Need to let loose a primal scream without collecting footnotes first? Have a sneer percolating in your system but not enough time/energy to make a whole post about it? Go forth and be mid: Welcome to the Stubsack, your first port of call for learning fresh Awful you’ll near-instantly regret.

Any awful.systems sub may be subsneered in this subthread, techtakes or no.

If your sneer seems higher quality than you thought, feel free to cut’n’paste it into its own post — there’s no quota for posting and the bar really isn’t that high.

The post Xitter web has spawned soo many “esoteric” right wing freaks, but there’s no appropriate sneer-space for them. I’m talking redscare-ish, reality challenged “culture critics” who write about everything but understand nothing. I’m talking about reply-guys who make the same 6 tweets about the same 3 subjects. They’re inescapable at this point, yet I don’t see them mocked (as much as they should be)

Like, there was one dude a while back who insisted that women couldn’t be surgeons because they didn’t believe in the moon or in stars? I think each and every one of these guys is uniquely fucked up and if I can’t escape them, I would love to sneer at them.

(Credit and/or blame to David Gerard for starting this.)

  • scruiser@awful.systems
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    3 days ago

    So this blog post was framed positively towards LLM’s and is too generous in accepting many of the claims around them, but even so, the end conclusions are pretty harsh on practical LLM agents: https://utkarshkanwat.com/writing/betting-against-agents/

    Basically, the author has tried extensively, in multiple projects, to make LLM agents work in various useful ways, but in practice:

    The dirty secret of every production agent system is that the AI is doing maybe 30% of the work. The other 70% is tool engineering: designing feedback interfaces, managing context efficiently, handling partial failures, and building recovery mechanisms that the AI can actually understand and use.

    The author strips down and simplifies and sanitizes everything going into the LLMs and then implements both automated checks and human confirmation on everything they put out. At that point it makes you question what value you are even getting out of the LLM. (The real answer, which the author only indirectly acknowledges, is attracting idiotic VC funding and upper management approval).

    Even as critcal as they are, the author doesn’t acknowledge a lot of the bigger problems. The API cost is a major expense and design constraint on the LLM agents they have made, but the author doesn’t acknowledge the prices are likely to rise dramatically once VC subsidization runs out.