Software complexity grows superlinearly, if not exponentially as you add components. There are things an engineer can do to flatten the curve - that is OP's co

Software complexity grows superlinearly, if not exponentially as you add components. There are things an engineer can do to flatten the curve - that is OP's complexity management idea - but complexity growth can never be linear as long as you are adding to the software. I made a model/theorem for this that I posted on X: https://x.com/i/status/2027771813346820349 https://x.com/i/status/2027771813346820349 Code generation has exposed that verification is the central problem of software engineering. And I think it always has been. Defining what is "correct" can be hard enough, let alone building a system that lends itself to verification, let alone spending the time to verify. Releasing software and letting users find bugs is therefore a very efficient strategy, because it spreads the burden. But you have to ride the line between losing users and getting enough feedback to find and fix the bugs that matter. As we confront whether AI might take our jobs, I take some comfort in the idea that the world might be too complex for even the largest, best trained AI we can imagine. At a certain point, you need to simulate the whole world (or some substantial portion of it) and the cost/benefit of trying to do all that with compute may not be worth it versus using the real world (that is, humans) as your verifier.