Comment by hansmayer

> Failure-prone stochastic ML systems produce testable, auditable code...

You're missing the bigger picture here. Yeah, they produce code. But "producing" code was never the bottleneck. Yes you can pop out a webapp within a couple of hours, but now you have no clue how it works, even if its a language and framework you are competent it in, because you skipped the part where you understand how the parts fit in together architecturally. So you wrote an elaborate spec, but the LLM "decides" to do something else. Maybe they don't make that PK autoincrement or they throw you in those nice empty "catch" blocks they ingested from various beginner tutorials, which will be very "helpful" when you application silently deviates from the happy path execution that you spec'ed the hell out of in your virulent spec-driven-workflow.. So it "kinda" works, it generates the code. It works the way your kid's toy car works - it "drives" but it cannot be driven to work, can it? So it does not work in the big picture. It's not a reliable enterprise ready system. It's a toy, and should be treated like one.