GenAI Reimagined
A counterculture faces off against... something
It’s been a week since my initial flurry of posts, and it hasn’t been due to a lack of effort with research and writing. On the contrary, I’ve been exploring different angles in the hopes they might better illuminate what we — the great unwashed masses of skilled professionals — need to do to navigate a rapidly changing world.
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As I’m a data guy, my initial hopes were to find data that would tell a story. Not data that could be arm-wrestled into just supporting a narrative I’d pre-determined, but real data taken at face value and used to tease out some “ah hah” moments. While I found some interesting economic views on the human condition, none fit the bill.
I’ll skip a long backstory and sum up the research. The TL;DR according to the 2025 UBS Global Wealth Report (which examines 2024 data) is:
The top 1.6% of the adult population controls 48.1% of the wealth. These are people with a net wealth of $1 million USD and up. The overwhelming majority would be nearer the $1M level as the pyramid gets extremely narrow as you approach the tip.
The bottom 40.7% of the adult population controls 0.6% of the wealth. The net wealth per adult in the band is $10 thousand USD and down.
What I actually wanted was data showing the number of decision makers controlling the economic fate of a significant portion of the population so that I could then reason about how GenAI-motivated layoffs might play out. I gradually realized I was facing a level of effort comparable to writing a Master’s thesis. Someday perhaps, but not today.
The Step Back
This began with something that has nagged at me for awhile about GenAI. I couldn’t put a finger on it exactly, but it was starting to seem perhaps data wasn’t the leverage I was looking for. It was entirely possible I was hunting down a dynamic that data alone wouldn’t be good at capturing, or at least not yet.
I’ve been slinging a keyboard professional for a long time. Multiple decades, and that multiple is not the number “two.” I’ve seen many different technology transitions, and I’ve seen industry reactions to those transitions. Booms and busts, marketing hype and book publishing waves, software ports, environment migrations, second-system re-engineering efforts, and process overhauls galore. I’ve seen just about all there is to toss at the industry since we were stumbling around on early Unix workstations and the advent of PCs. GenAI isn’t like the waves I’ve seen before.
The light bulb moment, for me at least, came from deciding what wasn’t relevant to that nagging feeling.
It wasn’t about the technology. As technology complexity goes, LLMs barely rate. It is a simple technology concept done at extremely large scale. Sure, there is ongoing evolution and improvement, and now more mathematical examination of how training works and the parameter topologies that might induce, but I could list dozens, maybe hundreds, of examples in software and hardware that have much more subtle or complex characteristics once you set mere scale aside.
It wasn’t about the range of application. Every programming language compiler or runtime, every well-developed application framework, every expansive library ecosystem, collectively have massive range of application.
It wasn’t even the economics, although excluding that entirely didn’t seem quite right either. Not that the economics of the LLM doesn’t tell a story, but any rational person in this space knows the story is complex and very context-dependent. Have you seen the world around us? How often do people get truly moved by the complex and context-dependent? It’s the social kryptonite of the millennium.
What was left was… something else. And I think that something else slithered in under the cover of other stress factors in the economic and political zeitgeist.
More than any other technology-related event other than perhaps cryptocurrency, for some reason, GenAI has people “living in their feels.” I’m not saying people aren’t being intelligent about GenAI in either direction of the various debates. I’m pointing out that the volume knob on emotional energy is cranked up very, very high and that alone is an artifact worth taking note of.
It isn’t that we never see emotion in technology issues, but historically they have been confined to small camps. Camps that most of us, truth be told, learned to avoid or tune out because they were just so obviously annoying, over-the-top, and not productive in helping us with our work at hand. The more experienced in the technology space you are, usually the more jaded you get because you learn through experience that almost all problems can be approached with many choices of tools, plus employment environments typically bias the tool choice and you either get with the program or you get a different job.
What we have instead are very broad-based coalitions advocating GenAI as not only the “one true way” but further reinforced with the message that the world divides into camps that either “get it” or “don’t get it.” This is not really the history of engineering or technology as lived by practitioners, where experience has been “found a better wrench for times when a wrench is useful, but tomorrow I may need a saw.”
There is, however, a dynamic in history that does cleanly fit this particular emotion-laden pressure for change plus division versus conformity. The counterculture.
Hoping for Change
We hear language like this in periods when part of the population is pushing to opt out of the social framework that preceded them, because that framework is seen as no longer working or insufficiently flexible to address a changing world. From Wikipedia:
A counterculture is a culture whose values and norms of behavior differ substantially from those of mainstream society, sometimes diametrically opposed to mainstream cultural mores. A countercultural movement expresses the ethos and aspirations of a specific population during a well-defined era. When oppositional forces reach critical mass, countercultures can trigger dramatic cultural changes. Countercultures differ from subcultures.
For me this sidelines debates over matters like GenAI effectiveness, or when AGI will manifest, or if LLMs will provide the ultimate final AI model. None of those things may actually be what is going on. If you think about it, if you were halo-dropped into July 2025 without knowing anything that had happened in the last couple of years, those factors would all seem a strange focus for emotional energy. I think that’s because they aren’t what the emotional energy is about at all. It’s people struggling with the status quo, and concluding — at least subconsciously — the status quo is badly wanting.
This could explain why people of such diverse backgrounds can find themselves unifying energetically under a common technology banner. It isn’t about “oh I can be lazy, and make a gadget do that job for me.” It may simply be about seeing the novelty and potential power of a tool to extend a little hope, when the technology and large-corporation employment baseline was for many people already a system of slowly-shrinking economic hope and disempowerment. In this respect the cryptocurrency community, particularly Bitcoin “maximalists,” may find common cause.
It is a bit fluid what this common cause will face off against. Big tech? Wall Street generally? Wealth inequality in some less-specific way that doesn’t have a clearly defined opponent?
Ultimately, GenAI may not turn out to be the final solution for empowerment any more than most crypto efforts were… but perhaps both are the start of something much bigger because part of society has tasted a little hope, and demands more. If that is the legitimate backstory, then the challenge will be to avoid the usual Wall Street juggernaut co-opting any benefit before change can form solid roots in the lower portions of the wealth pyramid. The lower 98.4% could do with a little wind beneath their wings.
The Experimentalist : GenAI Reimagined © 2025 by Reid M. Pinchback is licensed under CC BY-SA 4.0