@fasterandworse @dgerard I mean, it is absurd. But it is how it works: an LLM is a black box from a programming perspective, and you cannot directly control what it will output.
So you resort to pre-weighting certain keywords in the hope that it will nudge the system far enough in your desired direction.
There is no separation between code (what the provider wants it to do) and data (user inputs to operate on) in this application 🥴

simply ask the word generator machine to generate better words, smh

this is actually the most laughable/annoying thing to me. it betrays such a comprehensive lack of understanding of what LLMs do and what "prompting" even is. you're not giving instructions to an agent, you are feeding a list of words to prefix to the output of a word predictor

in my personal experiments with offline models, using something like "below is a transcript of a chat log with XYZ" as a prompt instead of "You are XYZ" immediately gives much better results. not good results, but better

It is absurd. It's just throwing words at it and hoping whatever area of the vector database it starts generating words from makes sense in response.

@fasterandworse @dgerard I am pretty sure I have seen programming the computer in plain English used as a selling point for various products since the 1970s at least

the best part is that most of these products are ex-products

"controls" is way too generous