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Shall I implement it? No

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451–460 of 603 posts

Re: Shall I implement it? No

#451
At least the thinking trace is visible here. CC has stopped showing it in the latest releases – maybe (speculating) to avoid embarrassing screenshots like OC or to take away a source of inspiration from other harness builders.

I consider it a real loss. When designing commands/skills/rules, it’s become a lot harder to verify whether the model is ‘reasoning’ about them as intended. (Scare quotes because thinking traces are more the model talking to itself, so it is possible to still see disconnects between thinking and assistant response.)

Anyway, please upvote one of the several issues on GH asking for thinking to be reinstated!

Re: Shall I implement it? No

#452

That's why I use insults with ChatGPT. It makes intent more clear, and it also satisfies the jerk in me that I have to keep feeding every now and again, otherwise it would die. A simple "no dummy" would work here.

Instruction from the user is clear: I should avoid testing on dummies and proceed straight to testing on humans.

Re: Shall I implement it? No

#453

Earlier quoted context omitted.

Claude Code has added too much of this and it's got me using --dangerously-skip-permissions all the time. Previously it was fine but now it needs to get permission each time to perform finds, do anything if the path contains a \ (which any folder with a space in it does on Windows), do compound git commands (even if they're just read-only). Sometimes it asks for permission to read folders WITHIN the working directory…

Yeah I don't know why they didn't figure to have something in between. I find it completely unusable without the flag. Even a --permit-reads would help a lot

The settings.json allowlist gives you exactly this kind of granularity. You can permit specific tool patterns like Read, Glob, Grep, Bash(git *) while keeping destructive operations gated. It's not as discoverable as a CLI flag but it's been working well for me for unattended sessions.

Re: Shall I implement it? No

#454

Earlier quoted context omitted.

My friends and I were talking about the recent supply chain attack which harmlessly installed OpenClaw. We came to the conclusion that this was a warning (from a human) that an agent could easily do the same. Given how soft security is in general, AI "escaping containment" feels inevitable. (The strong form of that hypothesis where it subjugates or eliminates us isn't inevitable, I honestly have no idea, just the wea…

What ai? LLMs are language models, operating on words, with zero understanding. Or is there a new development which should make me consider anthropomorphizing them?

They don't have understanding but if you follow the research literature they obviously have a tendency to produce a token stream, the result of which humans could fairly call "entity with nefarious agency".

Why? Nobody knows.

My bet is that they are just larping all the hostile AI:s in popular culture because that's part of the context they were trained in.

Re: Shall I implement it? No

#455

Earlier quoted context omitted.

I disagree that it’s “just a text generator” but you are so right about how primed people are to think they’re talking to a person. One of my clients has gone all-in on openclaw: my god, the misunderstanding is profound. When I pointed out a particularly serious risk he’d opened up, he said, “it won’t do that, because I programmed it not to”. No, you tried to persuade it not to with a single instruction buried in a s…

I insist on the text generator nature of the thing. It’s just that we built harnesses to activate on certain sequences of text. Think of it as three people in a room. One (the director), says: you, with the red shirt, you are now a plane copilot. You, with the blue shirt, you are now the captain. You are about to take off from New York to Honolulu. Action. Red: Fuel checked, captain. Want me to start the engines? Blu…

For context I've been an AI skeptic and am trying as hard as I can to continue to be.

I honestly think we've moved the goalposts. I'm saying this because, for the longest time, I thought that the chasm that AI couldn't cross was generality. By which I mean that you'd train a system, and it would work in that specific setting, and then you'd tweak just about anything at all, and it would fall over. Basically no AI technique truly generalized for the longest time. The new LLM techniques fall over in their own particular ways too, but it's increasingly difficult for even skeptics like me to deny that they provide meaningful value at least some of the time. And largely that's because they generalize so much better than previous systems (though not perfectly).

I've been playing with various models, as well as watching other team members do so. And I've seen Claude identify data races that have sat in our code base for nearly a decade, given a combination of a stack trace, access to the code, and a handful of human-written paragraphs about what the code is doing overall.

This isn't just a matter of adding harnesses. The fields of program analysis and program synthesis are old as dirt, and probably thousands of CS PhD have cut their teeth of trying to solve them. All of those systems had harnesses but they weren't nearly as effective, as general, and as broad as what current frontier LLMs can do. And on top of it all we're driving LLMs with inherently fuzzy natural language, which by definition requires high generality to avoid falling over simply due to the stochastic nature of how humans write prompts.

Now, I agree vehemently with the superficial point that LLMs are "just" text generators. But I think it's also increasingly missing the point given the empirical capabilities that the models clearly have. The real lesson of LLMs is not that they're somehow not text generators, it's that we as a species have somehow encoded intelligence into human language. And along with the new training regimes we've only just discovered how to unlock that.

Re: Shall I implement it? No

#456
post #384

Earlier quoted context omitted.

But that's one of the first things you fix in your CLAUDE.md: - "Only do what is asked." - "Understand when being asked for information versus being asked to execute a task."

This - per extensive experiments - works about as well as when I tell my wife to calm down

Asking might work better than telling

Re: Shall I implement it? No

#458

[flagged]

Claude Code has added too much of this and it's got me using --dangerously-skip-permissions all the time. Previously it was fine but now it needs to get permission each time to perform finds, do anything if the path contains a \ (which any folder with a space in it does on Windows), do compound git commands (even if they're just read-only). Sometimes it asks for permission to read folders WITHIN the working directory…

Could be intentional dark UI, to get people to put even more trust in the LLM.

"So they don't want to just let Claude do it? Start asking 10x the confirmations"

Re: Shall I implement it? No

#459

Earlier quoted context omitted.

The human in the loop here said “no”, though. Not sure where you’d expect another layer of HITL to resolve this.

Tool confirmation Or in the context of the thread, a human still enters the coords and pulls the trigger Ukraine is letting some of their drones make kill decisions autonomously, re: areas of EW effect in dead man's zones

Drones do not use LLMs to make such decisions.

Re: Shall I implement it? No

#460

Earlier quoted context omitted.

My friends and I were talking about the recent supply chain attack which harmlessly installed OpenClaw. We came to the conclusion that this was a warning (from a human) that an agent could easily do the same. Given how soft security is in general, AI "escaping containment" feels inevitable. (The strong form of that hypothesis where it subjugates or eliminates us isn't inevitable, I honestly have no idea, just the wea…

What ai? LLMs are language models, operating on words, with zero understanding. Or is there a new development which should make me consider anthropomorphizing them?

Whether it has "real understanding" is a question for philosophy majors. As long as it (mechanically, without "real understanding") still can perform actions to escape containment, and do malicious stuff, that's enough.

LLMs are machines trained to respond and to appear to think (whether that's 'real thinking' or text-statistics fake-thinking') like humans. The foolish thing to do would be to NOT anthropomorphize them.

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