Earlier quoted context omitted.
Software engineering as an occupation grew because of static analysis and GCs (literally why the labor market is the size that it is as we speak); the opposite appears to be the outcome of AI advances.
I'll take the other side of that bet. It's reasonable to expect that sometime relatively soon, AI will be a clear-cut aid to developer productivity. At the moment, I consider it a wash. Chatbots don't clearly save me time, but they clearly save me effort, which is a more important resource to conserve. Software is still heavily rate-limited by how much of it developers can write. Making it possible for them to write…
Hmm. We have very different experiences here. IME, the vast majority of industry work is understanding, tweaking, and integrating existing software. There is very little "software writing" as a percentage of the total time developers spend doing their jobs across industry. That is the collective myth the industry uses to make the job seem more appealing and creative than it is.
At least, this is my experience in the large FAANG type companies. We already have so much code. Just figuring out what that code does and what else to do with it constitutes the majority of the work. There is a huge legibility issue where relatively simple things are obstructed by the morass of complexity many layers deep. A huge additional fraction of time is spent on deployments and monitoring. A very small fraction of the work is creatively developing new software. For example, one person will creatively develop the interface and overall design for a new cloud service. The vast majority of work after that point is spent on integration, monitoring, testing, releases, and so on.
The largest task of AI here would be understanding what is going on at both the technical layer and the fuzzy human layer on top. If it can only do #1, then knowledge workers will still spend a lot of effort doing #2 and figuring out how to turn insights from #1 into cashflow.