My take is that the argument boils down to saying that overfitting is a thing in LLMs too, but it comes in at the prompting phase. That's almost obviously correct, but I hadn't seen it voiced explicitly before.
The addition of "scam" in the title was a bit of hyperbole, which is probably responsible for a lot of the views and responses.
Anyway, it seems to have triggered a lot of very reactive and defensive takes, which isn't surprising but also isn't really necessary.
I feel like 'using rhetorical devices to get attention' is a pretty good definition of clickbait.
However, this is clearly trivially true, and it and doesn't mean that it may not be advantageous to map a problem from problem space to system parameter space. Hence, I fail to see how this would be a scam in general.
That's not what the argument is. The operative keyword in the argument is the word "sell", not the quantifiers themselves. If you're not "selling" it under that premise and you're open about the nuance, then it's not a scam.
Intentional or not, your representation of the argument is a scarecrow.
You might argue that this is semantics, but it's not. It's literally the point that is driving real execs desire to replace actual humans with GPT, right now.
The argument is that several technologies don't work 'out of the box' and you have to tweak their settings for each problem that you face, and that this means it's a scam. For example you have to change prompts in LLMs or change hyperparameters in other machine learning solutions. This argument is some combination of not insightful and not true.