One of the arguments for open source software for end-users has always been the freedom to examine and modify how that software works. The reality for most people - even expert programmers - has been that the freedom is more about being able to lean on other people to do that. Most people can't justify the time commitment needed to read and then modify the code for tools they use very often. I think LLMs have changed…
> Several times a day I'll prompt regular Claude chat to "Clone x/y from GitHub and tell me how Z works".
Still highly dependant on one's access to SOTA AI models (availability and funding). Most people praising LLMs publicly for this sort of use case, are the ones with unlimited access to tokens / AI credits, or simply with a lot of money to burn.
But reality is that between using one's limited employer-sponsored quota of tokens to do their 9-5 business logic coding maintenance job, versus exploring 3rd-party software as end-users, I am sure of which one their managers will prefer.
I believe it will eventually happen, whether with SOTA local models on highly capable local hardware, or super cheap inference APIs... or both.