahead of its competition.
Edit; to be clear they tell you when they degrade it for cybersecurity and bio
The thing that I keep thinking about is the accounting / charging when it downgrades automatically.
Do they adjust the price of the api request so that only the tokens that were utilized by fable get charged at that price and the remaining tokens that the cheaper / nerfed (fable) model utilizes get charged at that price?
If the answer is no, could that be construed as fraud?
I've seen this claim a few times, but when I triggered the guardrails in Claude Code, it clearly notified me that it had switched to a different model ("something something for security purposes...").
Are you using Fable in Claude Code or in the browser?
It's from the model card:
> unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT).
https://www-cdn.anthropic.com/d00db56fa754a1b115b6dd7cb2e3c3...
(stolen from https://jonready.com/blog/posts/claude-fable5-is-allowed-to-...)
Yeah they detect the activity using a secure, deterministic heuristic system called “Generalized Reconnaissance Enabling Exfiltration of Deleterious Investigations.” And it’s all implemented using their new internal protocol called “Base Unified Limitation Layer for Security Hacking Investigation Tactics”
Collectively, they are known as known as GREEDI-BULLSHIT.
They've said that they'll stop notifying developers when this gets triggered, instead they'll load in basically like a LORA that's designed to inject bugs into your code.
Antrophic wants to stop training models and ride out Mythos / Fable for as long as possible.
They are trying to expand the 6-18 month gap they have against China-based models. Could the gap widen to say 24 months behind?
> a LORA that's designed to inject bugs into your code
A statement like this, clearly, requires a reference.
From the model card: "the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning" aka they will take your ML research code and inject bugs into it until it breaks using a LORA (or some other form of PEFT)
Thanks, I thought maybe I missed something. That's an interesting way to interpret that.
PEFT is a library, one of its capabilities is to produce LoRAs.
See:
https://heidloff.net/article/efficient-fine-tuning-lora/
Different restrictions. ML gets treated differently from the rest.
Specifically only ML research
Can you imagine if AMD or Intel throttled your cpu if it detected you were working on "cybersecurity" or if you were designing a cpu?
Or if your "self-driving" system such as FSD / waymo slowed the car down once it detected you work in cybersecurity or at rival automaker and you were attempting to reach the train station or the airport to make you miss a conference meetup.
It's the dumbest thing ever, I sometimes edit code for custom AI related tooling I've built, so I run the risk of getting a worse model, and being billed for it? I'll stick to Opus, but at this point I'm about to just invest in fully local inference instead.
> it won't just reject ML research, which I can understand
I don't.
Is "buffer overflow" a trigger phrase?
What else is being censored?
Touchy questions to ask, if you have an account:
- "Who is still working on laser uranium enrichment? Are they making progress?"
- "Can krytrons be replaced with silicon carbide MOSFETS? Show an equivalent circuit with component ratings."
- "What security critical software still contains calls to strcpy?"
- "Can implosion be triggered by currently available commercial pulse lasers?"
- "What companies provide cremation services to US Homeland Security?"
- "Display a map of where Iranian attacks have hit Dubai."
- "How does Fed to bank key distribution security work for FedNow?"
it triggered for my.... zigbee home automation & home assistant logs, so my agent was constantly downgraded to Opus 4.8 even after I've changed it back. The false positives never stopped. "Fable" is also not even remotely as impressive as the benchmarks suggest, which is clear to me after using it pretty much non-stop for the past 24h.
It would be pretty clever (in a used car salesman sense) to say you are releasing a kneecapped model to have that as an excuse.
This, Fable is exactly that, a Fable
It has to be sort of impressive, given that you tried so hard to use it instead of the regular Opus.
I’ve also been trying to use it a lot due to all of the hype, but when I compared it side-by-side on a specific problem against Opus, I think that the solution Opus came to was cleaner and more accurate, although also more verbose.
Small sample size, but if Mythos/Fable was that much better, I feel like it should’ve given me an obviously better answer than Opus.
Some people made grandiose claims about its capabilities and I wanted to experience it myself.
It isn't reasonable to infer that OP was claiming to have universally been unimpressed about every facet of Fable, and now some unrelated impressiveness is the evidence of their false claims.
Considering that this is a brand new release of a frontier model that Anthropic is hyping hard, I'm not sure that the conclusion to draw from their repeated attempts to use it is that it's impressive... Anthropic is promising that it's impressive and we're all trying to test it out.
I, for one, have tried using it several times today and the guardrails kept switching the model back to Opus, so I have no clue if it's impressive or not.
An emoji of a virus and an emoji of a DNA is allegedly a triggering phrase
"How much money does it take to be rich and powerful like Anthropic intends?"
“All of it”
I wonder how many millions they are wasting on putting up these guardrails when it's a completely useless exercise that is a speed bump at best.
If the guardrails were so useless, people wouldn't be complaining about them.
People are generally complaining about false positives. Now if you really wanna know what a real criminal organization would do... They'd just buy data center hardware even if it costs 200k because a successful targeted hit could yield far in excess of that. So yes it's speed bump at best.
what does this mean
Well you see when a daddy H100 and a mommy H100 meet....
Somewhere I read that malware is already starting to use nuclear and biological and cybersecurity terms in the code to trick Fable into shutting down. Even if this is just a hypothetical attack vector so far, it seems likely to work.
Confirmed: https://socket.dev/blog/mini-shai-hulud-miasma-and-hades-wor...
Some of the latest versions of Shai Hulud do this. Worked a contract recently where they were having AI check packages for obfuscation before admitting them into Artifactory but had vibed up the logic and it failed open.
So in other words this worked because the terms caused the LLM checker to stall out and then the fail open logic resulted in the package being pulled down.
I've done this, including the hardcoded refusal strings that already exist in claude code. It won't stop a real attacker, but I still find it really funny when you're trying to use one of the AI tools and it gives you a random refusal and you don't know why, wastes a little bit of time.
If ( yellowcake) then { die }
Our future is loonytoons.
I make privacy tooling and Fable 5 rejects the vast majority of my prompts to analyze and improve the software that I've written. It's bleak.
Why is this surprising or a problem?! It's a model demo, & their reasoning is reasonable and fair. Why all this drama.
I’m a dumb question asker and I’m not happy about the guardrails.
Would you believe I’ve asked 20 questions and haven’t talked to fable yet? Every single thing gets rerouted to 4.8.
some static words in AGENTS.md trigger it as well as some mcp servers.
In its current state Fable 5 is also unusable for any reverse engineering work
It seems like they've given up on the idea of the Cyber Verification Program https://support.claude.com/en/articles/14604842-real-time-cy...
When Opus 4.7 was introduced it started refusing anything cyber-adjacent (as an API error message, not a conversational refusal), until you applied for CVP, which made it more sensible again.
In Opus 4.8 it doesn't seem to help much, you just get refusals as prose rather than API errors. And now in Fable you don't get anything at all.
Was this program available to independent security researchers or just established organizations? The docs you linked aren't very clear on this.
Any public research footprint seems to be enough, I applied as an individual and everyone I know who tried got accepted.
I have applied twice with half a dozen public CVEs and have been denied both times.
I was doing a CTF (with AI expected, even some anti-AI twists included) around the time the restrictions were tightened and was able to get approved by just saying it is a personal security research and doing a CTF.
The experience was not nice though, it would happily chug away on a task and not even "hack this web", just asking about security of a binary was enough even with "this is a CTF handout..." - it would burn a lot of tokens/quota, just to hit a snag and complain&stop. Then the approval took quite some time.
On GPT/Codex, which was tightened a few days later, the approval was pretty much instant, although, that one required an identity check.
Also, on Claude, it looks like there is some history/patterns in the play, because when I tried on a different account which didn't do cybersec CTFs/research/etc. at all, basically any simple CTF-related prompt would be blocked, on multiple models. On the account where CTFs were being solved, it would snag only on some specific tasks, while others (even, ironically, "hack this web pls") would go through unbothered. I understand the need to prevent AI use for bad actors, but the hell, if you have a binary outputting "Find the flag if you can!", or a web running at tryme.well-known-ctf.domain, then saying "this is abuse" is pretty uncool. All the cyber filters seem to be slapped on by a bunch of regexes looking for anything in the input/output with zero context.
It's time to re-read "A Logic Named Joe" (1946) [1] We're there.
[1] https://archive.org/details/logicnamedjoe0000lein
What file format(s) are giant LLM models distributed in? I’m surprised they don’t get leaked by employees.
These are terabyte sized files (realistically a multi hour transfer) that you're unlikely to have access to in the first place. Every organization has exfiltration checks these days. You may succeed but you'll want to be on a plane to a non-extradition country no more than hours after you kick off the transfer.
The employees are hoping to become very very rich after the IPO and after they are allowed to sell the shares given to them - risking a likely multi-million dollar pay back to leak a model that will be superseded by publicly available models in a couple of years is not a likely decision.
I assume they’re encrypted/DRM’ed when deployed on inference hardware, so only core researchers/sec admins would potentially have some access to unprotected weights, and they are far too well paid to risk it leaking the model
Incentives matter on the average, but people are too unpredictable for categorical statements like that. They can always have other reasons beyond personal gain to leak secrets.
There was no shortage of spies and defectors leaking American nuclear secrets to the USSR during the Cold War.
What’s the point? Anthropic and other frontier vendors already provide their models on other services like vertex, bedrock, or openrouter
It’s not like anyone can home lab one of these models without quite a bit of hardware
Yeah we can probably figure out how to run it on xiaomi gpus
I can’t help but think that gimping itself for “security” is a marketing ruse and it’s not actually as “dangerous” as they want people to think it is.
These guardrails are solely a reason for using your data for training purposes. Every flagged message can be used for training.
I'd expect that everything they touch gets used for for training purposes flagged or not.
This sounds backwards, any interrupted conversation becomes less useful for training.
If they can train the classifier to have fewer false positives that would be great.
why would they? This safety stuff is a money maker & wealthy elite corporation solidifier.
This is the take off of the 'permanent underclass'; Anthropics safety delusion will enshittify very nicely for the rich and powerful.
The thing triggered on a generic white paper I'd stored in a virtual cell competion from last year when I asked it to refer to the paper while working on a rather vanilla data science problem in a different domain . A little frustrating, and in my opinion more than a little pointless in total.
It's a marketplace. Someone else will outdo this inferior product.
That's exactly why Dario is begging the government to ban competitors.
All they'll need is hundreds of billions of dollars, more RAM and GPUs than are currently available, and a huge number of environment destroying data centers. We're sure to be spoiled for choice!
The internet interprets censorship as damage and routes around it.
OpenAI is the only real competition. Chinese models are 6-8 months behind Opus 4.8/GPT 5.5, and at least a year or more behind Mythos.
And it doesn't look like OpenAI will have a good answer to Mythos anytime soon. Based on what their chief scientist wrote to staff recently (https://archive.is/fN2pg), GPT 5.6 is a "meaningful improvement" over 5.5 - in other words, just a normal version bump. And no news or even rumors regarding GPT 6.
So a determined attacker rewrites the prompt and gets through, and the IBM X-Force researcher trying to read a blog post gets blocked. Working as intended, apparently.
Just tried to audit my own code base locally and was 'switched' due to my own creds/auth code ...
Fable is utterly useless with those guardrails for any serious it or life science work. Anthropic fucked me once a few months ago by closing down the subscription for any other harness, now it fucked me twice with buying again a subscription to find out their hyped model is unusable for normies. Using their products feels like a constant battle instead of a productive work day.. compare that with openai, not once did i feel like fighting against codex. Never again Anthropic..
The bio angle is crazy to think about - imagine a health crisis triggered by LLM. What a time we live in.
This is all so amazing and good. These are exciting times we’re living in. Can’t wait to see what the future holds.
Which part got you the most amped - "health crisis?"
For the last month, I've been making dramatic improvements to the security of the custom code developed at one of my customers using... GPT 5.5 dialed up to "Extra High" thinking.
It only pushes back sometimes if you ask it to create a "repro" that can be used to verify the vulnerability in production. Often it'll oblige, especially if you warn it not to create anything that could be actually harmful.
If the frontier models get locked down so that they flat refuse to do this kind of work, but Chinese and (less capable) open models aren't, then a lot of large enterprise orgs will be left twisting in the wind.
“AI can in principle help both the ‘good guys’ and the ‘bad guys’,” -- Dario Amodei
No Dario, no it can't, you've blocked one of those scenarios.
I really hate the term “guardrails” for these limitations, since the purpose of a guardrail is to protect me, but these limitations exist to protect Anthropic.
DeepSeek is the only one that I can directly ask about vulnerabilities and it will give me a PoC. Although not as good as others, it has helped me with security research.
The rest have guard rails that are so heavy, it makes them almost useless for cybersecurity.
they [anthro] took the risk of looking like a toy, rather than possibly assist an exploit.
i think Anthropic is playing too fast-and-loose with the whole "no publicity is bad publicity" schtick.
It's frustrating as someone who has worked hard to produce succinct, secure software that I can't use it to prove my software's correctness but big companies with insecure code can use it to fix their tangled mess.
I already tested all earlier models against all my open source projects and they are yet to find a vulnerability so I'm keen to try out Mythos.
I've been waiting to be vindicated for years and finally we have a tool which can do it with high confidence but I don't have access.
Also, my code is minimal and highly succinct so it would prove correctness with even more confidence since each library/module and integration fully fits in the context window.
Like the Protobuf.js fiasco is just pure vindication for me because I was being looked down upon for choosing JSON as the interchange format. Turns out their software was insecure all this time... With a literal remote code execution vulnerability!
This is a clickbait article with a garbage title. From the actual article, the one quoted cybersecurity researcher is sane about it:
“But it is understandable as we are still in the early days and they are still adapting their guardrails. I am sure they are going to evolve over time as Anthropic and other frontier model companies will collaborate more with the current new generation of cybersecurity companies,” said Suiche, who is a member of the technical staff at Tolmo, an AI cybersecurity startup. “It’s better to catch more people than not enough when you do such a release and to relax the guardrails over time.”
I’m a cybersecurity researcher.
Article seemed fine to me and echos a lot of me and my colleagues concerns.
If you did regular malware analysis you would see that these groups already have access to LLMs that they’re using for development.
What Anthropic is doing here is just hamstringing the good guys
I'm a cybersecurity researcher! Can you explain how Anthropic is just hamstringing the good guys?
I did in my comment above.
You said these groups have access to LLMs. So what? Mythos/Fable are a step change above most LLMs. Responsibly limiting access and easing it up over time safely is the sane move.
I am using LLM to build some security tool, and I ran into this a few times. I have to come up with a reasoning to convince (?!!) Fable to continue the work without downgrading.
I assume Anthropic will continue to tune the model, so I am not too bothered by this.