Is this perhaps why the hegemonic system of the capitalist state feels so *exhausted* and unable to tackle seemingly any problem, despite theoretically being able to mobilize vastly more resources than they were even a generation or two ago?
Powerful states, that previously won world wars against industrial peers, struggle to win wars against far weaker opponents. Wealthy governments struggle to afford infrastructure projects. Grand national undertakings belong to an increasingly mythic past.
It’s in this milieu that I interpret (easily foreseeable) results like this:
“In our in-progress research, we discovered that AI tools didn’t reduce work, they consistently intensified it.”
“For instance, engineers, in turn, spent more time reviewing, correcting, and guiding AI-generated or AI-assisted work produced by colleagues. These demands extended beyond formal code review. Engineers increasingly found themselves coaching colleagues who were ‘vibe-coding’ and finishing partially complete pull requests. This oversight often surfaced informally—in Slack threads or quick desk-side consultations—adding to engineers’ workloads.”
As a society, we have massively invested in generative “AI” in a desperate attempt to manage the increasing complexity of our lives (and to goose the wealth of a handful of tech barons), but the end result has been unprofitable slop and *more* work to fix the errors generated by these massively expensive systems.
I strongly suspect that generative “AI” represents the stage of decreasing returns to additional complexity—not just diminishing marginal returns but rather negative returns as we invest more resources into managing the fallout
https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it
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