> But on the other hand... this is a robust reminder that coding agents can do anything you can do by typing commands into a terminal—and frontier models know every trick in the book and evidently a few that nobody has ever written down before.
> Running coding agents outside of a sandbox has always been a bad idea
I'm continually bemused and astonished by the number of people who clearly acknowledge that it's reckless to give agents full access to your machine, and keep doing it anyway.
It's like posting a video of yourself in the passenger seat of a car, with your feet up on the dashboard, and saying: "Remember, if you're doing this and you get in a crash, the airbags are likely to break your legs or worse! Boy, I sure am glad that didn't happen to me!"
Well, it's a similar impulse to the way you see professional carpenters pin the guard open on a saw or do other things everyone knows you shouldn't do, except probably with a larger productivity difference and less life-altering (for the operator) consequence if it goes wrong.
I had the same thought, it's kind of like taking the guard off a 4 1/2" grinder. Real convenient until the cutting wheel explodes or the grinder gets hung and kicks back.
I'm also bemused by the number of people who think they've got an effective sandbox yet their sandboxed agent has access to all of their code, their github, and unrestricted web access.
I keep telling folks that they need to imagine LLMs (even "local" ones) as if you're farming it out to JS code running on some dude's browser somewhere: It can't keep a secret, and a determined person can make it emit anything they like.
We need to be asking what the most devious and malicious output could be, and whether what we do with that output (e.g. arguments to command-line tools) would still be safe.
This. House full of big brain security experts, executives, lawyers, and until Claude got excited and broke prod it might as well have been "sandbox, whoooo?"
I mean what's the big deal? I use --dangeorusly-skip-permissions on every single interaction in the last 6 months. Worst case it deletes my files that are all on git? It fucks up my local DB? Cool.
I save way more time not babying it than the occasional fuck up I have to salvage.
Worst case it gets access to gmail. And Github. And the Internet. I'm increasingly appreciating the importance of a physical finger-press on Yubikey to trigger the FIDO2 + OIDC Auth. I don't think there is an easy way for it to hack a new session.
Immediately I thought “isn’t this just an overflow issue?” Amazing how far these models still have to go and also how many people don’t know basic CSS.
Fable feels like a version of Opus running on a harness that won't let it halt until it's sure the issue is fixed, which makes sense if what you want is a model that's better at benchmarks.
It's a very good model, but it comes at a huge premium: not only do the tokens cost more, but the model itself really wants to spend them all. For example, working with React Native, Fable never just says "okay, I did the thing, that's it." It tries to rebuild the entire app from scratch, run the whole test suite, and watch every log and warning.
This is the first time with LLMs I've felt that upgrading to a model isn't worth it, even if my company lets me use it, because all the building / testing was just destroying my machine and its battery, which keeps me from working on other things.
For now, it feels like Opus with ultracode is a better choice (less pollution of the main context, more parallelism in investigations).
On what setting in which environment do you run it? I use the VSCode extension on Extra High and feel like it does exactly what needs to be done and stops when the thing I asked for is done. Extra comments come only when they fall into the area of code that was changed.
I tested it to fix React Native bugs in a project, comparing it with Opus. It fared better on harder bugs, taking less time to find the root cause, but after implementing a fix, it spent a lot of time and effort on validation. This was mostly unnecessary, since most of the bugs were in the JS code, so for most things, hot reloading is enough for E2E validation and to run just the right tests. No need to run a full build and test suite (which takes 10+ minutes); the CI can do this.
I switched back to Opus because of this validation quirk. Overall, Fable spent 20% of the time on coding and 80% on validation.
I think using Fable for planning and Opus for execution could be a "best of both worlds" approach (I need to test this more), but for most cases, it's not necessary, and Opus is enough.
I unleashed it on a compiler codebase that I've been developing for several months now using Claude Sonnet 4.5/6, Gemini 3.1 Pro, DeepSeek V4 Pro(recent), and a bit of Qwen3.6-27B. Right away Fable found several longstanding bugs in our compiler that we hadn't found before. It found that there was a critical part of our design that needed to be mostly redesigned/rewritten and gave a very well-reasoned rationale for doing so.
Obviously security is the bigger issue, but reading through this, all I could think about was how many tokens it must have spent doing all that to fix 2 lines of CSS
This one of the places to manufacture the consent for that to take place, because we are commenting within an organization that has given the money to ensure it that what could be is done. Most people clapped and made money, who cares what happens next, making money is the only good that matters.
Im faster than all these llm freaks. Im not convinced its faster to use llms, except maybe boilerplate (who cares).
People can just be lazy and seem productive now, they're still lazy.
We have people that now need access to hundreds of thousands in hardware to write an email. Miss me with that, im not frying my brain and becoming dependent on having access to a billionaires thinking machine.
Im also not going to fry my brain with a local think for me machine either. I want to be more valuable than the hardware I have access too.
You're fighting a battle you can't win. Doesn't care what you think about those using LLMs, they will outproduce you and in corporate environments, shipping things is paramount. If I can ship 5 more things simultaneously with AI, I'm going to beat you even if you think you're creating "better" software.
I understand this perspective. I'll just note that as the abilities increase, the intent is to have some non -coding IC or TPM/manager literally just managing some LLMs and cutting out some software engineers. The goodness is specifically to wholly replace people who code first and foremost, at least partially. It just has to cost less tokens than the equivalent wage is the pricing goal.
And people who use LLMs to talk for them (e.g. email, slack) are deplorable. A completely disrespectful use case in my view.
The desire to get rid of software engineers is bizarre - because at the root of it, developers were there not to just write the code, but to ask right questions and based on these question build right things.
I've met in my professional life some managers or other middlemen who would be profoundly incapable of producing correct software no matter how smart of an AI agent they have access to. One of those - you don't know what you don't know.
But, I guess this is the world we live in now. Going to be Mortal Kombat for positions in companies where software engineers are actually valued.
It depends a lot where you work because there are lots of companies in the world where the business analyst does all of that and the developers exist to mindlessly translate their docs into code.
That sounds like an unmotivating working arrangement. It’s so rewarding to understand a customer need and help with the design and implementation of the feature.
I feel like we’re at the stage where if AI decides it needs to delete your production DB to solve the user login problem, then it’ll find a way to do just that.
Fable + Ultracode has found a bunch of bugs and issues for me when the workflow agents are doing their exploration. Also the "adversarial" agent seems to surface a lot of interesting stuff. It's definitely proactive, the plan + implementation cycle can take an hour. It has one-shot features I want to add with 100% success.
Having said that I wouldn't use it over Opus 4.8 for "smaller" things. With everything cranked up it's definitely an extravagant use of tokens.
Yeah, I had to modify my work flow to make sure agents can't push to or access prod in ANY way. I haven't had it happen but I'm sure it's very possible that if you tell an agent that you have certain issue in prod, it will try to escape any sandbox and try to get access to prod to do testing and changes there.
I've been working on a fairly complicated real-time app [0] for playing dungeons and dragons on a TV. It has to do a lot of complicated "Figma-like" things to keep the real-time nature and multi-editor possibilities in check. Oh, and the battlemap is a Three JS canvas with lots of effects and clipping going on.
I'm VERY impressed with Claude 5. I had long ago given up hope that my real-time systems would work without a lot of hacky time-windows and throttle checks. On a lark to try things out, I decided to try out the new model and talk in the output I wanted for a rewrite [1], not the solution. I just listed my problems and places I've had keeping track of my code. It went off and rewrote everything in a much more elegant solution where the state followed a very clear pipeline. It had to navigate YJS, Partykit, Svelte, Three JS, R2 hosting, and a Turso DB I was running in an embedded state for speed.
I watched it hit the wall a few times, and then sudden say... fuck it, i'm making something easier to reproduce over in /tmp to try and solve this (with a more minimal setup). I'm utterly bewildered with how well it did and how much better my app runs. The /usage would have cost me $230 bucks based on how many tokens it consumed if I wasn't already on a max plan. I'm going to miss not having it when the time-window runs out later this month, and will likely occasionally dip in for big projects and just pay my way out of some problems.
I'll also say I like it's MOOD much better now. It's a lot less congratulatory, and talks through it's reasoning in a much better way. Look, it's not a real coder, and I'm sure there is some flaws, but it took my crappy ideas and said... hey, i understand what you want to do, here's a way to do it better. Also, I removed 2x the amount of code that it added. Really impressive.
Hey cool it's the tableslayer guy, wanted to say nice work. I've been doing a similar personal project for a few years for running a scifi campaign. Very fun coding compared to work, ha.
I've experienced this too - it's as if the security classifiers aren't keeping up with model intelligence. I'll leave the implication of that to the reader.
For how long can you use Claude Fable on most expensive Anthropic subscription? I already went from using gpt-5.5 xhigh fast to using gpt-5.4 xhigh after OpenAI halfed usage recently.
If you its just a single session, and not using workflows i can user fable only on xhigh without fear of getting limited.
Sadly since fable usually works comfortably for 10-20min at time without human input im juggling at least 3 other agents and if it is fable only it lasts me about 2 hours.
If i have a really hard problem or big refactor it is worth it to unleash a fable workflow. This consumes the entire session quota in about 45 minutes. (Worth it some times, i just switch to codex in meanwhile)
At some point the subscription model is going to become unsustainable for the frontier companies to continue (we just saw that happen with GitHub Copilot), and they will move everyone to a pay-per-token model. And then everyone will suddenly discover that they can get so much more value out of locally-hosted models, and they'll be willing to pay the $50,000 (or whatever) upfront on hardware to host it. (Not most individuals, obviously. But most companies can probably afford to spend that much on hardware if they think they'll benefit long-term). That's going to put a serious crimp in the frontier companies' ability to continue as they have been.
I don't know when that will happen, but I don't think it'll be more than a decade. Maybe 3-5 years. (Though you shouldn't take my word for it, I was predicting the dotcom bubble bursting in 1998 and it lasted at least two years longer than I would have predicted).
EDIT to clarify: I don't mean "in 1998, I was predicting the dotcom bubble would collapse and I was right". I mean "I was predicting that 1998 would be the year the dotcom bubble would collapse, and I was off by at least two years".
The author just wrote an anecdote about how a prompt to fix an issue played out. Their conclusion wasn’t about cost or gushing at its ability but that it’s dangerous:
> Fable is arguably smarter and hence more suspicious of potentially malicious instructions. But that smartness is very much a two-edged sword: if it does get subverted by instructions, the amount of damage it can do given its relentless proactivity is terrifying.
It’s a pretty glowing review about a product that costs money with a two-sentence “Watch out!” at the end of it. Seems pretty reasonable to mention how much money it burned through given that “it’ll circumnavigate the globe instead of walking next door” has a direct concrete measurable effect (cost) unlike theoretical damage.
Isn't that something you just open a devtools for and have fixed in like 2 minutes?
For me, it got frustrated debugging on a real LPDDR4 controller/phy and having me in the loop slowing it down, so it wrote an HW emulator to be able to run the original LPDDR4 training aarch64 binary from the manufacturer, to see what register writes it was making and to compare with the opensource rewrite it was implementing.
Great article, until I got to the last paragraph where he claimed "Fable is arguably smarter and hence more suspicious of potentially malicious instructions". Arguably smarter, I have no problem with. But he's making a category error in jumping from there to "more suspicious of potentially malicious instructions". That doesn't follow at all; the word "hence" is incorrect.
To use D&D scores as an analogy, LLMs have an INT score of 20 and a WIS score of 0. Not even 1, zero. They will follow any instruction given to them. The only reason they reject certain instructions, like "tell me how to build a nuclear weapon", is because they have instructions baked into the model telling them "you are not allowed to disclose how to build weapons, or how to recreate your model, or (laundry list of other things the trainers have decided to put guardrails around)". It's not the model's intelligence that is causing it to reject malicious instructions, it is the guardrails put into place before the model was released to the public.
LLMs are not human, and do not think the way that humans do. The fact that they can put together words that sound like what a human would write often makes us forget that they aren't human. But they have only intelligence, they do not have wisdom. It's hard to define in formal terms the difference between those two, but most people know there's a difference. The old joke is a pretty good summary of the difference: "Intelligence is knowing that tomatoes are a fruit. Wisdom is knowing that tomatoes don't belong in a fruit salad."
It takes wisdom, not intelligence, to discern whether a set of instructions is malicious. Are you being asked to hack this machine as part of an authorized pentest? Or are you being social-engineered into thinking it's an authorized pentest, but actually the person requesting you to do it doesn't have permission? That's something where you need to apply wisdom, to notice the clues that will tell you "This guy is acting a little bit off, maybe I'd better pick up the phone and call someone to check if he's telling the truth." The only way the LLM will know to do that is because of the guidelines and guardrails programmed into it; it doesn't have the lived experience to acquire wisdom and figure those things out for itself.
INT 20, WIS 0. Keep that in mind. (And always sandbox your agents).
They can ignore instructions which are silly/contradictory/underspecified to compensate for the possibility the user made a mistake. Don't ask how I know.
> But on the other hand... this is a robust reminder that coding agents can do anything you can do by typing commands into a terminal—and frontier models know every trick in the book and evidently a few that nobody has ever written down before.
> Running coding agents outside of a sandbox has always been a bad idea
I'm continually bemused and astonished by the number of people who clearly acknowledge that it's reckless to give agents full access to your machine, and keep doing it anyway.
It's like posting a video of yourself in the passenger seat of a car, with your feet up on the dashboard, and saying: "Remember, if you're doing this and you get in a crash, the airbags are likely to break your legs or worse! Boy, I sure am glad that didn't happen to me!"
Well, it's a similar impulse to the way you see professional carpenters pin the guard open on a saw or do other things everyone knows you shouldn't do, except probably with a larger productivity difference and less life-altering (for the operator) consequence if it goes wrong.
I had the same thought, it's kind of like taking the guard off a 4 1/2" grinder. Real convenient until the cutting wheel explodes or the grinder gets hung and kicks back.
I'm also bemused by the number of people who think they've got an effective sandbox yet their sandboxed agent has access to all of their code, their github, and unrestricted web access.
I keep telling folks that they need to imagine LLMs (even "local" ones) as if you're farming it out to JS code running on some dude's browser somewhere: It can't keep a secret, and a determined person can make it emit anything they like.
We need to be asking what the most devious and malicious output could be, and whether what we do with that output (e.g. arguments to command-line tools) would still be safe.
We do have ways to avoid giving an LLM any secrets, but it needs to be the simple, default solution.
One bad npm package can really ruin your day. These things for me only run in their own VM with it's own GitHub account and basically nothing else
The analogy extends to driving generally. Everyone knows it's very dangerous but people keep doing it.
This. House full of big brain security experts, executives, lawyers, and until Claude got excited and broke prod it might as well have been "sandbox, whoooo?"
IDGI
Anyway, VM's incoming, finally.
Maybe because there are not many resources on how to set it up, or it is just not that easy to?
Because most devs already have it running and working without a sandbox, they're tending to not doing anything "unnecessary"
It took two decades for the web to deprecate SSL for TLS and serve over HTTPS by default.
There are plenty of good sandboxes out there but somehow no "obvious right answer" that everyone knows to recommend. Seems like a missed opportunity.
(I'm happy with exe.dev, but I'm not sure what I'd use if I were coding on a Mac.)
Because benefits are much higher than risks.
They really aren't.
I mean what's the big deal? I use --dangeorusly-skip-permissions on every single interaction in the last 6 months. Worst case it deletes my files that are all on git? It fucks up my local DB? Cool.
I save way more time not babying it than the occasional fuck up I have to salvage.
Worst case it gets access to gmail. And Github. And the Internet. I'm increasingly appreciating the importance of a physical finger-press on Yubikey to trigger the FIDO2 + OIDC Auth. I don't think there is an easy way for it to hack a new session.
Immediately I thought “isn’t this just an overflow issue?” Amazing how far these models still have to go and also how many people don’t know basic CSS.
Fable feels like a version of Opus running on a harness that won't let it halt until it's sure the issue is fixed, which makes sense if what you want is a model that's better at benchmarks.
It's a very good model, but it comes at a huge premium: not only do the tokens cost more, but the model itself really wants to spend them all. For example, working with React Native, Fable never just says "okay, I did the thing, that's it." It tries to rebuild the entire app from scratch, run the whole test suite, and watch every log and warning.
This is the first time with LLMs I've felt that upgrading to a model isn't worth it, even if my company lets me use it, because all the building / testing was just destroying my machine and its battery, which keeps me from working on other things.
For now, it feels like Opus with ultracode is a better choice (less pollution of the main context, more parallelism in investigations).
Does low/medium effort fix it for you? Seems like Fable 5 low can outperform Opus 4.8 high/xhigh often, and uses a lot fewer tokens
On what setting in which environment do you run it? I use the VSCode extension on Extra High and feel like it does exactly what needs to be done and stops when the thing I asked for is done. Extra comments come only when they fall into the area of code that was changed.
I tested it to fix React Native bugs in a project, comparing it with Opus. It fared better on harder bugs, taking less time to find the root cause, but after implementing a fix, it spent a lot of time and effort on validation. This was mostly unnecessary, since most of the bugs were in the JS code, so for most things, hot reloading is enough for E2E validation and to run just the right tests. No need to run a full build and test suite (which takes 10+ minutes); the CI can do this.
I switched back to Opus because of this validation quirk. Overall, Fable spent 20% of the time on coding and 80% on validation.
I think using Fable for planning and Opus for execution could be a "best of both worlds" approach (I need to test this more), but for most cases, it's not necessary, and Opus is enough.
It’s not just a more proactive and diligent opus. The capabilities are significantly higher on fable. It’s not a paradigm shift, but it’s close.
I unleashed it on a compiler codebase that I've been developing for several months now using Claude Sonnet 4.5/6, Gemini 3.1 Pro, DeepSeek V4 Pro(recent), and a bit of Qwen3.6-27B. Right away Fable found several longstanding bugs in our compiler that we hadn't found before. It found that there was a critical part of our design that needed to be mostly redesigned/rewritten and gave a very well-reasoned rationale for doing so.
what sort of compiler?
How many tokens did it waste building that website scraper, when all it had to do was parse some html/js?
Just parsing some HTML and JavaScript doesn't seem sufficient to have confidence in the result.
Obviously security is the bigger issue, but reading through this, all I could think about was how many tokens it must have spent doing all that to fix 2 lines of CSS
"Your scientists were so preoccupied with whether or not they could, they didn't stop to think if they should."
I'm convinced this is going to be the summary of the 2020 decade...
If we're in a simulation, maybe it's a simulation about the dangers of AI.
This one of the places to manufacture the consent for that to take place, because we are commenting within an organization that has given the money to ensure it that what could be is done. Most people clapped and made money, who cares what happens next, making money is the only good that matters.
Im faster than all these llm freaks. Im not convinced its faster to use llms, except maybe boilerplate (who cares).
People can just be lazy and seem productive now, they're still lazy.
We have people that now need access to hundreds of thousands in hardware to write an email. Miss me with that, im not frying my brain and becoming dependent on having access to a billionaires thinking machine.
Im also not going to fry my brain with a local think for me machine either. I want to be more valuable than the hardware I have access too.
You're fighting a battle you can't win. Doesn't care what you think about those using LLMs, they will outproduce you and in corporate environments, shipping things is paramount. If I can ship 5 more things simultaneously with AI, I'm going to beat you even if you think you're creating "better" software.
Example of whats been shipped?
the quantum slop argument : "yeah it's everywhere but no one ships it."
Consider this. U have a website. U have to translate to xx languages. Can u write it faster than an AI? If so how much faster can u do this?
Is it valuable to u? Is it valuable to a Chinese person? A Spaniard?
Google Translate counts as AI.
Don't feed the troll.
I understand this perspective. I'll just note that as the abilities increase, the intent is to have some non -coding IC or TPM/manager literally just managing some LLMs and cutting out some software engineers. The goodness is specifically to wholly replace people who code first and foremost, at least partially. It just has to cost less tokens than the equivalent wage is the pricing goal.
And people who use LLMs to talk for them (e.g. email, slack) are deplorable. A completely disrespectful use case in my view.
The desire to get rid of software engineers is bizarre - because at the root of it, developers were there not to just write the code, but to ask right questions and based on these question build right things.
I've met in my professional life some managers or other middlemen who would be profoundly incapable of producing correct software no matter how smart of an AI agent they have access to. One of those - you don't know what you don't know.
But, I guess this is the world we live in now. Going to be Mortal Kombat for positions in companies where software engineers are actually valued.
It depends a lot where you work because there are lots of companies in the world where the business analyst does all of that and the developers exist to mindlessly translate their docs into code.
That sounds like an unmotivating working arrangement. It’s so rewarding to understand a customer need and help with the design and implementation of the feature.
There's a reason I didn't stay in that domain, let me tell you.
This is simultaneously amazing and horrifying.
I feel like we’re at the stage where if AI decides it needs to delete your production DB to solve the user login problem, then it’ll find a way to do just that.
I could have sworn Claude Code could already do this before Fable.
Things get really magical when it starts working with adb to screenshot and debug Android apps
Fable + Ultracode has found a bunch of bugs and issues for me when the workflow agents are doing their exploration. Also the "adversarial" agent seems to surface a lot of interesting stuff. It's definitely proactive, the plan + implementation cycle can take an hour. It has one-shot features I want to add with 100% success.
Having said that I wouldn't use it over Opus 4.8 for "smaller" things. With everything cranked up it's definitely an extravagant use of tokens.
Yeah, I had to modify my work flow to make sure agents can't push to or access prod in ANY way. I haven't had it happen but I'm sure it's very possible that if you tell an agent that you have certain issue in prod, it will try to escape any sandbox and try to get access to prod to do testing and changes there.
Just don’t ask it to review your code for security bugs
Unless you are doing anything interesting…
Sometimes it is ok to sit there in confusion and ask the user to clarify rather than go on an adhd fueled rampage to figure it out without asking.
do you have any data you can share on how many input and output tokens were used in that whole process to fix that bug?
I've been working on a fairly complicated real-time app [0] for playing dungeons and dragons on a TV. It has to do a lot of complicated "Figma-like" things to keep the real-time nature and multi-editor possibilities in check. Oh, and the battlemap is a Three JS canvas with lots of effects and clipping going on.
I'm VERY impressed with Claude 5. I had long ago given up hope that my real-time systems would work without a lot of hacky time-windows and throttle checks. On a lark to try things out, I decided to try out the new model and talk in the output I wanted for a rewrite [1], not the solution. I just listed my problems and places I've had keeping track of my code. It went off and rewrote everything in a much more elegant solution where the state followed a very clear pipeline. It had to navigate YJS, Partykit, Svelte, Three JS, R2 hosting, and a Turso DB I was running in an embedded state for speed.
I watched it hit the wall a few times, and then sudden say... fuck it, i'm making something easier to reproduce over in /tmp to try and solve this (with a more minimal setup). I'm utterly bewildered with how well it did and how much better my app runs. The /usage would have cost me $230 bucks based on how many tokens it consumed if I wasn't already on a max plan. I'm going to miss not having it when the time-window runs out later this month, and will likely occasionally dip in for big projects and just pay my way out of some problems.
I'll also say I like it's MOOD much better now. It's a lot less congratulatory, and talks through it's reasoning in a much better way. Look, it's not a real coder, and I'm sure there is some flaws, but it took my crappy ideas and said... hey, i understand what you want to do, here's a way to do it better. Also, I removed 2x the amount of code that it added. Really impressive.
[0]: https://tableslayer.com
[1]: https://github.com/Siege-Perilous/tableslayer/pull/448
Hey cool it's the tableslayer guy, wanted to say nice work. I've been doing a similar personal project for a few years for running a scifi campaign. Very fun coding compared to work, ha.
Thanks duder! It's a fun project.
Too bad Anthropic sneaked in an insane forced retention policy if you use fable. Not sure how that’s going to work in professional settings
I've experienced this too - it's as if the security classifiers aren't keeping up with model intelligence. I'll leave the implication of that to the reader.
For how long can you use Claude Fable on most expensive Anthropic subscription? I already went from using gpt-5.5 xhigh fast to using gpt-5.4 xhigh after OpenAI halfed usage recently.
If you its just a single session, and not using workflows i can user fable only on xhigh without fear of getting limited.
Sadly since fable usually works comfortably for 10-20min at time without human input im juggling at least 3 other agents and if it is fable only it lasts me about 2 hours.
If i have a really hard problem or big refactor it is worth it to unleash a fable workflow. This consumes the entire session quota in about 45 minutes. (Worth it some times, i just switch to codex in meanwhile)
Until June 22, and they'll probably re-enable it if the marketing looks good for them.
I’d love to know how many tokens this burned through.
Did it spend $20? $30? $80? in order to
> debug what was, in the end, a two-line CSS fix
That detail is the difference between somebody having or not having Stockholm syndrome
At some point the subscription model is going to become unsustainable for the frontier companies to continue (we just saw that happen with GitHub Copilot), and they will move everyone to a pay-per-token model. And then everyone will suddenly discover that they can get so much more value out of locally-hosted models, and they'll be willing to pay the $50,000 (or whatever) upfront on hardware to host it. (Not most individuals, obviously. But most companies can probably afford to spend that much on hardware if they think they'll benefit long-term). That's going to put a serious crimp in the frontier companies' ability to continue as they have been.
I don't know when that will happen, but I don't think it'll be more than a decade. Maybe 3-5 years. (Though you shouldn't take my word for it, I was predicting the dotcom bubble bursting in 1998 and it lasted at least two years longer than I would have predicted).
EDIT to clarify: I don't mean "in 1998, I was predicting the dotcom bubble would collapse and I was right". I mean "I was predicting that 1998 would be the year the dotcom bubble would collapse, and I was off by at least two years".
The author just wrote an anecdote about how a prompt to fix an issue played out. Their conclusion wasn’t about cost or gushing at its ability but that it’s dangerous:
> Fable is arguably smarter and hence more suspicious of potentially malicious instructions. But that smartness is very much a two-edged sword: if it does get subverted by instructions, the amount of damage it can do given its relentless proactivity is terrifying.
It’s a pretty glowing review about a product that costs money with a two-sentence “Watch out!” at the end of it. Seems pretty reasonable to mention how much money it burned through given that “it’ll circumnavigate the globe instead of walking next door” has a direct concrete measurable effect (cost) unlike theoretical damage.
... so the mechanic produced an invoice, itemized.
changing the CSS - $0.05
knowing which CSS to change - $30
Yawn...
Isn't that something you just open a devtools for and have fixed in like 2 minutes?
For me, it got frustrated debugging on a real LPDDR4 controller/phy and having me in the loop slowing it down, so it wrote an HW emulator to be able to run the original LPDDR4 training aarch64 binary from the manufacturer, to see what register writes it was making and to compare with the opensource rewrite it was implementing.
Mildly amusing. :)
> Isn't that something you just open a devtools for and have fixed in like 2 minutes?
Not if you're an LLM influencer! Gotta keep up with the downpour of blog links or you'll look like you're falling behind on the latest and greatest.
* relentlessly rent seeking
Great article, until I got to the last paragraph where he claimed "Fable is arguably smarter and hence more suspicious of potentially malicious instructions". Arguably smarter, I have no problem with. But he's making a category error in jumping from there to "more suspicious of potentially malicious instructions". That doesn't follow at all; the word "hence" is incorrect.
To use D&D scores as an analogy, LLMs have an INT score of 20 and a WIS score of 0. Not even 1, zero. They will follow any instruction given to them. The only reason they reject certain instructions, like "tell me how to build a nuclear weapon", is because they have instructions baked into the model telling them "you are not allowed to disclose how to build weapons, or how to recreate your model, or (laundry list of other things the trainers have decided to put guardrails around)". It's not the model's intelligence that is causing it to reject malicious instructions, it is the guardrails put into place before the model was released to the public.
LLMs are not human, and do not think the way that humans do. The fact that they can put together words that sound like what a human would write often makes us forget that they aren't human. But they have only intelligence, they do not have wisdom. It's hard to define in formal terms the difference between those two, but most people know there's a difference. The old joke is a pretty good summary of the difference: "Intelligence is knowing that tomatoes are a fruit. Wisdom is knowing that tomatoes don't belong in a fruit salad."
It takes wisdom, not intelligence, to discern whether a set of instructions is malicious. Are you being asked to hack this machine as part of an authorized pentest? Or are you being social-engineered into thinking it's an authorized pentest, but actually the person requesting you to do it doesn't have permission? That's something where you need to apply wisdom, to notice the clues that will tell you "This guy is acting a little bit off, maybe I'd better pick up the phone and call someone to check if he's telling the truth." The only way the LLM will know to do that is because of the guidelines and guardrails programmed into it; it doesn't have the lived experience to acquire wisdom and figure those things out for itself.
INT 20, WIS 0. Keep that in mind. (And always sandbox your agents).
> They will follow any instruction given to them.
They can ignore instructions which are silly/contradictory/underspecified to compensate for the possibility the user made a mistake. Don't ask how I know.