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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.

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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?

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