Everything is Fleeting: A Roadmap to the Post-Labor AI Economy

TL;DR

• LLMs push the boundaries, and AI tools take the jobs away. In the future, whether short or long, no one will have a traditional job.
• For now, management ability and capital are the ultimate keys to enjoying the benefits of AI.
• Skill depreciation will be the major issue in the short term.
• As AI agents take over, the Matthew Effect of wealth concentration will accelerate violently, rapidly eroding the middle class.
• The “Rumbling” of the labor market is coming. Survival must be permanently decoupled from labor, and work will no longer be a virtue.
• We might expect “compute allowance” to become a new form of circulating currency.
• The loss of traditional work will trigger a severe ideological crisis and polarization between techno-idealists and bio-conservatives, weaponized as a political instrument.
• Because human attention is capped, we will eventually live entirely within an experience economy driven by the “Human Premium.”
• The “end of the story of humans” as laborers transitions into the beginning of humans as pure explorers, philosophers, and creators.

Introduction

I have been thinking a lot lately about the trajectory of artificial intelligence, not just as a technological marvel, but as an economic wrecking ball. When you look at the landscape today, a clear pattern emerges: frontier AI models are continually advancing, pushing the boundaries of what is possible. In their wake, derivative AI tools proliferate even faster. Notable examples include OpenClaw ¹, FARS ², autoresearch ³, and Claude Code ⁴. These tools—a combination of raw AI models, curated rule-based algorithms, and human involvement—are systematically dismantling traditional workflows. In short: LLMs push the boundaries, and AI tools take the jobs away.

This development is rapidly turning the “intelligence market” into a fully competitive, hyper-commoditized arena. For almost any type of cognitive work, given enough resources, one can now find tools that handle it to some degree. If we extrapolate this trend, we arrive at a stark destination: in the future, whether soon or far off, no one will have a traditional job ⁵. That might sound like the end of the human story. Perhaps that day is 30 years away, or perhaps it is 100. But the exact date is not the main point. The real question is: What can we control before that day arrives?

Before the “end of the story,” the Earth still belongs to humans. For every droid, robot, or AI agent, there is an owner. In this transitional period, management ability and capital are the ultimate keys. You cannot properly incentivize or utilize artificial intelligence unless you possess the orchestration skills and the right prompts to direct it. Furthermore, it is an undeniable and unfair reality that the poor cannot easily access truly frontier AI models. Computation requires capital.

If this continues unabated, the ladder to the upper class ceases to exist. The elites, armed with frontier AI, will move through the economy like a hurricane. The Matthew Effect ⁶ will grow exponentially. We are heading toward a phase where most people will not have jobs and, economically speaking, will not even “deserve” them when measured against the efficiency of droids. Everyone currently employed will live in constant fear of layoffs. Like the “Rumbling” in Attack on Titan ⁷, workers will stand at the edge, watching colossal forces approach and knowing they will eventually be brutally trampled.

To understand how we get there, and what comes after, we need to map out the actual phases of the AI economy.

The Assumptions

It is crucial to note that this entire roadmap relies on strict ceteris paribus (all other things being equal) assumptions. If any of these fundamental constraints break, the projections change:

Intelligence Remains External: We assume humans and machines remain separate entities. If mature Brain-Computer Interfaces (BCIs) become mainstream, the “Human vs. AI” dynamic vanishes. Instead of AI taking our jobs, we merge with the machine, and our cognitive limits expand to match those of AIs.

Energy Scarcity Persists: This timeline assumes we do not achieve a sudden, miraculous energy breakthrough tomorrow. If energy becomes functionally infinite and free in the next five years, the cost of compute plummets to zero, radically accelerating the timeline to Phase 5.

Earth-Bound Economics: If interstellar exploration or asteroid mining technologies mature, they introduce an infinite frontier of new resources and challenges, permanently delaying the scarcity-driven phases and creating massive new sectors for both human and AI endeavors.

AI as Pure Utility (Anthropocentric Focus ⁸): We assume that the economic and societal focus remains strictly on humanity. We do not attribute moral weight, consciousness, or the capacity for “fun” to AI agents. How agents interact among themselves is only relevant insofar as it serves human ends. If society begins granting AI civil rights or prioritizing artificial “well-being,” the economic framework fractures into an ethical dilemma that falls outside the scope of this roadmap.

Operating strictly within these four constraints, we can more accurately project the future of labor. But to do so, we must first tear down the outdated economic theories we currently use to comfort ourselves.

Dismantling Classical Economic Defenses

When faced with the prospect of AI-driven mass unemployment, economists usually offer comforting theories. However, when subjected to the physical and computational realities of modern AI, these classical defenses collapse.

1. The Fallacy of the Jevons Paradox in an Attention Economy

The Jevons Paradox ⁹ states that as a technology increases the efficiency with which a resource is used, the demand for that resource actually increases. Traditional economists argue that if AI makes coding or writing 100 times faster and cheaper, we will simply demand 100 times more software and content, creating more jobs for human “editors.”

But this ignores the fundamental bottleneck of the internet age: Attention.

As Herbert Simon famously noted, a wealth of information creates a poverty of attention ¹⁰. Human beings have biological limits; we only have 24 hours in a day. We already have far more content, software, and digital products than we have demand for. When AI drives the marginal cost of creating digital goods to zero, supply explodes, but human attention remains capped. Therefore, the Jevons Paradox does not hold here. The economy will continue shifting from production to the curation and capture of limited human attention.

2. The Compute Cost Floor (The Illusion of Open-Source Equality)

Optimists point to open-weight models as the great equalizers. Stratification, they argue, is mitigated because anyone can download a powerful model.

While open weights are incredibly helpful, they level the playing field only to a limited extent. The fatal flaw in this optimism is the difference between knowledge and execution. Deploying a cutting-edge open-weight model—or even using a hosted one at scale—requires massive amounts of money. The physical realities of GPUs, data centers, cooling, and electricity cannot be open-sourced. We are drifting toward a dystopia where the intellectual architecture is democratized, but the hardware required to run it is violently monopolized by the elite.

3. The Breakdown of Comparative Advantage

The most common economic defense against the “end of jobs” is Comparative Advantage ¹¹. This theory suggests that even if an Artificial Superintelligence (ASI) is better at everything (Absolute Advantage), it will focus its compute on high-value tasks (curing cancer, physics) and leave lower-value tasks (flipping burgers, basic data entry) to humans because human labor will be relatively cheaper.

This assumes the ASI is merely a worker. But an ASI is an inventor. An ASI can design, code, and deploy millions of hyper-efficient, narrow sub-agents or cheap physical droids at near-zero marginal cost.

If an ASI can build a specialized tool to do a simple job for fractions of a penny, the cost of artificial labor drops below the human biological requirement for food and shelter. Comparative advantage fails because humans become too expensive simply by virtue of needing to eat.

The Five Phases of the AI Economy

If traditional economics cannot save the labor market, what does the actual timeline look like? Software scales instantly, but the physical world—corporate inertia, legal frameworks, energy grids, and manufacturing—moves slowly. Based on these physical bottlenecks, we can project five distinct phases.

Phase 1: The Orchestration & Attention Era (Present to ~10 Years)

We are currently in the Copilot era. AI models are incredibly powerful, but they hallucinate, lack long-term agency, and still require human intent. They automate tasks, not entire jobs.

In this phase, the winners are the “orchestrators.” These are the managers who possess the ability to string together different models, craft precise prompts, and align AI outputs with real-world goals. The immediate danger here is not mass unemployment, but rapid skill depreciation. Workers will feel the exhausting pressure to constantly learn the newest AI tools just to tread water. The market floods with AI-generated supply, squeezing entry-level knowledge workers as their raw output is commoditized.

Phase 2: The Agentic Economy & Capital Concentration (~10 to 30 Years)

This phase begins when AI models achieve reliable, long-term agency. They will be able to browse the web, execute code, manage budgets, and interact with other autonomous agents.

Companies will realize they no longer need a marketing department; they need a single “Marketing Agent.” Here, the Matthew Effect accelerates violently. The elites who own the massive compute clusters will reap almost all global profits. The “Compute Divide” replaces the digital divide as the primary mechanism of class stratification. If you do not have the capital to afford massive inference compute, you simply cannot compete. The middle class begins a rapid and painful erosion.

Phase 3: “The Rumbling” — The Labor Crisis & Decoupling (~30 to 40 Years)

This is the dystopia. This phase arrives when physical robotics (droids) catch up with cognitive AI. Establishing the global supply chains needed to manufacture billions of humanoid robots takes decades, but once achieved, human cognitive and physical labor reaches a true zero-value state in the standard market.

People will not have jobs, and economically, they will not deserve them. Traditional capitalism fundamentally breaks down because if humans have no wages, they cannot buy the goods the AIs and droids are producing. It is the ultimate crisis of the capitalist system.

To maintain societal stability, government intervention becomes an absolute necessity. AI democratization must be forced. Intelligence will become a fundamental public utility, like water or electricity. This is where concepts like Sam Altman’s Universal Basic Compute (UBC) ¹² step in as the ultimate safety net. We might even expect compute allowance to become a new form of circulating currency—one that is inherently more resistant to inflation than traditional fiat cash. UBC treats compute as a highly liquid asset. With your daily allowance of compute, you could have an AI research a personalized medical treatment, render a video game tailored to your preferences, or simply rent that compute allowance out to a scientific lab in exchange for traditional currency.

Since all work can be done by AI, this era forces the Great Decoupling: survival must be permanently decoupled from labor. From then on, labor is no longer a virtue ¹³.

Phase 4: The Great Bifurcation — The Ideological Crisis (~40 to 50 Years)

As survival becomes permanently decoupled from labor, the immediate threat of starvation fades, but a massive psychological void opens. This phase is defined by the struggle for meaning. Without the structure of a traditional job, society will fracture into two distinct ideological camps: techno-idealists, who embrace deep AI integration into every facet of human life, and bio-conservatives, who reject it as fundamentally dehumanizing.

This transition will not be socially smooth. The resulting struggle will not be merely cultural; it will be weaponized as a political instrument. In many systems, this conflict will become a convenient focal point for leaders, redirecting public attention away from the permanent entrenchment of wealth concentration and the reality that the actual economic engine is now entirely controlled by AI. The central conflict of this era is no longer Human vs. Machine, but Human vs. Human over how to live alongside the machine.

Phase 5: Post-Scarcity & The Human Premium (50+ Years and Beyond)

Eventually, we solve the energy bottleneck, perhaps through commercial fusion. Energy, compute, and physical droid labor become functionally infinite. The concept of a traditional “economy”—a system for allocating scarce resources—ceases to exist.

However, human desire continuously shifts, mutates, and differentiates across generations. Individual attention, time, and emotional energy remain hard biological constraints. In this post-scarcity civilization, the only functioning markets left will be based entirely on the Human Premium. People will pay a premium for a handmade wooden chair, a live theatrical performance, a human therapist, or a human-written blog post—not because AI could not do it faster or better, but purely for the authenticity, the friction, and the connection of another human being. No one can stand a world that is completely rigid and unyielding. We will live entirely within an experience economy ¹⁴.

Here, we finally prove the “Lump of Labor Fallacy” ¹⁵ right in a new context: we don’t run out of things to value, because the nature of what we value transforms. The “end of the story of humans” as laborers transitions into the beginning of humans as pure explorers, philosophers, and creators.

Conclusion

Everything is fleeting. The jobs we hold, the skills we spend decades refining, and the economic models we blindly trust are all temporary structures built on the shifting sands of technological capability.

The “Rumbling” of the labor market is coming, and it will challenge the very foundation of human purpose. But recognizing the storm is the first step toward surviving it. Before that day comes, the Earth still belongs to humans. The transition through these phases relies entirely on our management ability, our political will, and how we choose to distribute foundational compute.

We are moving toward an era in which we must strip away the necessity of labor to discover what human beings actually want to be. It will be terrifying, it will be chaotic, but if we navigate the decoupling successfully, we may well end up living in the ultimate experience economy.

So, you should think further.

Acknowledgments

Special thanks to Hanyu Wang for the valuable debates and insights, and to Qingchen Yu and Huayi Lai for their feedback and suggestions on this post.

Citation

@article{shichaosong2026everythingisfle,
  title = {Everything is Fleeting: A Roadmap to the Post-Labor AI Economy},
  author = {Shichao Song},
  journal = {The Kiseki Log},
  year = {2026},
  month = {March},
  url = {https://ki-seki.github.io/posts/260314-ai-economics/}
}

References