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jdw64 • today at 5:57 PM • 1 reply • view on HN

In his book Programming as Theory Building, Peter Naur viewed programming not as the act of generating source code, but as the act of building a theory about the problem and its solution.

He said the lifecycle of a program ends when the development team is disbanded or when knowledge transfer fails to happen. But these days, people develop with AI. Will that knowledge actually remain? There's a slightly tircky point here

Of course, even in the past, once a codebase got big enough, everyone was writing code on top of an incomplete theory. But when you delegate work to AI, the theory itself isn't yours anymore, which makes it even trickier.


Replies

ajrouvoet • today at 6:28 PM

I’ve recently given a talk on R&D in the time of AI and based it on Naur’s essay for exactly that reason.

While it is in some sense harder, there are also opportunities, because the reach of a person is bigger and one can refactor more frequently to align with the theory being developed without the cost that used to be associated with this. AI is also effective for producing materials to teach the theory, increasing the chance that others can contribute coherently to a product.