Most “AI is rubbish” takes treat it as an open-loop system: prompt → code → judgment. That’s not how development works. Even humans can’t read a spec, dump code, and ship it. Real work is closed-loop: test, compare to spec, refine, repeat. AI shines in that iterative feedback cycle, which is where these critiques miss the point.
What’s tough for me is figuring out where people are realizing significant improvements from this.
If you have to set up good tests [edit: and gather/generate good test data!] and get the spec hammered out in detail and well-described in writing, plus all the ancillary stuff like access to any systems you need, sign-offs from stakeholders… dude that’s more than 90% of the work, I’d say. I mean fuck, lots of places just skip half that and figure it out in the code as they go.
How’s this meaningfully speeding things up?