It's nice to see a wide array of discussions under this! Glad that I didn't give up on this thought and end up writing it down.
I want to stress that the main point of my article is not really about AI coding, it's about letting AI perform any arbitrary tasks reliably. Coding is an interesting one because it seems like it's a place where we can exploit structure and abstraction and approaches (like TDD) to make verification simpler - it's like spot-checking in places with a very low soundness error.
I'm encouraging people to look for tasks other than coding to see if we can find similar patterns. The more we can find these cost asymmetry (easier to verify than doing), the more we can harness AI's real potential.
In like fashion, when I start thinking of a programming statement (as a bad/rookie programmer) and an assistant completes my train of thought (as is default behaviour in VS Code for example), I get that same feeling that I did not grasp half the stuff I should've, but nevertheless I hit Ctrl-Return because it looks about right to me.
this is something one can look in further. it is really probabilistic checkable proofs underneath, and we are naturally looking for places where it needs to look right, and use that as a basis of assuming the work is done right.