I use it to brainstorm and prototype approaches to a problem. First, I'll ask it to give me an overview of the problem domain; this gives the LLM context. Then, I describe the problem and ask it to generate solutions, along with pros/cons of each approach. This is iterative: you might ask it questions, modify its suggestions, periodically summarize. After that, you can either ask it to give you code for a prototype or build it yourself.
These models are good for ideation, scaffolding, and prototypes. It's currently clumsy to fully build an app with an LLM, but they are quite useful for certain tasks.
Mostly machine learning pipelines, small react sites, and python CLIs. I've also used this framework for planning a schedule for my hobby project, getting advice for social predicaments, and optimizing the location of desk fans in my bedroom.
These models are good for ideation, scaffolding, and prototypes. It's currently clumsy to fully build an app with an LLM, but they are quite useful for certain tasks.