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Claude Fable is relentlessly proactive

simonwillison.net

431–440 of 748 posts

Re: Claude Fable is relentlessly proactive

#431
post #279
post #233

Earlier quoted context omitted.

You’ve picked an interesting example, as driving a car, even with all safety precautions, is pretty much the most dangerous activity we do on a daily basis. Yet somehow we decide that the benefits outweigh the risks.

In case of driving the stakes are equally high for everyone on the road. Can we say the same for an agent? Having an agent is like forever having a genius intern who'll almost always do the perfect job for you. But there is non-zero chance that they'll also come up with quirky solutions and execute those with confidence and no follow-ups. You don't grant the intern production access and hope they check with you. I do…

> In case of driving the stakes are equally high for everyone on the road

The stakes are significantly higher for everyone outside a car. This seems like a pretty good metaphor for slop bombing people who don't use AI. People drive because they don't feel safe around everyone driving. People slop bomb because they can't handle all the slop.

Re: Claude Fable is relentlessly proactive

#432
> 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

This is why I always run code agents inside containers (Apple containers specifically, for better hypervisor-level isolation)

This is my OSS project to manage said containers and agents: https://github.com/prettysmartdev/awman

Re: Claude Fable is relentlessly proactive

#433
post #279
post #233

Earlier quoted context omitted.

You’ve picked an interesting example, as driving a car, even with all safety precautions, is pretty much the most dangerous activity we do on a daily basis. Yet somehow we decide that the benefits outweigh the risks.

In case of driving the stakes are equally high for everyone on the road. Can we say the same for an agent? Having an agent is like forever having a genius intern who'll almost always do the perfect job for you. But there is non-zero chance that they'll also come up with quirky solutions and execute those with confidence and no follow-ups. You don't grant the intern production access and hope they check with you. I do…

I don’t think that’s really true of driving, pedestrians and cyclists are at a much higher risk of getting killed by a driver than a driver themself. There are huge negative externalities to driving

Re: Claude Fable is relentlessly proactive

#434

Earlier quoted context omitted.

> Car lobby certainly accelerated the process, but car users were the main driving force. Not really. We know it’s not as much of a natural force as some would like it to be because there are places where the lobbies lost, and while cars are common and widespread they’re nowhere near as dominant as they are in, say, the USA. NJB’s next video (currently available on nebula) is about exactly that, Amsterdam’s (/ De Pij…

Isn't Not Just Bikes some US expat/biking maximalist? I'm not sure I'd take him as some neutral authority on the history of cars and driving in Europe.

> Isn't Not Just Bikes some US expat/biking maximalist?

You should really ponder the sanity of asking if a channel called “not just bikes” is a bike maximalist.

Re: Claude Fable is relentlessly proactive

#435
post #130

Earlier quoted context omitted.

I haven't yet had an agent rm -rf files. I've had one f up an account by placing 2000 limit orders at the wrong price, but that's another story.

I've had agents run `rm -rf`, but it's been on directories that did actually need to be removed. To a certain extent I think the existence of `rm -rf` as a command that runs blindly without any understanding of what it's deleting is the problem.

Yeah, spot on. I had an agent delete some files it shouldn't have as well, similarly to me making the same mistake. I think system prompts should default to using `trash` over `rm`. For now that's just in my AGENTS.md, and gets honored most of the time.

Re: Claude Fable is relentlessly proactive

#437
post #197

[flagged]

I'm kind of on the fence about it and have a similar feeling. I don't mean to undermine the effort he has put in over all the years. That's definitely commendable. But I have strong suspicions that he's becoming an AI influencer, with his own AI focused newsletter, so chances are major AI companies are approaching him. And also to be honest, I see far too many posts making it to the front page. @dang I trust in the m…

Most of my posts that make it on Hacker News weren't submitted by me. You can see who is submitting what on https://news.ycombinator.com/from?site=simonwillison.net - including a few that I submitted which got nowhere at all.

I accept paid sponsors for my blog (the banner at the top of each page) and newsletter (a clearly marked sponsored message at the top). I try to stay at arms length from those as much as I can - I want it to be very clear that sponsoring me will not result in me writing about a company.

Re: Claude Fable is relentlessly proactive

#438
post #399

Earlier quoted context omitted.

[flagged]

Here's a handy calculator you can use to estimate how much CO2 and water I wasted with my coding agent session: https://www.andymasley.com/visuals/ai-prompt-footprint/

Not sure what point you wanted to make, but this calculator is quite shocking. GPT 5.5 pro, with "a long document" and 10 requests a day gives 25% of daily CO2 emissions!

Ten coding sessions a day with Opus is still 4.7%!

This feels enormous. I will definitely stop rolling my eyes when people complain about AI CO/water usage...

Re: Claude Fable is relentlessly proactive

#439
post #393
post #342

Earlier quoted context omitted.

This is exactly right. By offloading this trivial task to the LLM, Simon has abandoned the opportunity to evaluate the abstraction with additional information and improve it. Instead, we let the agent spend $12 and make the fix while learning nothing.

Things I learned from this: - Fable will do a whole lot more than you might expect in order to verify a fix. I learned that it's "relentlessly proactive". That's a good title for a blog entry! - You can take screenshots of a window in macOS using the "screencapture" CLI command, but you'll need the integer window ID first. - That windowID is accessible via "Quartz.CGWindowListCopyWindowInfo(Quartz.kCGWindowListOption…

It's like saying you can learn so much about math from using SymPy to solve equations. Yes, you probably can. If you pay close attention to what is happening and can integrate the techniques being used into your knowledge.

But your learnings here are what, a handful of hacks? For most people it's like being shown the chain rule (which frankly, is more general than any of these learnings) without knowing what a derivative is. It's knowledge that comes context free. And even when it can be understood, I'm not sure I believe it gets integrated especially well when you did none of the work to understand it. If you are extremely diligent and self-aware about what your limitations are, and careful to be sure you have an understanding of this knowledge, sure I guess you can learn a lot.

And ultimately what do you think is more likely? People using the experience of using these tools to progress their knowledge or for them to rely on the answers uncritically? I think people with a rosy view about this are severely undercounting the problems associated with the trust relationship between a person and an LLM and what that means.

Re: Claude Fable is relentlessly proactive

#440
post #395

Earlier quoted context omitted.

My experience has been the exact opposite. As the models get better you need to know more about their capabilities, because otherwise you risk prompting Claude Fable 5 like it's GPT-4o and complaining loudly about how it's all hype and nothing about these models is improving at all (yes, I do see people say that.) Getting the best results out of these models requires skill, experience, intuition, and domain expertise…

Isn't the whole point of a better model that it should be better at understanding you than the previous one? So the same prompt should return a better answer. Prompting differently to the new model seems entirely backwards when trying to determine if the model has improved.

I think this is true when models were going from bad to pretty good like happened last year. But when they start to get good, and can work deeper and with more nuance, how you prompt also can change the results quite a bit. Note this is also true of asking smart humans to do things; personality and approaches vary, they don’t exist on a single axis continuum of quality
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