That's insightful how you connected the "comprehension debt" of LLM-generated code with the idea of programming as theory building.
I think this goes deeper than the activity of programming, and applies in general to the process of thinking and understanding.
LLM-generated content - writing and visual art also - is equivalent to the code, it's what people see on the surface as the end result. But unless a person is engaged in the production, to build the theory of what it means and how it works, to go through the details and bring it all into a whole, there is only superficial understanding.
Even when LLMs evolve to become more sophisticated so that it can perform this "theory building" by itself, what use is such artificial understanding without a human being in the loop? Well, it could be very useful and valuable, but eventually people may start losing the skill of understanding when it's more convenient to let the machine do the thinking.
That's insightful how you connected the "comprehension debt" of LLM-generated code with the idea of programming as theory building.
I think this goes deeper than the activity of programming, and applies in general to the process of thinking and understanding.
LLM-generated content - writing and visual art also - is equivalent to the code, it's what people see on the surface as the end result. But unless a person is engaged in the production, to build the theory of what it means and how it works, to go through the details and bring it all into a whole, there is only superficial understanding.
Even when LLMs evolve to become more sophisticated so that it can perform this "theory building" by itself, what use is such artificial understanding without a human being in the loop? Well, it could be very useful and valuable, but eventually people may start losing the skill of understanding when it's more convenient to let the machine do the thinking.