nojs

This is not about admin rights, it’s about the agent leaking information it knows from its memories. Sandboxing won’t really help you.

I mean CF already forces 5 minutes of motorbike identification on anyone not in a whitelisted western country, so a small percentage of blind people is unlikely to worry them.

Not OP, but I’ve been nuked with downvotes for this several times too and tend to delete the dead comments. The slop is so prevalent that at this point it’s not a particularly interesting thing to say I think.

people said this would be too expensive

I imagine this is why the filter is so bad. Doing it with an intelligent model that better understands intent would be too expensive, currently.

Would you really write “Private video titles aren't just metadata”?

Just want to say I really enjoyed your writing style, it’s just the right amount of funny/witty without distracting from the (very interesting!) ideas.

all be it

fyi you probably mean “albeit”.

“tell my obnoxious boss to fuck off about the tps reports” isn’t a great career move for them though

that was a fantastic story, thanks

It’s in the image, designed to survive those kinds of operations

One solution I haven’t seen recommended much is to have a Claude instruction/skill that explicitly audits the diff of every upgrade, and force this manual audit as part of your upgrade workflow. This seems like it would work pretty reliably.

$300/day token quota

Are companies using per-token billing? Why - is there some reason they can’t buy the $200/mo Claude plan for every employee?

What about access to GPUs and memory? This is becoming a pretty major bottleneck.

Every week, somewhere between 1.2 and 3 million ChatGPT users, roughly the population of a small country, show signals of psychosis, mania, suicidal planning, or unhealthy emotional dependence on the model.

Why is mental-health crisis not a gating category, the kind where the conversation stops, full stop, and the user is routed to a human?

Well, obviously “routing to a human” is not feasible at that scale. And cold exiting the conversation is probably worse for the user than answering carefully.

Yeah, the solution given is actually wrong as stated!

This conflict is popping up everywhere. There is a push by a lot of companies to allow agentic use of their services (and new companies explicitly offering "X for agents"), ignoring the fact that "agent" means the same thing as "bot" which we've spent the last couple of decades actively filtering out. Will be interesting to see how it plays out.

Another vote for this - we’ve been using it for years without issues.

My working theory is that all models are approximately the same, and the variance in quality mostly depends on how long they think for.

So the trick is to always set to max, and then begin every task with “this is an extremely complex task, do not complete it without extensive deep thinking and research” or whatever.

You’re basically fighting a battle to make the model think more, against the defaults getting more and more nerfed to save costs.

Ads do not appear in accounts where someone tells us—or we predict—they are under 18.

Time to make a deal with the kids - i’ll verify you for instagram if you verify me for ChatGPT

hot MILFs in my area

https://youtu.be/FBSam25u8O4

this is super cool, well done

It’s 100% LLM text. HN really needs a button “flag as slop”.

That would be a sensible comparison if concrete was free

Oh it’s worse than that. This one ended up getting my account banned: https://github.com/anthropics/claude-code/issues/22284

Yes, worktrees with workmux.

I expected this to become less necessary over time as models got faster, but the opposite has happened. It feels like Claude has actually gotten slower (but in fairness does more per prompt), meaning worktrees are even more essential now.

It’s weirder than that. There is a surge of companies working on how to provide automated access to things like payments, email, signup flows, etc to *Claw.

There is no equivalent of the network effects seen at everything from Windows to Google Search to iOS to Instagram, where market share was self-reinforcing and no amount of money and effort was enough for someone else to to break in or catch up.

What is the network effect of Google Search?

The most common case would be defensive sentry logging that tracks unexpected LLM API call responses/parsing bugs, which are handled gracefully in the app (so not critical), but that i still want to know about to improve the prompts, response structures, cleaning code, etc.

Claude will typically resolve these in a surface level way when in practice they often require deeper changes (to prompts, routing to different model, more general cleaning code, etc) and it’s hard/impossible to have Claude do these without some input.

Other noise arises from Claude thinking related issues are unrelated and so solving them separately, and also just intermittent infrastructure type issues that are clearly transient being “solved” with some weird code change.

The argument is more like “humans always invent new things to want that are scarce”, and until AI literally replaces all human labour to the point of the marginal utility of a human being zero, this category will continue to exist.

it’s generally a poor marketing strategy to ignore explicit requests for list removal, because users manually flag the emails as spam which is catastrophic to your domain rep and will tank deliverability. the incentives are heavily in favour of removing people who unsubscribe