This is just a state of play issue. It's not good enough YET. On cost: 3.5 is 1/15th the cost, and a bunch faster though supports less context, so it's worth e

This is just a state of play issue. It's not good enough YET. On cost: 3.5 is 1/15th the cost, and a bunch faster though supports less context, so it's worth experimenting with which parts of tasks need GPT-4 and which need 3.5 (perhaps a feature where GPT-4 manages the main tasking / verification and 3.5 handles the individual small tasks - even if GPT has to be called 15 times to get the same result, this approach wins). On functionality: yeah, this is just some person's plaything. Reading the code it doesn't seem particularly well production grade (like many a python passion program). Something built similarly with a decent architecture (multi-agent + using an approach that automatically optimizes tasks) I can see this getting cheaper and better easily. Just like in software dev, where we write a spec, write a plan, write acceptance criteria, write code, write tests, run tests, iterate, Auto-GPT type software needs a similar framework to work within that is not just defined by the code, but by generalizing that to an architecture. https://github.com/daveshap/raven https://github.com/daveshap/raven is an interesting project exploring some of this.