241–250 of 748 posts
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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.
It's worse than gpt 5.5 xhigh
I’d say it’s overall better, but not universally better.
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
Yet another reminder to use Sandbox and Guardrails. Trusting model to be nice is not a good way.
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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 bu…
Have you tried adding this instruction to your agents.MD? Avoiding situations were the agent start running a loop is the main use case of the file for me
I asked Fable to digest some test logs to help me figure out a situation, but I had launched VSCode without activation the virtual env in the terminal first. Consequently, the tests failed to run.
And then:
Because the tests failed to run, Fable attempted to fix the test execution to no end, doing everything it could to get them to work. I had to stop it when it started to pollute my system with manual installs of packages.
At least I'm glad there's a guardrail to not circumvent or bypass sudo, because I'm convinced we would have ended up there.
A coworker made the joke that with enough tokens, Fable would try and solve any programming problem by building Linux from scratch.
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Yeah, you've exactly captured one of the main problems with the model being relentlessly proactive: it will happily burn like $5 of tokens to avoid asking the human to take a screenshot or click a button for it.
Honestly Claude straight up ignores my input sometimes, preferring to instead run commands for output and processing that and burning through a series of tokens when thinking hard about whether to ignore me. Like today, I told Claude exactly the name of the folder it had mistaken (it was supposed to be prod, not production), and it disregarded my input to then examine the directory itself. Small example of the kind o…
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
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A couple of months ago I was paying $200/month for Anthropic and $20/month for OpenAI. I decided to split it evenly to get full access to both of their offerings.
I've actually chosen not to sign up for their free plans for open source maintainers, because paying the regular subscription price feels more honest, given that I write about them so much.
I do have the free GitHub Copilot for open source maintainers deal - I've had that for years. Given how much code I have published on GitHub over the decades I feel less conflicted about that one.
I sometimes get preview access to models, which includes the ability to use them for free during the preview. That comes with a big catch though: I can't publish any of the code that I write using those previews while the model is still unreleased.
As a result I don't use those preview tokens much at all, because the vast majority of my work is open source and I don't want restrictions on when and where I publish the code I'm producing.
Am I the only one who slightly miss the pelican on a bike? It was a nice novelty... of course I could make one myself, but I became conditioned to expect one for every new model. Other than his great writing on AI, it became part of the package. Some small fun quirk to distract us from the non stop ping pong between the extremes of "omh are you still writing prompts you should use loops / 200k github stars, for a mar…
I posted the pelican a couple of days ago: https://simonwillison.net/2026/Jun/9/claude-fable-5/#and-som... It wasn't particularly noteworthy as pelicans go - in fact, given the strength of Fable, I see it as another signal that the pelican benchmark no longer has the unexplained predictive power of model capacity that it used to.
> 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 reckle…
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It seems that you've not worked out how to harness the LLM as a tool to improve your qualified knowledge and abilities in a domain, and have instead focused on whether or not its a crutch for lack of knowledge or laziness. When paired with your skill and knowledge, it is a force multiplier. You maintain control, the ability to direct, structure, strategise, and refine. That some are using it as the entire brain does…
Im not denying its usefulness for Q&A on docs/code as a search tool. Im talking about people who use it design and write their code, people who are offloading problem solving altogether, they aren't faster.
And make maximum use of it to learn as much as possible, while it lasts...