I mean, you could make a better comment about it, but in my opinion the sarcasm is justified.

AI has greatly increased the number of security bugs found on a weekly basis (which is great) and we're getting one of those one-shotted and then immediately abandoned open source "projects" every day (which is useless).

And yet there is no indication that any of this new software development capacity is going into improving the quality and efficiency of the software we use on a daily basis.

Why is widely used professional software not getting better and more efficient if bug fixing is supposedly so much cheaper now? Is it not worth putting any effort into optimisation at all?

I think the reason could be that AI can only do more of what we have done manually before, i.e. more lowest common denominator code.

Or am I just too impatient and this is all coming?

> Or am I just too impatient and this is all coming?

I doubt its coming, at least not within the timescale OpenAI or Anthropic would like to believe. If we were close, then we'd see the fruits of that, which like you said, we are seeing the opposite currently.

The bottleneck was never writing code, and it still isn't. Writing code is like 15% of the job, but the labs can't tell investors "Yeah we make everyone only 15% more efficient" and still be able to raise trillions in capital. Whatever AI accelerates, the bottleneck is still code review, comprehension, and security debt.

Vibe coded slop gets abandoned because non-devs were never going to be able to use AI to make commercial software beyond an MVP. Once your app needs multi-tenant auth, session invalidation, concurrency handling, API changes, graceful degradation under load, etc. natural language prompts will fail. You still need a mental model of how things work.

When building a house, lowering the cost of bricks and getting them delivered faster does nothing to speed up the rest of the process that still relies on engineering discipline.