My friend Markus Eisele put it in one line: code is cheap now, software isn’t. Until recently, both were expensive, so the gap stayed hidden. Now you just get to the expensive part faster.
Writing code was never the same thing as making software. The typing was always the cheap half, and the cheap half is the one that got cheaper.
Matt Pocock points to the other side: bad code is far more expensive today than it used to be. The reason is speed. The rate at which I can push bad code into production has no ceiling anymore. Whatever I used to get wrong once a sprint, I can now get wrong continuously.
Here is what I see day to day. AI does great work on a good codebase. Well structured, well written, documented, and it just flies. Working with it is a pleasure. On a bad codebase, it goes the other way and starts going nuts.
I once read Venkat Subramaniam stating the sharpest version of why. Developers say AI-generated code is bad. AI was trained on code written by developers. That, he says, is called karma. 🙂
So none of this is a new problem. We have been dealing with design, structure, and documentation for a very long time, and we already know what happens when they are missing. What changed is the clock. The same problems now arrive faster, and usually at a much bigger scale.
If you are running AI on a legacy codebase right now, I would like to hear which of the two you are getting: does it fly, or does it go nuts?