I must be using LLMs very differently than y'all, because I can't think of a single thing I would rely on an LLM that's "dumb as a stump" to do for me.
To me, LLMs are for asking research questions + exploring design spaces + pointing at codebases to investigate bugs. And those all benefit from the model being as "smart" (in terms of both fluid intelligence and burned-in knowledge) as possible.
I'm guessing there exist problems where "intelligence past a certain point" doesn't matter, so these medium-sized models can match the performance of the bigger models. But what problems might those be?
Things that are tedious but simple but I'm unfamiliar with.
"Go add a gh action to compile and deploy this thing and run its tests" is one I've found it's good at. Yes I know how to make a gh pipeline but it's always a hassle to remember what goes where.
Cranking out unit tests is okay. It's good at summarizing things so it's not half bad at writing jsdoc/xmldoc comments.