Comment by timschmidt
1 month ago
I think there's a level above that where the words to describe such structure are familiar and readily available and hey guess what? The model understands those too. Just about every pattern has a name. Or a shape. Or an analog or metaphor in other languages or codebases. All work as descriptors.
This presumes that most of this stays encoded as words in our brains: the effort to translate some of these into words might be similar to translating it into code (still words, just very precise).
It's like talking legalese vs plain English; or formal logic vs English. Some people have the formal stuff come more naturally, and then spitting code out is not a burden.
No, it really doesn't presume anything about brains or information encoding. Just points out that there is a level of mastery in which all the techniques and all the forms have names or adequate descriptions. Teachers often attempt to achieve this, to facilitate education.
It's no accident there is an adage from Aristotle in the vein of: "Those who can, do. Those who understand, teach."
So yes, there is a level of mastery that is beyond being able to do a good job of designing and evolving complex systems which enables people to teach others the same skill set.
However, this is a smaller number of practitioners, and most have learned through practice and looking over how more experienced engineers apply their knowledge.
Where I disagree is that this means everybody is equally capable of teaching with words, or that there are no experts who are bad at teaching (humans or directing AI) — this clearly indicates it is not encoded as words for said experts.
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