Ah, interesting. I myself have made my own library to create callable "prompt functions" that prompt the model and validate the JSON outputs, which ensures type-safety and easy integration with normal code.

Lately, I've shifted more towards transforming ChatGPT's outputs. By orchestrating multiple prompts and adding human influence, I can obtain responses that ChatGPT alone likely wouldn't have come up with. Though, this has to be balanced with giving it the freedom to pursue a different thought process.