The only way I've found LLMs to be useful for building real software, which isn't included in your list of use cases, is for "pseudo boiler-plate". That is ther

The only way I've found LLMs to be useful for building real software, which isn't included in your list of use cases, is for "pseudo boiler-plate". That is there are some patterns that are tedious to write out, but not quite proper boiler-plate in the traditional sense, as so not as amenable to traditional solutions. One example I deal with frequently is creating Pytorch models. Any real model is absolutely not something you want to leave in the hands of an LLM since the entire point of modeling is to incorporate your own knowledge into the design. But there is a lot of tedium, and room for errors, in getting the initial model wiring setup. While, big picture, this isn't the 10x (or more) improvement that people like to imagine, I find in practice I personally get really stuck on the "boring parts". Reducing the time I spend on tedious stuff tends to have a pretty notable improvement in my overall flow.