Discussion summary
Fable is now API-only, affecting how users run it, with some using it in loops for tasks like bug fixing. There are mixed opinions on its performance and use cases, with some noting improvements and others expressing skepticism.
What the discussion says
- Fable's API-only design limits looping use cases.
- Some users report successful overnight runs fixing bugs.
- Concerns about performance and suitability for certain tasks.
- Discussion about Fable's subscription plans and changes.
“Fable changes the game yet again, because it's API-only.”
“I just had Fable run overnight in a loop, fixing bugs.”
Comments
Hacker News
You're not likely to want to run Fable in a loop any more than you want to take a bunch of dollar bills and light them on fire. Every invocation of Fable has to be intentional, its context carefully managed. I feel like a babysitter.
by zarzavat
> You're not likely to want to run Fable in a loop any more than you want to take a bunch of dollar bills and light them on fire. Every invocation of Fable has to be intentional, its context carefully managed.
Eh, that's just because it's the current frontier model. Give it a few weeks, and prices will drop.
by eru
Let's take this [1] benchmark. A bit more context here [2].
Here models are asked to create kernels for running inference on models. This is a benchmark perfectly suited and highly relevant right now. It's easily verifiable, an active are of research, and the results are immediately useful.
Say you have 1 unit of compute, it costs 300k $ and serves 1x users. In comes Fable and after one session it gives you 30% speed-up on your 1 unit of compute. It can now serve 1.3x users. How much is that one session worth for you? How much is it worth for a company using 10 units? 100 units? How much is it worth for a hyper-scaler running 10.000 units? How much is it worth for a lab that trains the next frontier model and then serves it from 100.000 units? 30% is relative. And the cost for one session is really meaningless. It can cost 1m$ / session and it would still be worth it for someone.
[1] - https://kernelbench.com/mega
[2] - https://x.com/elliotarledge/status/2072814573753975266
by NitpickLawyer
Anthropic says the change is about capacity and is temporary. In its launch announcement on June 9, 2026, it says:
"After this point—when sufficient capacity allows us to do so—we aim to restore Fable 5 as a standard part of subscription plans. We intend to do this as quickly as we can."by jacobgold
I wouldn't start with Fable - when I use burndown loops I tend to include instructions to document progress and set aside anything that turns out to be harder than expected, and solve the easy stuff first. When a model runs out of easy stuff and start struggling to make progress on what is left, I can let it keep churning on that - they get there eventually - or I can bump it up to a smarter model if one is available.
Opus had churned a week driving down spec failures, and did a great job. The 150 Fable took overnight were the ones Opus had kept putting aside.
by vidarh
by weird-eye-issue
by foobarbecue
by MomsAVoxell
by stingraycharles
by brcmthrowaway
by mock-possum
by martey
by skrebbel
by pluc
by dan-robertson
I work on large C++ applications used by international airlines. If this software failed, it would make national headlines.
Claude Code with Opus 4.8 is great at handling the boring code I don't want to write myself. It gets it right almost every time.
However I still review every change and test everything before committing.
Trust, but verify.
by deterministic
Even with it's issues, the latest models are going to disrupt the labor economics.
by cognitiveinline
by layer8
by baq
This blog is quite unreadable for 27/32" monitors.
by zapnuk
by layer8
by ornornor
by Aldipower
> If a company were shipping bugs at, say, a hundredth the rate we were at Centaur while relying primarily on review to catch bugs, then I could see their point, but that's not what's happening at the typical software company where people don't want to move away from human review [there might be non quality (as in non bug rate) related reasons to keep human review, such as keeping a high bar for code quality or keeping the codebase human-understandable, which pretty much immediately stops being the case if you let a fleet of agents go wild on a codebase] because of the perceived risk of shipping bugs.
I don't agree that the main point of a code review is quality assurance; there are other reasons that have more to do with team convergence and junior staff learning: https://www.embeddedrelated.com/showarticle/807.php
by jason_s
You should talk to https://www.mechanize.work/ for sponsorship/credits and about environments.
by gwern
I haven't even begun to try to comprehend how to use fuzzing testing to improve the ability to find bugs, but it sounds really interesting. I've seen mutation testing to be very useful for finding gaps in tests, so I can only imagine that fuzzing + LLMs might produce insane results.
by nasretdinov
That is a massive amount of information even if we are being sloppy with it. You can read The Hobbit and the first Harry Potter book cover-to-cover and still have room to spare. I would deeply struggle to develop a world model this detailed for any business. Anything that needs to get more specific than these narratives can be a SQL query tool into the data warehouse, grep over the codebase, MS graph API lookup, etc.
Giving the business a balanced way to collaborate over this one shared model of the world is a new challenge I am beginning to engage with. I've also noticed that the world model will compound on itself in terms of self-detection of update opportunities. The more constraints there are, the more likely we appear to violate one.
by bob1029
If only. There is a huge difference between "Gives good responses/can easily spot things within N context size" and "Technically works but sucks within N context size", almost all models basically become cave-people once you go beyond 50% of the "supported" context size, meaning while they may technically work with 1 million output tokens, those last 500K tokens are gonna be massively "dumber" than the first 500k tokens.
by embedding-shape
by stingraycharles
> In general, when I talk to software folks about testing, I'm coming from such a different place that they immediately look at me like I'm an alien, so let's talk about how we tested at this hardware company I worked for, Centaur, which informs my biases about how I like to work. Some of the things that we did that were or are unorthodox in the software world are:
> Hired dedicated QA / test engineers, with testing being a first-class career path on par with being a developer - No code review by default - Virtually no hand-written tests - Constant testing via what programmers sometimes called property based testing, randomized testing, fuzzing, etc., although we just called those tests (hand-written tests were called "hand tests"). - Large regeression test suite (3 months wall clock to execute on compute farm) - No unit tests
Anybody here tried that (or a similar) approach? Especially going all-in on property based testing and fuzzing with no unit tests.
I tried that approach somewhere before and the initial results were promising, but ran into political issues so the idea was canned.
by duckmysick
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- Hacker News
- Fable changes the game yet again, because it's API-only.
You're not likely to want to run Fable in a loop any more than you want to take a bunch of dollar bills and light them on fire. Every invocation of Fable has to be intentional, its context carefully managed. I feel like a babysitter.
by zarzavat - For now, I can use Fable from the web just fine.
> You're not likely to want to run Fable in a loop any more than you want to take a bunch of dollar bills and light them on fire. Every invocation of Fable has to be intentional, its context carefully managed.
Eh, that's just because it's the current frontier model. Give it a few weeks, and prices will drop.
by eru - I agree with you that you don't need fable for everything, and you have to be careful on what you run it on. CRUD stuff, sure even the small models can do it. But there certainly are tasks that are very much suited for the absolute SotA and you'd leave money on the table by not using it. And how much a task is worth is dependant on how much it improves your bottom line. So the cost/token becomes largely irrelevant.
Let's take this [1] benchmark. A bit more context here [2].
Here models are asked to create kernels for running inference on models. This is a benchmark perfectly suited and highly relevant right now. It's easily verifiable, an active are of research, and the results are immediately useful.
Say you have 1 unit of compute, it costs 300k $ and serves 1x users. In comes Fable and after one session it gives you 30% speed-up on your 1 unit of compute. It can now serve 1.3x users. How much is that one session worth for you? How much is it worth for a company using 10 units? 100 units? How much is it worth for a hyper-scaler running 10.000 units? How much is it worth for a lab that trains the next frontier model and then serves it from 100.000 units? 30% is relative. And the cost for one session is really meaningless. It can cost 1m$ / session and it would still be worth it for someone.
[1] - https://kernelbench.com/mega
[2] - https://x.com/elliotarledge/status/2072814573753975266
by NitpickLawyer - Fable is supposed to return to subscription plans, unless I'm missing something: https://jacob.gold/posts/fable-5-removal-is-temporary/
Anthropic says the change is about capacity and is temporary. In its launch announcement on June 9, 2026, it says: "After this point—when sufficient capacity allows us to do so—we aim to restore Fable 5 as a standard part of subscription plans. We intend to do this as quickly as we can."by jacobgold - I just had Fable run overnight in a loop, and it fixed ~150 compiler crashing bugs that Opus had kept deferring.
I wouldn't start with Fable - when I use burndown loops I tend to include instructions to document progress and set aside anything that turns out to be harder than expected, and solve the easy stuff first. When a model runs out of easy stuff and start struggling to make progress on what is left, I can let it keep churning on that - they get there eventually - or I can bump it up to a smarter model if one is available.
Opus had churned a week driving down spec failures, and did a great job. The 150 Fable took overnight were the ones Opus had kept putting aside.
by vidarh - Compared to Opus 4.8 I really haven't been impressedby weird-eye-issue
- It's "Galapagos" or "Galápagos," not "Galapogos."by foobarbecue
- He's not referring to the real islands, but rather the state of mind imposed upon existence on Vancouver Island.by MomsAVoxell
- You miswrote OP’s miswriting in the third version :)by stingraycharles
- This seems like the beginnings of AI psychosis, tbh.by brcmthrowaway
- How do you figure?by mock-possum
- OP's alt text makes it clear that by "Galapagos Island" they mean Vancouver. I assumed that this was some sort of local nickname, but all of the references to "Galápagos of Canada" I could find are talking about Haida Gwaii instead.by martey
- Yeah I was like “woa a PGConf on the galapagos, i gotta get my ass to one if those!”by skrebbel
- Nobody calls it that.by pluc
- I think it’s just a metaphor for being isolated from the wider tech community.by dan-robertson
- I've read a lot of comments about using AI for coding, and my experience has been very different.
I work on large C++ applications used by international airlines. If this software failed, it would make national headlines.
Claude Code with Opus 4.8 is great at handling the boring code I don't want to write myself. It gets it right almost every time.
However I still review every change and test everything before committing.
Trust, but verify.
by deterministic - It's really coming down to "Do we want to subscribe to a human with a salary of many ~$10000(s) ", or "Do we spend 100(s)$ on an AI subscription"
Even with it's issues, the latest models are going to disrupt the labor economics.
by cognitiveinline - On the other hand, you have many more humans to choose from than models, and they don’t change their character every few months.by layer8
- It’s going to even out on both eventually, the diffusion will be painful though.by baq
- There is a reasone we use left and right margin/padding.
This blog is quite unreadable for 27/32" monitors.
by zapnuk - There’s a reason not to maximize your browser windows. How do you handle HN threads on that monitor?by layer8
- The point of a wide monitor for me is to have two 720 wide windows side by side, not a single gigantic 1440 window with impossibly long lines.by ornornor
- Toggle to "reader view" or resize your window. It is up to you and really isn't that hard.by Aldipower
- Really interesting article but there's one thing I wanted to point out about the reasons for code review:
> If a company were shipping bugs at, say, a hundredth the rate we were at Centaur while relying primarily on review to catch bugs, then I could see their point, but that's not what's happening at the typical software company where people don't want to move away from human review [there might be non quality (as in non bug rate) related reasons to keep human review, such as keeping a high bar for code quality or keeping the codebase human-understandable, which pretty much immediately stops being the case if you let a fleet of agents go wild on a codebase] because of the perceived risk of shipping bugs.
I don't agree that the main point of a code review is quality assurance; there are other reasons that have more to do with team convergence and junior staff learning: https://www.embeddedrelated.com/showarticle/807.php
by jason_s - URL typo: "hange how he works](/productivity-velocity/)". (I make this kind of Markdown syntax error all the time and set up a lint for '](/'.)
You should talk to https://www.mechanize.work/ for sponsorship/credits and about environments.
by gwern - I can agree with Dan on two things: LLMs do often produce incorrect results and that it's still useful for productivity when used in moderation. For me the wrong results actually cause some kind of ragebait response so I become much more motivated to learn more about the subject to actually generate correct response. After I've learnt the subject area enough I find I'm better off having LLM review my code instead of writing it.
I haven't even begun to try to comprehend how to use fuzzing testing to improve the ability to find bugs, but it sounds really interesting. I've seen mutation testing to be very useful for finding gaps in tests, so I can only imagine that fuzzing + LLMs might produce insane results.
by nasretdinov - A lot of the crazy ideas seem to have melted away in the face of massive context sizes. Today, I can put roughly a megabyte of utf8 text into my system prompt before things start to get weird.
That is a massive amount of information even if we are being sloppy with it. You can read The Hobbit and the first Harry Potter book cover-to-cover and still have room to spare. I would deeply struggle to develop a world model this detailed for any business. Anything that needs to get more specific than these narratives can be a SQL query tool into the data warehouse, grep over the codebase, MS graph API lookup, etc.
Giving the business a balanced way to collaborate over this one shared model of the world is a new challenge I am beginning to engage with. I've also noticed that the world model will compound on itself in terms of self-detection of update opportunities. The more constraints there are, the more likely we appear to violate one.
by bob1029 - > melted away in the face of massive context sizes
If only. There is a huge difference between "Gives good responses/can easily spot things within N context size" and "Technically works but sucks within N context size", almost all models basically become cave-people once you go beyond 50% of the "supported" context size, meaning while they may technically work with 1 million output tokens, those last 500K tokens are gonna be massively "dumber" than the first 500k tokens.
by embedding-shape - You’re forgetting that keeping the context small is better economically and delivers better results.by stingraycharles
- I'd like to highlight a different part of the article:
> In general, when I talk to software folks about testing, I'm coming from such a different place that they immediately look at me like I'm an alien, so let's talk about how we tested at this hardware company I worked for, Centaur, which informs my biases about how I like to work. Some of the things that we did that were or are unorthodox in the software world are:
> Hired dedicated QA / test engineers, with testing being a first-class career path on par with being a developer - No code review by default - Virtually no hand-written tests - Constant testing via what programmers sometimes called property based testing, randomized testing, fuzzing, etc., although we just called those tests (hand-written tests were called "hand tests"). - Large regeression test suite (3 months wall clock to execute on compute farm) - No unit tests
Anybody here tried that (or a similar) approach? Especially going all-in on property based testing and fuzzing with no unit tests.
I tried that approach somewhere before and the initial results were promising, but ran into political issues so the idea was canned.
by duckmysick
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