Medvi has just become the first one-person company valued at a billion dollars. A single founder. No team. AI doing the work that once required dozens of people. Headlines are celebrating this as a triumph of efficiency. And technically, it is. But a question emerges that few are willing to ask outright: what happens to the work that efficiency eliminated?

This isn't a rhetorical question. It's the structural challenge of the next decade.

When one person captures the value that used to be generated by a hundred, the problem isn't the technology. AI is operating exactly as designed. The real challenge is distributive. The wealth that used to be split among analysts, designers, developers, coordinators, and assistants is now concentrated at a single point. AI doesn't create inequality. It accelerates it at a pace no current political system is prepared to handle.

What's striking is who gets displaced first. Not manual laborers. Rather, data analysts, writers, junior developers, accountants, legal assistants. That educated middle class that spent years building its identity around knowledge as a valuable asset. They invested in universities, certifications, specializations, assuming technical expertise offered protection. That assumption is collapsing.

The trend isn't unprecedented, though its speed is. In the Industrial Revolution, the first affected were skilled craftsmen, weavers who had honed their trade for years. Then came factory workers, and the system eventually created new jobs. That transition lasted generations and was conflictive. This reorganization is condensing into years, not decades. The institutions meant to cushion the impact — education systems, labor frameworks, social safety nets — were designed for a world where technological change allowed time to adapt.

Here enters a vicious cycle predictable from systems theory. Fewer employees mean fewer consumers. Fewer consumers reduce demand. Less demand weakens viable businesses. An economy of billionaire founders without a solid consumer base is structurally vulnerable, no matter how many unicorns it produces. When concentration exceeds a threshold, the structure destabilizes internally. It doesn't require an external collapse. It erodes on its own.

Faced with this, the suggestion is to redirect people toward AI-resistant careers: plumbers, electricians, nurses, caregiving roles. Those trades are hard to automate, and that much is correct. But this idea has a limit rarely mentioned: there's no sustainable plumber in an economy without a middle class. The market for physical services depends on broad purchasing power. If that power collapses due to the disappearance of cognitive employment, manual jobs won't serve as a refuge. They become the last stop before the same abyss.

It's worth noting that during the 19th-century European agrarian transition, manual trades absorbed labor displaced from the countryside, but only because global trade expanded demand. With AI, that expansion isn't guaranteed. Universal Basic Income emerges, then, as the most debated proposal: an unconditional state payment covering essentials, regardless of whether one works or not. The experiments in Finland and Kenya are revealing. They refute the main counterargument: that people would stop making an effort. The data shows otherwise. Those who received basic income sought employment with greater calm, started businesses with less fear, and took better care of their health. No disincentive to work emerged. What emerged was relief from chronic stress.

Financing it poses real challenges. In robust economies, taxes on capital and automation could cover part of it. In Mexico, projections place UBI between four and six percent of GDP. Mathematically viable. Institutionally improbable. The knot lies in political incentives. Those with the power to redistribute tend to benefit from inaction. Game theory illustrates this precisely: the Nash equilibrium doesn't always favor the collective. It often leads to outcomes nobody wants, but that nobody changes because no individual actor has an incentive to move first.

This is where UBI diverges from what the Luddite Manifesto proposes. Universal income trusts that the state will redistribute what the market accumulates. A valid bet where institutions are solid and transparent. The Manifesto proposes another path: a model where verifiable contribution grants direct access to resources, without state mediation. It's not managed charity. It's coordination restructured from the ground up. The distinction isn't ideological, but one of design. A structure tied to state will has a single point of failure. One where distribution is built into the rules of the game avoids that dependency.

Everything gets more complicated with geopolitical tensions that rarely surface in debates about AI and employment. The growth capacity of artificial intelligence requires tangible resources: rare earths, advanced chips, data centers with unsustainable energy consumption, quantum computing advancing faster than regulations. Few countries control those elements. Any financing for distributive solutions depends on a global economy that these very resources could destabilize. The energy transition offers an exact parallel: the critical minerals needed for the green economy reproduce the dependencies it was supposed to overcome. The same is happening with AI.

The one-person company valued at a billion dollars isn't the core problem. It's the most visible symptom of a labor restructuring that's been underway for some time. Medvi makes tangible the gap between what technology achieves and what institutions manage. It's still unclear how to resolve this in countries with fragile institutions and dominant informal economies. What is clear: the key question isn't whether Universal Basic Income is viable. It's whether the institutions tasked with implementing it have the right incentives. And if they don't, there's an urgent need to design structures that don't depend on that goodwill.

Stones don't lie, but historians sometimes do.

Sources:

1. Finland's Universal Basic Income Experiment (2017-2018) — Kela (Social Insurance Institution of Finland)

2. GiveDirectly — Results from the direct transfer program in Kenya (2016-2023)

3. Nash, J. (1950). "Equilibrium Points in N-Person Games" — Proceedings of the National Academy of Sciences

4. World Bank — Reports on wealth concentration and the impact of automation on emerging labor markets (2022-2024)

5. IEA — Critical Minerals and the Clean Energy Transition (2023)