I see two points:
1. AIs aren't yet good at architecture.
2. AIs aren't yet good at imagining technically exciting stuff to build.
And I agree that there's still space there to build a career in the short to medium term (plus Jevons Paradox). When both those points are no longer true we are certainly much closer to, dear I say it, agi. I suspect that (1) will be solved for somewhat limited domains in the near future using harnesses. And it could snowball from there.
Nearly every argument that hinges on the word "yet" is just an example of over-extrapolation[0] at play.
0: https://www.fallacyfiles.org/overxtra.html
But saying "LLMs are not good at architecture so software engineering has a bright future" is _also_ extrapolation.
Anyone who claims to know the correct strategy to be best positioned for the future is lying or misinformed. The most you can reasonably say is that for the moment an LLM in the hand of an non-expert or naive user is unlikely to produce high quality results or create an absurd boost in productivity. We can make reasoned decisions now and continue to monitor things.
It would be just as unwise to ignore the progression of LLM agents as it would be to over-index on them.
I think be both agree that the future of software engineering is very uncertain right now (and likely will be for years). For me personally that alone is enough to recommend not investing money and time to get into software engineering anymore.
Moreover we haven’t seen all the effects of today’s tech to understand the net benefits.
E.g ‘productivity’ is seemingly increasing but what is the effect on a firms financial position? It’s all speculative and experimental right now.
You're probably on point there.