This one talks about understanding state is key to making effective decisions and automation abstracts that state away

> The other important aspect of cognitive skills in on-line decision making is that decisions are made within the context of the operator's knowledge of the current state of the process.

Basically, despite it being from 1983 and that a lot has been added to human factors research since then, it's short and well worth at least a skim

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Stop trying to upgrade disabled people's body when the problem is your design!
@WeirdWriter argues that the tech industry needs to stop trying to sell useless expensive gadgets no disabled person wants, or can afford, and start fixing actual accessibility barriers, like bad code, and poorly designed infrastructures.
sightlessscribbles.com/posts/d

#Accessibility #DisabilityDongle #FixYourHTML

huh, somehow I missed this while I was distracted with netbsd (thank you @techokami)

awful.systems/post/10050264/12

> Thanks for linking my toot, here’s another update since then: the same person that found the race condition also found that there was a performance regression on non-synthetic benchmarks. It went super fast on his little test but is complete dogshit when used in the real world! lwn.net/ml/all/atI0edrmeiRuRtN

the remarkable kernel patch that remarkably convinced linus torvalds to go all-in on LLMs, remarkably running into all of the reasons why this was a horrible fucking idea

anyone with an ounce of familiarity with how LLMs function could’ve seen this coming, but not kernel boy. why wouldn’t you slop up a feature and all of its tests and its documentation and then just go on vacation so someone else can try to clean up your mess?

How the world changed for me with GenAI code generation: from bad to mediocre code piling up slowly, to bad to, at best, mediocre code piling up 10x faster while the team's mental model of how the system they build and own works dissolves.

“Pangram is not an oracle • Buttondown”

buttondown.com/maiht3k/archive

> But as always, we have to be wary of any proposed technical solutions and evaluate them with care (including asking whether a technical solution is called for at all). This is again one of those cases where machine learning can easily create something that looks like a solution, but isn't, because it's easy to make a machine that gives “scores” for how likely some text is to be synthetic/authentic.

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