We tend to think that markets reflect consumer choice. But the artificial-intelligence boom has been powered by the investment decisions of concentrated capital rather than by consumer demand.
What drives me up a fucking wall these days is how people will use AI to make a more “professional” message, then due to it’s verbosity it needs an AI to summarize on the receiving end.
Yet when I tell that to our marketing department they just complain about how it would be expensive to pay someone to do it themselves. You get what you pay for, except in this instance where ai is expensive and still bad.
There’s a balance here, and I definitely lean toward: make the “professional” message with all the possibly pertinent details, but also use the AI to summarize it to as short a summary as possible that hits the points I consider essential, and put that at the top with fair warning: excessive detail follows.
When using AI to generate documentation specifying things like how to build a piece of software, I say: go for the detail, but review for consistency. Detail beats ambiguity for LLM coding agents because if it’s ambiguous the agents tend to just make assumptions and keep rolling.
What drives me up a fucking wall these days is how people will use AI to make a more “professional” message, then due to it’s verbosity it needs an AI to summarize on the receiving end.
My attitude is if you put no effort into creating something then I will put no effort into consuming it.
My AI will talk to your AI.
Yet when I tell that to our marketing department they just complain about how it would be expensive to pay someone to do it themselves. You get what you pay for, except in this instance where ai is expensive and still bad.
I can tell when people use AI because it doesn’t sound professional. It’s not direct enough. It doesn’t get to the point and uses a lot of filler.
That’s also some of us before our stimulant medication kicks in. I swear to fuck, if I get called AI one more time…
It sounds like how students think professional sounds.
Well, also some executives that I can’t stand that, if I didn’t know better, would swear were ChatGPT for decades…
There’s a balance here, and I definitely lean toward: make the “professional” message with all the possibly pertinent details, but also use the AI to summarize it to as short a summary as possible that hits the points I consider essential, and put that at the top with fair warning: excessive detail follows.
When using AI to generate documentation specifying things like how to build a piece of software, I say: go for the detail, but review for consistency. Detail beats ambiguity for LLM coding agents because if it’s ambiguous the agents tend to just make assumptions and keep rolling.