[wongarsu]

It's pretty fascinating to look at the impacts this has had in the last 2000 years, or even just the last 200.

Take construction work. Incredible improvements through power tools, gasoline-powered mobile cranes, etc. The productivity per worker has exploded. A lot of this has been captured by induced demand: we build bigger, taller, grander. But the improvements aren't distributed equally. Which means that crafts that haven't seen much improvement are now more expensive in comparison to everything else. Which has contributed to our buildings having less elaborate facades and becoming more "bland"

The same in clothing. Clothing has become dirt cheap. Even the poorest people can afford new clothing multiple times a year. But in the same transition we have gone from everything being custom tailored to most things only kind of fitting, being made for variations of the most common body shapes. Not necessarily because tailored clothing has become much more expensive (though higher labor costs from higher average productivity haven't helped), but because every other step has become cheaper and tailoring hasn't.

I wonder what we will say about the trajectory of software in a couple decades

[sally_glance]

That's a great angle - will handcrafted software of the future become the equivalent of a tailored suit today? One might argue it already is, most companies and individuals do just fine using cloud/SaaS offerings and COTS apps. So on first glance it seems like automating software engineering would mainly benefit exactly those providers. The other side of the coin is that it also allows for cheaper/faster in-house DIY solutions and competition.

[wongarsu]

Yeah, I could see a world where it swings exactly the opposite way for software. Writing software for yourself is becoming cheap, but gathering requirements, getting alignment between stakeholders or marketing your software isn't getting much cheaper. Maybe everyone will end up with their own in-house solution? Or maybe we end up with configurable SAP-like behemoths, but instead of an army of expensive consultants configuring the software for your use case you have AI agents taking that part

I'm sure whatever path this takes will seems obvious in hindsight