You Are Using Fable 5.1 Wrong (Do This Instead) transcript

Fable 5.1 is the latest release from Anthropic, and it's one of the best models you can use right now. But, it doesn't behave the same way the previous models did, and there are a few small things you need to change in how you work with it. Because, if you use it the way you use the previous models, you're not using it to its full potential, and you might even get worse results out of it. For example, Anthropic says this model is best for long-running tasks, but it only does that well if you prompt it in a specific way.

And, there's one setting that Anthropic says to keep turned up, but it's actually making the results worse. If this is your first time, we're a software company, and this is our channel AI Labs. And, in this video, we're going to go over seven tips for getting the most out of Fable 5.1. But, before we go into those tips, there are some things we need to say about this new model first. With the release of Fable 5.1, Anthropic claimed this model is way better at finishing tasks, but Fable 5.1 isn't doing better work.

It's getting through more work for less money. We saw this on our own client projects. We gave Fable 5 and Fable 5.1 the same tasks and ran each one several times. We can't reveal the details of the projects, but Fable 5 did better work on most of the tasks, and Fable 5.1 was only better on one of them. That one was the hardest task of the lot, and on it Fable 5.1 did better work, finished around 40% faster, and cost well under half as much.

So, Fable 5.1 is stronger when the job gets harder. And, even on the tasks where its work wasn't better, it kept going. Fable 5 stopped before the end of some of its attempts, while Fable 5.1 finished every single one. It also costs less on every task. Now, you might already know that Claude code has a usage command that basically estimates what a session would have cost you if you were paying per use instead of on a subscription.

And, by that estimate, Fable 5.1 was around 47% cheaper than Fable 5. But, it isn't cheaper because the model suddenly uses fewer tokens. It's because the price of Anthropic changed. But, before we get to that price change, you need to know one thing. The The the task runs, the longer the conversation grows, and because of that, the model has to read more before it answers a new prompt. Models don't remember the conversation from one message to the next.

So, every time a model needs to give you another response, the whole conversation has to be sent to it again. But, instead of processing the same conversation from scratch each time, Claude keeps a saved copy of the parts it has already processed and reuses that copy the next time you prompt it. This is basically called a cached read. These cached reads also cost, but they are lower in price as compared to the usual input and output.

And with Fable 5.1, Anthropic cut the price of that by 75%. So, the conversation that gets sent again before each response now costs way less. That saving might look small on a single prompt because there isn't much conversation to send again, but on a long task, the same growing conversation is sent again and again, so the saving grows every time the model responds. Now, that only covers what the model reads. What the model writes is priced separately, and that price didn't change.

An artificial analysis, who test models and score them independently, found that Fable 5.1 wrote way more than Fable 5 did. So, the bill went up even with the cheaper reads. In their tests, it generated around 1.7 times more output than Fable 5 and cost about 20% more per task. Anthropic's Fable models have safety guardrails, which are rules that stop them from doing certain types of tasks. And with Fable 5.1, Anthropic says those guardrails interrupt Claude code sessions around 60% less often.

But, when it does hit one of those guardrails now, Claude code switches to a weaker model without telling you and keeps going. And that weaker model handles the rest of the session even when your next request has nothing to do with what triggered it. So, instead of a refusal, you get weaker work and think Fable 5.1 produced it. And this is already happened to someone building a game that had a joke file with the word biological in it.

The project had nothing to do with biology, but that one word was enough to switch the model handling the work. And if your project is actually about one of the subjects those guardrails cover, like security or biology, there's no setting and no way of wording it that avoids this. It's just something Fable 5.1 costs you. Now on Artificial Analysis is tests, Fable 5.1 scores higher than Fable 5 on accuracy, but it also hallucinates more, which is when a model doesn't know the answer, so it invents one and presents it as true.

When Fable 5.1 didn't know an answer, it hallucinated 72.6% of the time. Fable 5 did that 63.6% of the time. And a model saying it doesn't know is actually better than a model pretending to know everything because then you can go and check things yourself. But when it makes something up and you trust it because the model said so, that made up answer goes straight into your work. And that matters even more when you're using it for research or writing because verifying that becomes a whole task later on.

But before we move on to the tips, it would be great if you subscribe to the channel and hit the hype button. This small gesture of support goes a long way for us. Now after hearing these things, you're going to say that the older model is clearly better in some aspects. That is true, but at the same time it's going to become the default model in the apps that you use. This is why you need to follow the tips that we are going to talk about.

Otherwise, you're not going to get its full potential. Now the first way to actually use Fable 5.1 better is to turn down the effort. For those who don't know, effort is the setting that decides how much work the model does before it gives you an answer. And that one setting affects both the quality of the work and what it costs. Code Rabbit, who make a tool that reviews code, tested Fable 5.1 on their real review work and found that it caught 61% of the problems on low effort compared with 57.1% on high, and it finished around 3 minutes faster as well.

And we saw the same thing when we used Fable 5.1 to add a feature to our community website. On high effort, it spent a long time going back and forth on one part of the feature, while on low effort it finished the whole thing and gave us a better result. We recommended low effort in our previous Fable video as well, and after using Fable 5.1, that's still what we recommend. So, you should start with low effort and only turn it up if the result gives you a reason to.

Otherwise, you're spending time and tokens for very little in return. The next thing you need to do is remove the instructions you wrote for older models. Those instructions stay in your setup when you switch to Fable 5.1, even though the behavior they were fixing is gone. So, Fable 5.1 still has to follow a growing list of fixes for problems it doesn't have. They're just wasting your limit, and some of them now cause new problems.

We mentioned this in our previous video as well. Now, you might think, "How are you going to know which instruction is important and which is not?" You can test it by taking an instruction out of your Claude.md and giving Claude the same kind of work again. If the result is the same without it, that instruction doesn't need to be there. But, you don't need to do everything yourself. Claude code has a command called Claude API prompt audit that finds those instructions for you.

You need to run that command in the terminal, and it'll check everything you've saved for Claude. Then, it shows you which instructions were written for older models and gives you the exact changes it recommends. It doesn't change anything on its own, so you can review the list first and only approve the changes you agree with. But, before we move on to the next tip, let's have a word by our sponsor, Porkbun. So, you finally ship your app, but it's stuck on some random default URL, and what it really needs is a proper domain of its own.

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It just asks a question and waits, and when nobody's there to answer, waiting is the same as stopping. This happens because its usual behavior assumes you're working alongside it. So, Anthropic's prompting guide for Fable 5.1 says you need to tell it in the prompt that nobody's watching and that it should continue with anything already covered by your request as long as it can be undone. That gives the model permission to finish a long job without stopping for questions that don't need asking.

Fable 5.1 also has a habit of doing more work than you asked for. For example, if you ask it to add one feature, it may notice another problem nearby and fix that as well, or extend the feature beyond what you described. We saw this on one of our client projects where we asked it for a feature and it also edited the test files that nobody had asked it to touch them. The problem is that those extra edits can change parts of your product that you wanted left exactly as they were.

So, when you give Fable 5.1 a task, you should also tell it what to leave alone, which means it changes only what the request needs. And if it notices another problem, it mentions that at the end. And when we did that on our project and told it specifically not to edit the test files, it only worked on the feature we asked for. Fable 5.1 has another habit, and it happens whenever it changes files. When it's working on a task and only needs to edit a small part of a file, it rewrites the whole file instead, even though the rest of it doesn't change at all.

This might look fine to you because you're still getting the right result, But every one of those lines costs output tokens, and if it's working with a lot of files, it drains your limit much faster. We saw this on our own Second Brain, where every small change cost more than it should have because it kept rewriting files it could have just edited. To stop that, you need to tell Fable 5.1 that when a small change will give you the same result, it should edit just that part.

The next problem isn't how much Fable 5.1 writes, but how it writes. We already saw this with Opus 5, which used of what Anthropic calls mannered prose. For those who don't know, mannered prose is when the model uses fancy phrases and metaphors instead of just saying what it means. For example, instead of saying a setting is worth changing, the model calls it a dial worth turning. And in a long research task, that kind of language makes it hard to even see the point the model is trying to make.

Now, Fable 5.1 uses less of it than Opus 5 and Fable 5, and it also uses fewer stock phrases and less unexplained jargon. But the problem is still there in its writing. And compared with Fable 5, its sentences run longer with fewer paragraph breaks, which makes it even harder to follow. So, you just need to tell it to remove all mannered prose, and that fixes both. That's what we did when we ran it on one of our own research tasks, where we were using it for writing rather than building.

The last thing is what kind of work you give Fable 5.1. Everything we've covered so far is about getting more out of it, but the kind of job matters just as much because Fable 5.1 is at its best on the big ones. When we ran the tasks on our projects, Fable 5 actually did better work on the simplest task, but on the hardest one, Fable 5.1 did better work, and it finished around 40% faster and cost 58% less. So, the big jobs are where Fable 5.1 wins because that's where finishing the whole thing without stopping actually matters.

That's why you shouldn't break a feature into lots of small prompts and give it one step at a time. You should give it the whole feature and describe the result you want clearly, and then you'll see it finish the whole feature by itself. Now, if you want access to all the skills and workflows that we show you in our videos, you can get them in AI Labs Pro, which is our community. So, if you found value in what we do and want to support the channel, this is the best way to do it.

The link's in description. That brings us to the end of this video. If you'd like to support the channel and help us keep making videos like this, you can do so by using the Super Thanks button below. As always, thank you for watching and I'll see you in the next one.