As I understand, this would require somehow “saving the state” of the LLM, as it exists after the last prompt — since I don’t think the LLM can arrive at the same state by just being fed the code it has written.
As I understand, this would require somehow “saving the state” of the LLM, as it exists after the last prompt — since I don’t think the LLM can arrive at the same state by just being fed the code it has written.
As it turns out, you don't really need to "save the state"; with decent-enough code and documentation (both of which the LLM can write), it can figure out what needs to be done and go from there. This is obviously not perfect - and a human developer with a working memory could get to the problem faster - but its reorientation process is fast enough that you generally don't have to worry about it.
[0]: https://news.ycombinator.com/item?id=46005813 [1]: https://github.com/philpax/perchance-interpreter/pulls?q=is%...
I've found it perfectly capable of adding eg new entities and forms to existing CRUD apps.