Curious whether the author is envisioning changing configuration of running code on the fly (which shouldn’t require an interpreted language)? Or whether they are referring to changing behavior on the fly?
Assuming the latter, and maybe setting the LLM aspect aside: is there any standard safe programming paradigm that would enable this? I’m aware of Erlang (message passing) and actor pattern systems, but interpreted languages like Python don’t seem to be ideal for these sorts of systems. I could be totally wrong here, just trying to imagine what the author is envisioning.
"Configuration" implies a preset, limited number of choices; dynamic languages allow you to rewrite the entire application in real time.
Interpretation isn’t strictly required, but I think runtimes that support hot-swap / reloadable boundaries (often via interpretation or JIT) make this much easier in practice.
So we generate one or many changesets (in series or in parallel) then iterate on one. We force the “chosen one” to be the one true codification of the spec + the other stuff we didn’t write down anywhere. Call it luck driven development.
But there’s another way.
If we keep starting fresh from the spec, but keep adding detail after detail, regenerating from scratch each time.. and the LLM has enough room in context to handle a detailed spec AND produce output, and the result is reasonably close to deterministic because the LLM makes “reasonable choices” for everything underspecified.. that’s a paradigm shift.
But without the need to “program” you can focus on the end user and better understand their needs - which is super exciting.
Every single documentation out there for new libs is AI generated and that is feed again into LLMs with MCP/Skills servers, the age of the RTFM gang is over sigh