To be honest I don’t believe this is the case. Admittedly, I don’t have any experience with the best of the best models, only up to clause Opus. AI accelerates coding for myself a hell of a lot, but frankly the amount of time I spend coding complex programs feels about the same. I think there’s still a bottleneck, and it has been reiterated here before: judgement, testing, and understanding. If AI really accelerated coding, no amount of cultural inertia would be able to hold it back. It’s just not.

I was about to say something similar. The article’s premise is solid as long as we accept the assumption that AI is actually fundamentally changing the velocity and methodology of coding.

To me, so far it seems like it is and it isn’t simultaneously. Some things are going at insane paces. I see things like reverse engineering and emulation breaking barriers. But we don’t see things like the quality and complexity of highly architected systems getting much better, maybe even getting worse as management pushes velocity onto employees.

I think what this shows is that AI is great at tedium and brute forcing, but it’s not actually good at making substantially better software with less of that “rationed” expertise. At least, not yet.

All this talk about removing bottlenecks at all costs, and we haven't even considered the final boss of bottlenecks: the end users themselves. All the gains will be a waste if the end users have a choice. And as "The Goal" has taught us, we must remove the further-most bottlenecks first. Hence, we must remove all choice and power from end-users first.

Tell me I'm wrong.