A Foresight article puts AI and crypto side by side and asks what actually creates wealth. Its answer is blunt: efficiency is not the real cutoff. What matters is whether a technology rewires production relations.
The author says this question had already surfaced in a Sept. 16 article titled From Farming to the Dining Table: Will AI Change Your Compensation, or Your Status? Back then, the issue was put simply: when people learn AI tools, are they just trying to work better and faster, or are they trying to shift their position? Then the author read an article by Meng Yan and decided that earlier framework still stopped short.
Higher personal productivity does not mean the network will pay more
The article cites two passages attributed to Meng Yan. In the first, he says, "Modern society is a densely interconnected collaborative network. Each person is really responsible for only a tiny slice of the work. Aside from a very small number of people, most people are basically just routing resources within this network. As long as individual productivity meets the required standard, pushing it even higher does not bring any obvious gain to the system as a whole." That is, modern society works as a tightly packed collaborative network where each person handles only a small piece. Apart from a tiny minority, most people mainly act as resource routers inside that system, and once personal productivity clears the bar, more improvement does little for the network overall.
The second passage says, "So, as a node in a collaborative network, no matter how high your IQ is or how productive you are, the network does not actually need it and cannot really use it. In AI terms, that means your own work efficiency may double, but the network does not need your extra output. At most, you gain some free time, but your income will not increase. Most people start using AI and think, I'm amazing, my productivity has gone up N times, so I should become impressive very soon. In fact, you are overestimating the effect of that little bit of IQ and productivity. When that productivity boost is placed into the whole network, it does not have much value, and it cannot really be distributed." The article leans on this to make a sharp point: even if AI doubles someone's efficiency, the wider network may have no use for the extra output. Nice for free time, maybe. Not necessarily for pay.
According to the piece, those two passages lay out the link between individual productivity and the larger collaborative network. And they also help explain why many solo founders or small AI companies have not broken out as fast as so many people expected.
Inside an already formed production network, the author says, individual ability often matters less than people think. Plenty of workers already have more skill than their jobs really demand. So if AI pushes those abilities even higher, but the person stays in the same production network, that extra capability still may not produce meaningful incremental value. No extra value. No extra pay. Pretty simple.
Workers may use AI every day and still see no rise in income
The author points to employees at the author's own company. They are already using different AI tools in their daily work, the article says. They work faster than before. The output is better than before. But their salaries have not gone up. Some still worry that a weak macro environment could bring wage cuts or, later on, layoffs.
So the article asks a fair question: why do these people, who have felt AI's power firsthand, still not see AI as a source of wealth opportunity or as something that could change their social position? Instead, the piece says, they often feel the broader environment matters more right now than AI itself.
The answer, in the article's framing, still comes back to production relations. These employees remain in the same old production network. If their position as a node does not change, stronger personal ability and faster improvement may still be more than the network actually values. And if that is the case, their status inside the network does not improve either.
The article adds another point. Even if AI makes someone far more capable, that value still has to be distributed outward. If other people cannot see it, or if other networks that need those capabilities cannot reach it, then stronger ability does not automatically turn into stronger returns.
Why many individual AI startups still struggle to break out
The article applies the same logic to AI startups built by individuals or small teams. Its argument is that many of these companies may still be doing basically the same kind of work and holding roughly the same place in the network as before. New company, sure. New tools, sure. The product may look better too. But if they are not creating extra value inside the broader production network, there is no obvious reason for extra rewards to show up.
From there, the piece pushes a bigger claim: only by changing the existing production network, creating new production relations, and becoming a new node in that new network can a company or an individual take part in a fresh redistribution of traffic and resources. That is where new pricing power appears. That is where a bigger voice comes from. And that is where outsized returns may show up.
Rising AI valuations are framed as a fight over key positions in new networks
The article says this way of thinking also helps explain why leading AI companies keep pulling in higher valuations and stronger expectations. In the author's view, those companies are pushing into existing production networks, creating new production relations, and trying to lock down the most important node positions in those emerging networks. That is how they get new pricing power and influence.
The piece gives broad examples, saying these companies move into mathematicians' fields one day and pharmaceutical research the next. In the author's telling, that process touches a huge range of existing interests and alters many established production-relation networks. The scale, the article says, is hard to see the end of. Huge, really.
The takeaway here is direct. In the AI era, if a person cannot use AI tools to identify new production relations and cannot find a place in a new network, then even strong command of AI tools and skills may carry only limited real meaning and limited value.
Crypto is presented as a more direct way to alter production relations
Against that backdrop, the article casts crypto technology as a more direct way to change production relations. It says it is still difficult to clearly see how crypto will reshape current production relations in the future, or what new nodes it may create. Even so, the author says one thing has become clear over the years: every wave of change in crypto creates a new kind of relationship.
Some of those relationships may later turn out to be worthless. Some may later be seen as the wrong form. But at the moment a relationship network is formed, the article says, people who enter that network and become nodes can often capture wealth opportunities more easily.
The article gives several examples from crypto history:
- ICO
- DeFi
- NFT
- blockchain gaming
- inscriptions
- memes
Many of these later turned out to contain bubbles, the article says. Even so, during their growth phase they did, for a time, form new production-relation networks. People inside those networks, or those who got in early, really did experience memorable stretches of rapid wealth creation.
Reference links
Reference link 1: https://x.com/myanTokenGeek/status/2102984539836649701?s=20
Reference link 2: https://x.com/fankaishuoai/status/2103043935333658739?s=20
The article ends with a disclaimer saying markets carry risk and investing requires caution. It says the piece is not investment advice, and readers should judge for themselves whether any opinion, view, or conclusion in the article fits their own circumstances before making investment decisions.
