The Age of Abundance

Writing TheGreySwan has now become a personal exploration. I started it with a simple goal: to think about the world through three lenses—markets’ uncertainty, operating, and life. Technology rarely changes just one of these. It reshapes markets, forces organizations to adapt, and eventually changes how individuals navigate their careers and choices.

So, I’ve been spending more time thinking about the operating layer—the messy space where humans and machines actually meet. Last week’s essay, Age of Genius, was one step in that direction. This week’s thought continues this journey.

This post is about where scarcity moves in the age of AI.

In the 1980s, robotics researcher Hans Moravec made a strange observation about artificial intelligence. At the time it sounded like a technical curiosity. Today, it could reads like a roadmap for the AI era.

Tasks that humans consider intellectually difficult—playing chess, solving equations, or passing intelligence tests—turned out to be relatively easy for computers. But tasks humans perform effortlessly—perception, movement, common sense—proved extraordinarily difficult to automate.

Moravec summarized the paradox succinctly:

“It is comparatively easy to make computers exhibit adult-level performance on intelligence tests… and difficult to give them the skills of a one-year-old.”

This became known as Moravec’s Paradox.

Recent progress has been breathtaking. Models now achieve gold-medal-level performance on Olympiad mathematics. “Vibe coding” has become commonplace. AI agents navigate computer interfaces and complete multi-step workflows. Yet even as these capabilities expand, something curious persists. Real-world reliability remains stubbornly low—benchmarks for autonomous action still hover in the 30–60% range. A toddler can grasp that a fallen cup still exists; as models continue to hallucinate.

Moravec revealed something deeper than a technical puzzle. We had been searching for intelligence in the palace of abstract thought—in chess championships and calculus problems. But intelligence, it turns out, was hiding in the humble desert of sensorimotor skills all along.

This reframes the question that haunts every era of technological disruption:

If machines can now perform intellectual work at scale, what happens to the value of human effort?

History suggests an answer that defies first instincts. Abundance rarely destroys value. It moves it.

Whenever technology makes one capability abundant, the economic system reorganizes itself around a new constraint. Value flows away from what becomes easy and gathers around whatever remains scarce.

This is the Abundance Paradox.

When Books Flooded Europe

To understand the pattern, we need to revisit the last great information revolution. Before Gutenberg’s printing press, the scarce resource was obvious: information.

Books were copied by hand. Knowledge lived inside monasteries and universities. Producing a single manuscript could take months of labor. Naturally, value accumulated around those who controlled the production and preservation of knowledge. Then the printing press changed the equation.

By the year 1500, roughly 20 million books had been printed across Europe. The cost of producing information collapsed.

At first glance, this should have destroyed the value of knowledge. But it didn’t.

It simply moved the bottleneck.

Once information became abundant, the scarce resource became attention—the ability to read, interpret, and navigate an expanding ocean of texts.

The winners of the new era were not merely printers. They were interpreters.

The Protestant Reformation illustrates the shift. Martin Luther did not invent the Bible. What he did was translate and frame it for a new audience. In a world flooded with texts, he provided something scarce: interpretation.

The printing press did not eliminate value. It relocated it—from information to attention.

Three Transfers of Value

Today we are experiencing a similar transformation, but compressed into years rather than decades.

AI and digital infrastructure are triggering three simultaneous transfers of value.

Transfer 1: From Information to Attention

The internet solved the problem of information scarcity.

Search engines made knowledge instantly accessible. But once information became abundant, a new constraint emerged.

The scarce resource became attention. This dynamic reflects what we described earlier as the Attention Constraint.

Human attention remains finite even as the supply of information grows exponentially.

AI intensifies this dynamic. When machines can generate and process content at unlimited scale, the bottleneck becomes even clearer.

In the cognitive economy, attention is the ultimate scarce resource.

Transfer 2: From Content to Taste

Generative AI is now pushing abundance further.

Music, essays, marketing copy, software code, visual design—AI can generate them all with minimal effort.

The world is entering a phase of infinite content.

AI will produce infinite content, but human attention will remain painfully finite.

When everything can be produced, the valuable skill becomes deciding what is worth consuming.

So, taste becomes the scarce asset, and bottleneck shifts from creation to curation.

"Curating is not about choosing, it's about connecting. It's about creating a context in which a work can breathe and a viewer can think."

The economy of creators slowly evolves into an economy of editors and filters. As generative tools proliferate in 2026, premium human curation (and hybrid human-AI taste) commands rising value.

Transfer 3: From Computation to Judgment

In the industrial era, the key constraint was physical capital. Factories, machinery, and infrastructure defined the limits of production.

In the software era, the constraint shifted toward human capital, particularly the ability to write code. In the AI era, both constraints are weakening.

Compute capacity continues to scale. Code can increasingly be generated through natural language prompts. Execution—the “slope” of work—is becoming automated.

But one constraint remains stubbornly difficult to scale. Judgment. AI can optimize execution. But it cannot determine intent, we talked at length about this here.

The more intelligence machines generate, the more valuable human judgment becomes.

Graham Allison's Essence of Decision, mentioned a moment of operational judgment during the Cuban Missile Crisis (by John F. Kennedy), as

The Rule of Technological Abundance

Across every technological revolution, the same pattern repeats.

When something becomes 10× easier to produce, its economic value collapses.

When something becomes 10× harder to filter, its value explodes.

Printing made information abundant → attention became scarce
The internet made distribution abundant → trust became scarce
AI makes creation abundant → judgment becomes scarce

Value always flows toward friction.

Machines flatten the slope—execution, speed, scale.

But the intercept—defining the problem itself—remains human.

Execution becomes abundant. Direction remains scarce.

Operating Implication: The Indian IT Example

This pattern becomes clearer when grounded in real industries.

In Climbing the Curve Before the Crown, we examined how Indian IT services captured value during the globalization wave.

Companies like TCS and Infosys became the interface between Western corporations and a large pool of technical labor. But abundance changes the equation.

If AI makes basic coding abundant, the traditional advantage of labor arbitrage weakens. In 2026, Indian IT giants face real pressure—headcount reductions, automation fears, and the risk that legacy delivery models may erode.

Yet they are also adapting.

TCS is expanding AI infrastructure partnerships. Infosys is collaborating with AI labs. Both are investing heavily in workforce reskilling.

Clients will not simply need more code. They will need certainty.

The value for Indian IT will migrate from companies that provide execution to companies that provide judgment and trust.

When production becomes cheap, distribution and trust dominate.

Those that remain focused on supplying labor may struggle. Those that become institutional layers of verification and assurance may capture the next phase of value creation.

The Personal Scarcity

The Abundance Paradox does not only apply to markets. It also applies to individuals. We now live inside an unprecedented abundance of tools, information, and opportunity. AI will rewards people who direct attention intentionally.

AI can assist with writing, coding, research, and analysis. But abundance creates its own constraints.

If information is infinite, the scarce resource becomes focus.

If content is infinite, the scarce resource becomes taste.

If execution becomes automated, the scarce resource becomes judgment.

The most valuable asset you will possess in the coming decade will not be your ability to produce information.

It will be your proprietary lived experience—the pattern recognition, scars, and relationships that cannot be scraped from the internet or generated by a model.

So, what next?

The promise of AI is abundance: infinite content, infinite intelligence, near-zero cost creation.

But abundance does not eliminate scarcity. It relocates it.

In the AI era, scarcity moves from production to attention, from information to judgment, from access to trust. As the world fills with limitless outputs, the signals that guide human choice—credibility, taste, reputation, and meaning—become exponentially more valuable.

The real law behind the Abundance Paradox is:

When one constraint disappears, another becomes dominant.

The future will not belong to those who produce the most. It will belong to those who can navigate abundance.

In a world where machines generate endlessly, the scarce capabilities become profoundly human:

Attention — the ability to focus when distraction is infinite.
Taste — the ability to select when creation is free.
Judgment — the ability to decide when data is abundant but clarity is not.
Trust — the willingness to take responsibility when machines can only execute.

In an age of abundance, the ultimate advantage is not access to intelligence, but the wisdom to know where to look—and what to ignore.

The palace of abundance will keep expanding. Its halls will fill with generated noise, automated output, and infinite copies of everything. But value will always live in the desert.

Find the desert early, and Learn to live there.