People have been developing neural networks since the 70's, and there's been two major hurdles to their usefulness for software development:

1. They require gigabytes to terabytes of training data.

2. A non-trivial percentage of output data is low confidence.

The first problem requires tens to hundreds of gigabytes of training data.

This first problem not only requires the slow but predictable increase in processing power and data storage capabilities that were unachievable until recently, but is also only possible because open-source software has majorly caught on, something that was hoped for but not a given early in AI development.

The second problem means that the output will be error prone, without significant procedural processing of the output data that is a lot of work to develop. I never would have thought that software writing by neural networks would be competitive, not because of effective error control, but because the entire field of software development would be so bad at what they do (https://xkcd.com/2030/) that error-prone output would be competitive.