Perhaps from the overhead of the language interface coupled with the ease of the expansion of the amount of 'stuff' you potentially need to read and internalise?
Human language can be wonderfully descriptive or terribly verbose as a way of communicating ideas. Writing everything out and being forced to externalise it is its own cost, which pays off only when the space of work to then do collapses with as little feedback as possible (and, ideally, with correct outcomes).
On the other hand the ease with which you can simply get back more text to process means the upfront language heavy interface is now just returning back more information to pull back into your internal model.
Which, for me at least, feels tiring, and stressful when doing language-heavy exploratory tasks that don't collapse or resolve neatly and simply give you back more decisions.
"And in tonight's news, the worldwide CRM solution Salesforce had a global outage affecting one hundred percent of its customer base. We interviewed users of the service to find out the scope of the impact. Everyone agreed that they were impacted, but strangely, nobody could describe _in what way_ they were affected."
Unfortunately YouTube captures the full set of extremes and everything in between, so I don't think it's fair to label the entire thing a cesspit of stupidity.
For every MrBeast there's a 3Blue1Brown. For every recycled clip from a well-known TV series uploaded purely to drive ad revenue for a bot-controlled channel there's a fine art restoration video showing a very niche process with a real, skilled human behind it.
Perhaps that company failed because it chose to port things to Rust and not because of Rust itself? Or any other number of reasons that survivorship bias might be mistaking.
I emphasised too much in that comment perhaps. I was going for because it chose to port things, meaning that maybe that company wasted time working on porting things instead of working on things needed to survive.
Human language can be wonderfully descriptive or terribly verbose as a way of communicating ideas. Writing everything out and being forced to externalise it is its own cost, which pays off only when the space of work to then do collapses with as little feedback as possible (and, ideally, with correct outcomes).
On the other hand the ease with which you can simply get back more text to process means the upfront language heavy interface is now just returning back more information to pull back into your internal model.
Which, for me at least, feels tiring, and stressful when doing language-heavy exploratory tasks that don't collapse or resolve neatly and simply give you back more decisions.
reply