[cjf101]

Yes, absolutely. There's a lot of people moving in to capitalize on the space between what people imagine they can do with LLM's, and what is currently possible. The difficulty in estimating what the LLM is likely to do with an output, the actual randomness that is involved in getting there, and the variability of the output creates a situation where you might as well put up an "INSERT GRIFT HERE" sign.

Even this post (which I think is making some pretty well informed and intentioned suggestions) exists largely because getting exactly what you want out of an LLM can be pretty difficult. Even fairly static tasks like data extraction can have aggravatingly variable outputs. I don't think that most of these are the _right_ way to get to the goal but are rather, largely clever hacks that can help a user try and nudge the LLM towards the desired latent space when adjusting the instructions fails.