One of the problems here is that things like this only count as "increased productivity" in the economic sense if it results in more income at the end of the funnel. Are you actually making more product faster in all your new-found free time?
Very few orgs I've worked in have actually been limited by the speed of programmers writing code. Usually it's communication overhead and management processes eating up most of the bandwidth - and those tend to expand to absorb any additional bandwidth.
Right, but are you delivering 3x more software now, and more importantly, are you selling 3x more software now?
This strikes me as a problem with how we define productivity in this context. If I can do my job in 1 hour, when it took me 8 before, am I not more productive in a rate-based sense? Sure, I might only work 5 hours in a week instead of 40, so my net production is the same, but my rate of productivity was certainly much higher.
It's like "work" meaning one thing to a normal person, but something very specific and counterintuitive in Newtonian physics (if you carry a fifty-pound weight in a circle and stop at your starting point, you've done no work).
So, if the product isn't selling any more expensive even though you're adding ~8 times more features, or if you're still getting paid for the full 40 hours even though you only really work 5, then economic productivity hasn't actually increased.
You've returned one of the most valuable resources (time) back to a human. In my mind there's simply nothing more valuable, and no sign of of efficiency more poignant than that.
The reason why it is very relevant is that, in the way we have unfortunately structured our economy, the amount of work you have to do to be able to eat and enjoy your time will always expand to grow to at least force you to maintain (if not increase) your economic productivity. That is, if AI enables engineers to deliver 10x more features in the same unit of time, then their employers will expect them to deliver 10x more features to continue earning their current pay.
So, while the AI did, in principle, allow you to just reduce your work schedule while getting the same pay, as you're providing the same results in 1/10th of the time, the economic system does not - your previous work is instead simply worth less than it used to be. Assuming you're not happy to take a 90% pay cut, you'll have to continue spending 40+ hour weeks, just using AI as well now.
Look at all the shit github README before llm. Most repos didn't bother because it was effort. those few that did, were because of autistic focus. Of those, very few were "great" user documentation.
now llms are here, the effort barrier is gone, and now we're inundated with shit README that provide no value to users nor respect their time.
Once you start applying SKILL.md that revolve around fixing HOW to communicate value to users in a way that respects their time, you'll see this story change in noticeable places.
I doubt it will change everywhere because it also requires that you give a shit about doing this in the first place, so those people Ed Zitron talks about... business idiots won't care, because they're ultimately nihlist.
The Principles of Scientific Management was just wrong that these ideas extend universally but we are still doing this stupid Barnesian performance as if they do. It clearly makes no sense with knowledge work. It is stupid.
Then the efficient market hypothesis provides a type of circular proof because since the market is always right, if this didn't work we wouldn't be doing it. Another stupid idea we are not able to get past.
This goes back before AI, with computers not being found to be improving productivity numbers: Solow's paradox.
* https://en.wikipedia.org/wiki/Productivity_paradox
* https://www.brookings.edu/articles/the-solow-productivity-pa...
For my job and basically everyone I know outside of programming, the productivity from AI is literally zero.
I think what this says is the productivity is in specific silos and why the experience of the utility of AI is so vastly different for different people.