Comment by roarcher

I feel like the dismissal of mental models is a direct consequence on the tech industry's manaical focus on scale and efficiency as the end-all be-all values to optimize.

Nevermind other important values like resilience, adaptability, reliability, and scrutability. An AI writes a function foo() that does a thing correctly; who has the know-how that can figure out if foo() kills batteries, or under what conditions it could contribute to an ARP storm or disk thrashing, or what implicit hardware requirements it has?

Hunter S. Thompson claimed to have re-typed The Great Gatsby because he wanted to know what it feels like to write a great novel.

Apparently, he actually meant this as a somewhat serious piece of writing advice, but I still prefer my initial reading of it as sarcasm.

I am suspicious of this argument, because it would imply that you can’t understand the design intent / tradeoffs / etc of code written by your own coworkers.

Which: of course you can. Not least because both your coworkers and these coding agents produce changes with explanatory comments on any lines for which the justification or logic is non-obvious; but also because — AI PR or otherwise — the PR consists of commits, and those commits have commit messages further explaining them. And — AI submitter or otherwise — you can interrogate the PR’s submitter in the PR’s associated discussion thread, asking the submitter to justify the decisions made, explain parts you’re suspicious of, etc.

When you think about it, presuming your average FOSS project with an open contribution model, a PR from an AI agent is going to be at least strictly more “knowable” than a “drive-by” PR by an external one-time contributor who doesn’t respond to discussion-thread messages. (And sure, that’s a low bar — but it’s one that the average accepted and merged contribution in many smaller projects doesn’t even clear!)