This reminds me a lot of AutoGPT and GPT-engineer and other "full automation" systems, only much more practical and reasonable. Like if I was going to try to m

This reminds me a lot of AutoGPT and GPT-engineer and other "full automation" systems, only much more practical and reasonable. Like if I was going to try to make one of those self-programming systems work I'd be focused on getting it to outline and specify components, then divide that work on components, maybe doing revision passes, think about the specification order, etc. Many of those steps are things programmers naturally do and are supported by modules and functions and tests... So phrasing the specification language as a programming language instead of a single prompt is pretty reasonable. That said, I'm not sure if this needs to be its own language? Could it be in Python directly? (I'm reminded of my own magic Python module: https://ianbicking.org/blog/2023/01/infinite-ai-array.html https://ianbicking.org/blog/2023/01/infinite-ai-array.html – though honestly I haven't touched it since writing it... too much magic makes something not really useful.) I think it would help if the development process was maybe more incremental. I don't really use REPLs because I find it hard to construct and maintain the REPL environment. But maybe those compromises are more reasonable given the unique challenges of AI-written code. Like maybe the AI should be building mocks from the beginning, kind of gentle placeholders that get thrown away quickly, but since the AI wrote the original code no one really cares. I guess I'm proposing processes (architectures?) of construction that are specific to AI. Maybe not entirely novel, but the result of looking holistically at the development experience and picking out ideas that allow for incremental confirmation and refinement. AI is often better at making changes and refinements than creating something from whole cloth.