People are doing this now. It's basically what skills.sh and its ilk are for -- to teach AIs how to do new things.

For example, my company makes a new framework, and we have a skill we can point an agent at. Using that skill, it can one-shot fairly complicated code using our framework.

The skill itself is pretty much just the documentation and some code examples.

Isn't the "skill" just stuff that gets put into the context? Usually with a level of indirection like "look at this file in this situation"?

How long can you keep adding novel things into the start of every session's context and get good performance, before it loses track of which parts of that context are relevant to what tasks?

IMO for working on large codebases sticking to "what the out of the box training does" is going to scale better for larger amounts of business logic than creating ever-more not-in-model-training context that has to be bootstrapped on every task. Every "here's an example to think about" is taking away from space that could be used by "here is the specific code I want modified."

The sort of framework you mention in a different reply - "No, it was created by our team of engineers over the last three years based on years of previous PhD research." - is likely a bit special, if you gain a lot of expressibility for the up-front cost, but this is very much not the common situation for in-house framework development, and could likely get even more rare over time with current trends.

The question is, who made the new framework? Was it vibe coded by someone who does not understand its code?

A framework is different than a paradigm shift or new language.