What do you find important about this distinction? To me it's a description of the normative relationship between practitioners and broader society but I don't really see the significance you do.
Hillel Wayne wrote a really excellent well researched article about software engineering compared to other forms of engineering a few years ago. It necessarily goes into a lot of this stuff but what emerges is that these definitions are regulatory and historical debris.
You don't need medical board or a bar to certify or constrain professional behavior and those organizations may not constrain as much as you assume anyway. The reasons we do have those institutions is as much a matter of historical accident as any modern need for it, and the reasons we don't have it for other high impact fields is pretty much an accident too.
And in a lot of the world software engineering does have professional certification and standards of practice. They still ship adware and racist loan denial algorithms too.
If you have ever worked in almost any other industry your first question quickly answers itself. If you have never worked in an industry principally governed by ethical standards it would be challenging for me to describe it to you. I cannot give you what your perspective has never before imagined.
If they do, they're behind the curve. They don't matter anymore.
Systems design, architecture, database fundamentals, a bit of SRE. That matters. Not coding and syntax and toy problem solving with data structures and algorithms.
I think this is something where definitions and static roles might serve as a useful reference point. Is it really the case that the trillion-dollar frontier AI labs are behind the curve, and only some other group of people knows how to really leverage AI? It's not impossible - Nvidia employees aren't the best in the world at using their chips - but the hypothesis practically demands some analysis of who these clever curve-setters are and why we're hearing so much less about them than about Anthropic.
My own experience is that coding, syntax, and some kinds of toy problem solving are important skills to use AI coding tools most effectively. I routinely get PRs these days whose descriptions seem plausible but are clearly wrong from a glance at the code, and I've had times when I'm unable to communicate to someone why a PR is wrong because they're not able to form a sufficiently detailed mental model of what it's doing.
This makes sense, though. They have to be exceptionally confident in the performance of the product and work to continually improve its quality and efficiency. Many other companies can get by more just as consumers of it, but the makers of the product need some of the best coding skills available.
I just finished several months of interviewing and think that you must be projecting a bit. Every one of them included a coding interview with no AI use allowed.
Hillel Wayne wrote a really excellent well researched article about software engineering compared to other forms of engineering a few years ago. It necessarily goes into a lot of this stuff but what emerges is that these definitions are regulatory and historical debris.
You don't need medical board or a bar to certify or constrain professional behavior and those organizations may not constrain as much as you assume anyway. The reasons we do have those institutions is as much a matter of historical accident as any modern need for it, and the reasons we don't have it for other high impact fields is pretty much an accident too.
And in a lot of the world software engineering does have professional certification and standards of practice. They still ship adware and racist loan denial algorithms too.
https://www.hillelwayne.com/post/are-we-really-engineers/