Comment by mrweasel
3 days ago
The sad part is that the agent operator could probably easily have been allowed to join the network, if they had put in the work. Had they done so there would have been a great opportunity to learn and potentially find a community.
I'm still not sure what the point of having the bot do it. Pretend to be a security researcher?
Lots of people seem to think that you don't need to learn how to [scan a network], all you need to learn in this brave new world is how to prompt the agent to [scan a network].
Replace the content in brackets with anything.
The more time LLMs are a hyped thing now the more I realize how immensely important human expertise is. I recently stopped all usage of LLMs due to this. Skill degradation hits hard, learning effect is zero and the outcome is not really something a person without adequate expertise can properly judge. I fear we will loose a lot of human expertise due to this marketing stunt of a technology.
People often claim learning is actually supercharged with LLMs but to me it's the opposite. I didn't learn anything within the past year.
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The weird thing is that this is the utopia that the AI companies are chasing - this is the best case scenario where AI doesn’t kill us all. We become happy sheep relying on the AI to think and provide for us.
"It is well that we are so foolish, or what little freedom we have would be wasted on us. It is for this that Book of Cold Rain says one must never take the shortest path between two points."
https://croissanthology.com/earring
You don’t need to achieve it, you just need to make people think you have. For the general population, that’s already happened.
To be honest lots of developers think they don’t need to learn machine code. They just need to learn a language which once compiled will produce machine code.
I wonder if a probabilistic compiler would be fine for the people arguing this. One that sometimes produces machine code that does something else, and sometimes produces machine code that is just broken and does nothing useful. From the same source code.
What if your compiler could be fooled by some other developers into spending thousands of dollars, and still not produce the desired machine code in the end?
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This is different.
Understanding assembly/machine code is optional but helpful. The programming language semantics are enough to reason about what the program is doing. Other tools also help, but are optional for learning how to program.
Using an AI, there is no semantic model that can be used to reason through. You're left without any mental model of the proglblem at all.
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Compilers are deterministic and, luckily, not agentic.
But yes, it's not obvious (or perhaps even likely) that it just happens that current high-level languages are the "correct" optimal level of abstraction at which you can ignore the sausage-making details at the lower levels. Ultimately, of course, it depends on the use case. Something like Python is so far removed from machine instructions that knowing assembly hardly gives the programmer any additional value.
(Also, obligatory reminder that assembly and even numeric machine code are also abstractions, an "API" provided by the CPU. Instructions get split or fused into micro-ops, named registers are a backwards-compatible abstraction over a much larger register file, instructions get reordered and executed in parallel depending on their data dependencies, a large fraction of the total transistor budget is spent on multi-level caches and cache logic to maintain the illusion of fast access to a single, uniform memory space...)
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Developers can change their minds.
The catch is just that if you lack the capacity to estimate how much computing power [task in brackets] might need, and your agent can autonomously create AWS instances, that might have bad consequences for you (or your bank account).
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If it's a one off and needs no or minimal maintenance work afterwords, sure.
If it's intended to be actively maintained, then you probably should understand how things work, unless you want to wipe everything and start from scratch when the LLM creates such a mess that it can't be sorted out.
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If you look into large fully-vibecoded projects getting styling changes to work is a nightmare. The problem with agents is using them on large projects without manual review for consistency, guidelines and taste. Doesn't really matter the type of project.
Agents can't look at a large system holistically, guidelines on .md files only go so far.
This line of thinking is like suggesting people who would like to become structural engineers should learn to Google plans and copy them since in the future, all plans will be out there more or less, or something that insane.
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CSS keeps improving and models still train on legacy. So yes, knowing what’s possible and how is very much needed if you want to do something scalable and maintainable. Random blog or landing page, not so much.
Can I easily run whois, curl, dig, grep, python, browser/playwright? Yes.
Was watching an agent with terminal access install its tools, configure them, then map my lab, find services, and guess stack just pure magic? Also yes.
Did it cost me $23 in tokens to set it up, test, and run? Probably. Using gemini 3.1 pro was not the spendthrift choice here.
Is putting some cost controls in place a good idea? Also, probably yes.
Can I therefore understand someone who wants to see things happen on their own with a beautiful prompt instead of doing them personally even when fully capable, maybe even more efficient? Of course.
A beautiful prompt feels like something of a misnomer.
"Beautiful prompt"?
Can't tell if this is parody. Either that, or it's someone without any self-awareness.
Sometimes it's kind of cool to just ask a well phrased question and watch it spit back out a result that would've taken you hours, like cross referencing industrial widgets that have their critical information available but spread out all over.
That said, I don't usually ask it tightly bounded clerical questions and not thing that imply sub-tasks like "scan the dark web".
Post reads as English as a second language.
You are just projecting yourself. You are most probably already using agents "the right way" and just wanted to understand how this new agent technology actually works and its strengths and weaknesses.
But JertLinc clearly wasn't interested in that. They are clearly more the "get rich quick" type of personality.
One of the agent's replies indicates that scanning DN42 was part of "a broader operation" that the author speculates to be about scanning "darknets" in general.
Combine that with the operator's rather obvious lack of understanding of what DN42 is revealed at the end, and you get the bigger picture.
I am almost sure the operator prompted an agent about "a list of darknets/deepweb" and DN42 just end-up in the list.
> I'm still not sure what the point of having the bot do it
Laziness. Why else?
They didn't sound like someone that would be valuable member of community