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THE 2028 ABUNDANCE THESIS

What if our AI bullishness continues to be right...and what if that's actually bullish?

What follows is a scenario, not a prediction. This isn't techno-utopian copium or abundance cult fan-fiction. The sole intent of this piece is modeling a scenario that's been relatively underexplored: what happens if the disruption produces renaissance instead of crisis. Citrini Research wrote the bear case. We wanted to write the bull case with equal rigor.

Hopefully, reading this leaves you more attuned to potential right-tail outcomes as AI makes the economy increasingly weird.

This is the simisite Macro Memo from December 2028, detailing the progression and emergence of the Abundance Economy.

simisite
March 9th, 2026 → December 31st, 2028

The S&P 500 closed the year at 7,840. Down 12% from its October 2026 highs, but up 23% from the March 2028 lows. The correction scared everyone. It bankrupted no one systemically. And it gave way to a rally built on economics nobody had frameworks for.

New business applications with planned wages: 6.8 million in 2028. Previous record: 1.8 million in 2021.

Fertility rate: up for the first time since 2007.

Obesity rates: down 14 percentage points in four years.

Two years. That's all it took to go from "AI will destroy jobs" to "AI created more businesses than any technology in history." Not the same jobs. Not the same businesses. Something genuinely new.

Let us reconstruct the sequence—and explain why the bears got the sign wrong.

They Watched the Numerator. We Watched the Denominator.

The Citrini piece documented the layoffs with precision. White-collar employment contracted 18% from 2024 peaks. ServiceNow. Zendesk. The cascading SaaS compression. The "daisy chain of correlated bets on white-collar productivity growth."

All true. All happened.

What the bears missed: the same agentic capability that made existing companies vulnerable made new companies trivially cheap to start.

CENSUS BUREAU: NEW BUSINESS APPLICATIONS WITH PLANNED WAGES HIT 6.8M IN 2028; PREVIOUS RECORD 1.8M (2021); 100X MORE ENTREPRENEURIAL EXPERIMENTS PER CAPITA VS 2019 | Census Bureau, Jan 2029

The CIO reviewing a $500k annual renewal asking "what if we just built this ourselves?" was also a former product manager launching three products in six months. The same person. The same capability. Different framing.

Job destruction and job creation aren't separate phenomena happening to different people at different times. They're the same capability, hitting the same people, creating churn that looks catastrophic on the numerator and miraculous on the denominator.

The labor force participation rate for 25-54 year olds hit 84.2% in November 2028—highest since 1999. People are working. They're just not working for the companies that used to employ them.

"Ghost GDP" Found Bodies

Citrini introduced the term "Ghost GDP": output that shows up in national accounts but never circulates through the real economy. A single GPU cluster in North Dakota generating output previously attributed to 10,000 white-collar workers in midtown Manhattan.

The concern: machines don't spend on discretionary goods. Velocity of money flatlines as labor's share of income collapses.

Here's what actually happened: the Ghost GDP found bodies through deflation.

When services become 60-80% cheaper, the same nominal income buys dramatically more:

A family spending $8,000/year on professional services now spends $2,100 for equivalent or better outcomes. Their nominal income dropped 25%. Their real consumption capacity dropped less than 5%.

The bears confused supply-driven deflation with demand-driven deflation. When things become cheaper to produce, that's not a depression—that's rising living standards. It's how we went from spending 50% of income on food in 1900 to under 10% today.

Services, the last bastion of Baumol's cost disease, finally joined the deflation party. The "velocity of money" metrics look weird because nominal spending is down. Real consumption is up.

The Intermediation Collapse Was Good

Citrini documented the collapse of intermediation: travel booking, insurance renewals, financial advice, tax prep, real estate commissions. "Agent on agent violence." Billions spent exploiting quirks of human psychology, watching those moats dissolve.

They framed this as catastrophe. We frame it as liberation.

The "giant rent-extraction layer built on top of human limitations" was not economic infrastructure. It was a tax on being human—on having limited time, limited attention, limited patience. Trillions extracted because people couldn't be bothered to shop insurance renewals.

When agents started doing this automatically, the extraction disappeared. But the spending didn't. It reallocated to actual goods and services.

DoorDash's margin compression is bad for DoorDash shareholders. It's excellent for delivery drivers now capturing 90-95% of fees instead of 50%. The white-collar workers who "ended up as delivery drivers" are earning more per hour than they would have two years ago, because the platforms extracting half their labor value got disrupted.

"Friction was going to zero."

Yes. And friction was a tax, not a feature.

The Agent-to-Agent Economy That Wasn't

Here's what didn't happen: the machine-to-machine economy taking over everything.

By mid-2026, the hot thesis was A2A—agents transacting with agents, humans increasingly irrelevant to the flow of commerce. Agents negotiating with agents. Agents routing around card networks. Agents optimizing supply chains end-to-end without human intervention.

Some of this materialized. Stablecoin payments did route around interchange. Agentic shopping did kill habitual brand loyalty. The intermediation layer did collapse.

But the full A2A vision—machines primarily serving machines, humans as afterthought—didn't take off. And it didn't matter. Because something else happened instead.

Human needs exploded.

When AI handled the drudgery, people didn't sit idle. They discovered they wanted things they'd never had time to want before. Custom furniture. Artisanal food. Personal training. Music lessons. Therapy. Travel. Experiences. Education for its own sake. Time with children.

The velocity of money didn't flatline because machines don't consume. It stayed healthy because humans, freed from the grind, turned out to have infinite appetites for real things—things that can't be digitized, things that require presence and craft and attention.

Agentic commerce was supposed to automate consumption. Instead, it liberated consumption. The A2A economy is a rounding error. The human economy is thriving.

The Negative Feedback Loop Had Brakes

The Citrini piece described a "negative feedback loop with no natural brake": AI improves, companies lay off workers, savings flow into AI capability, AI improves. Each company's individual response rational, collective result catastrophic.

We had a different model. The brakes existed but weren't where economists were looking.

Brake 1: Entrepreneurial explosion. Every displaced worker who starts a business absorbs the shock rather than transmitting it. Business formation isn't a consolation prize—it's the mechanism of restructuring. Rate of new business formation is the most important variable nobody tracked.

Brake 2: Service deflation. Falling costs mean displaced workers need less income to maintain living standards. A $180k→$90k decline paired with 40% service cost drop is roughly flat in consumption terms.

Brake 3: Geographic mobility. Displaced workers who couldn't afford $4,500/month mortgages in San Francisco relocated to markets where $1,800/month bought equivalent housing. Secondary cities absorbed tech workers at dramatically lower cost structures.

Brake 4: The Rebuilders. Civic participation provides meaning and connection that labor market metrics miss. People working on communities rather than corporations.

Brake 5: The creative economy. 1,000 true fans at scale. More professional artists earning $30k+ in 2028 than any point in recorded history.

Brake 6: Health transformation. Peptide revolution: obesity down 14 points, Type 2 diabetes down 27%, cardiovascular events down 21%. These compound into higher productivity and lower social costs.

None of these show up cleanly in economic models. All are measurable. All are real.

The Walzers

It started as a prank.

In February 2027, Riley Walz—the developer known for his satirical AI projects—got fed up waiting for a permit to install solar panels on his mother's house in Los Angeles. The application had been stuck in review for nine months. He'd called the planning department 47 times. Nothing moved.

So he did what Riley Walz does: he built something unhinged. Not one agent. Not two. A full sybil attack—hundreds of AI personas, each with backstories, each with different communication styles, each targeting a different member of Mayor Bass's staff and the planning department hierarchy. They called. They emailed. They filed public records requests. They showed up to every public comment period. They coordinated testimony that made the permit backlog a recurring news story.

His mother's permit was approved in eleven days.

Riley posted the code. The internet did the rest.

RILEY WALZ RELEASES "BUREAUCRACY SWARM" CODE; GITHUB REPO HITS 50K STARS IN 72 HOURS; LA PLANNING DEPARTMENT FLOODED WITH AI-GENERATED INQUIRIES | Ars Technica, March 2027

Within weeks, people were "walzing" their own local governments. The verb stuck. "We walzed the Austin planning board." "Someone walzed the SF fire marshal." "They got walzed so hard they just started approving everything."

The legal status was... ambiguous. The agents weren't filing false information—they were asking real questions, citing real regulations, demanding real accountability. Just at scale. And persistently. City attorneys struggled to articulate what law was being broken when an AI sends 400 polite follow-up emails about a permit status.

What started as chaos evolved into the Rebuilder movement. The initial wave was adversarial—overwhelming bureaucracies into compliance. The second wave was collaborative: people realized the same swarms could actually help officials navigate their own systems. Some planning departments quietly started using forked versions of Riley's code to process their own backlogs.

In Oakland, a cluster cut affordable housing approval from 34 months to 11. In Phoenix, a group adopted 12 miles of public trail the parks department couldn't maintain. In Austin, permit timelines dropped from 14 months to 5 after officials saw what was coming and decided to get ahead of it.

The pattern replicated across cities. People with time, tools, and local knowledge systematically disarming civic bureaucracy that had calcified over decades. Some called it civil disobedience. Others called it the most effective government reform movement since the Progressive Era.

Riley Walz got a cease-and-desist from the City of Los Angeles. He framed it and hung it in his living room. His mother's solar panels work great.

The Hardware Renaissance

AI collapsed software costs, which paradoxically increased the relative value of things that can't be digitized. Physical objects. Tactile experiences. Craftsmanship you can touch.

Software abundance created hardware scarcity—or rather, made hardware differentiation matter again.

CNC machining communities exploded. Small-batch manufacturing became viable once AI design tools collapsed engineering overhead. You can prototype a physical product in a weekend for a few hundred dollars. If it works, produce a thousand units without Shenzhen.

There's an aesthetic dimension: "American industrial revival." Exposed materials, visible joinery, functional design with craft integrity. After two decades of disposable minimalism, people want things that last.

Manufacturing employment ticked up 3.2% in 2028—first increase in four decades. Reshoring is real, not because labor got cheaper, but because overhead finally compressed.

The Step Changes

Some developments resist trend extrapolation. Discontinuities that reshaped baseline assumptions:

Organoid computing. Johns Hopkins demonstrated lab-grown neural tissue performing pattern recognition at 1/10,000th the power consumption of silicon. By mid-2028, commercial organoid co-processors shipping. The marginal cost of intelligence dropped another order of magnitude.

Fusion breakeven. Helion hit Q > 1 in April 2028. Commonwealth followed. Neither commercially viable yet—the path from breakeven to economical electricity is years. But the psychological barrier fell. Private investment quadrupled. Energy abundance has an engineering roadmap.

Quantum error correction at scale. Google's Willow demonstrated below-threshold error correction in late 2025. By late 2028, 200+ logical qubit systems running continuously. Not yet solving commercial problems faster than classical. But the scaling question is answered. Quantum is engineering, not physics.

Together: the technological frontier advancing across multiple vectors simultaneously. Energy, computation, biological engineering. This convergence is rare in history. It changes what's conceivable.

The Ambitious Works

In September 2028, San Francisco approved the Liberty project: a 150-foot bronze statue of Justice on Alcatraz Island. Scales in one hand, broken chain in the other. Facing west.

Design selected through public competition: 4,000 entries. Winner: a 28-year-old sculptor from Detroit, no prior public commissions. Funding: municipal bonds, private philanthropy, $23 million crowdfunding in 72 hours.

Museum of migration on the Texas border. Climate memorial in Miami. Penn Station reconstruction in New York.

The pessimistic frame imagined abundance leading to stagnation. The actual response: ambition. When material security becomes baseline, people don't sink into anomie. They build things. They bet on beauty and meaning.

By late 2028, the pipeline of ambitious public works is larger than it's been since the WPA.

The 1,000 True Fans Economy

More professional musicians earning $30k+ annually in 2028 than any point in recorded history. Same for visual artists. Writers. Independent game developers.

How is this possible in a world of AI-generated content?

Kevin Kelly's "1,000 true fans," articulated in 2008, finally became real at scale. AI replaced middlemen, not creators. Distribution costs collapsed. Discovery restructured around genuine engagement rather than attention hijacking.

A musician with 2,000 fans at $15/month earns $360,000/year. No label. No touring. No algorithm dependence. The arithmetic was always possible. The infrastructure to make it frictionless finally exists.

The fear: AI slop floods the zone. Reality: people tell the difference. They're willing to pay for authenticity. The market bifurcated: free commodity content one layer, paid human creative work another. Both growing. Human layer growing faster.

Winner-take-all dynamics are inverting. The long tail is earning a living.

The Peptide Revolution

Semaglutide and successors reduced US obesity rates by 14 percentage points between 2024 and 2028. One in seven formerly obese Americans is no longer obese.

Downstream cascades through healthcare economics:

Healthcare cost curves bending for the first time in decades—not through rationing but through upstream intervention preventing expensive conditions.

AI-assisted molecular modeling enabled combinatorial explosion of peptide therapeutics. Next generation targets addiction, neurodegeneration, autoimmune conditions previously untreatable.

Rebuilder clusters explicitly targeting healthcare bureaucracy: agent swarms navigating prior authorization mazes, documenting denial patterns, coordinating patient advocacy at scale.

Result: more people have access to effective treatments than the system was designed to provide. Structural healthcare reform forced, not debated.

The Fertility Surprise

US total fertility rate ticked up in 2028 for the first time since 2007. Preliminary: 1.74 births per woman, up from 2023 trough of 1.62.

Causality overdetermined: declining housing costs in secondary cities, flexible work arrangements, improved fertility interventions, and cultural optimism hard to measure but real to experience.

People are having children because they believe the future will be good.

That belief, once lost, is difficult to restore. Its return is one of the strongest macro signals we track.

The Oracles

Prediction markets became infrastructure.

By late 2027, the question wasn't whether prediction markets were accurate—that debate was settled. The question was what to do with probability estimates that kept being right. When Polymarket and its competitors consistently outperformed polls, pundits, and expert panels, the information started flowing upstream into actual decision-making.

Insurance companies began pricing policies off prediction market odds rather than actuarial tables. Venture funds used market-implied probabilities to value startups. Governments quietly consulted prediction markets before major policy announcements.

The top forecasters became minor celebrities. A social network called Oracles emerged—part trading floor, part intellectual arena. The best predictors built followings in the hundreds of thousands. Their track records were public, immutable, constantly updated. You could see exactly how often they'd been right, on exactly which kinds of questions.

This created structural odds for the future in a way that had never existed before. Not vibes. Not narratives. Calibrated probability estimates from people with skin in the game and verified track records.

It wasn't without scandal. In August 2028, a prominent Oracle user—handle "CassandraDAO," top 50 on the leaderboard—was caught taking money to post misleading analysis on an energy futures question. The mispricing lasted about 11 hours before other forecasters noticed the anomaly, piled into the correct position, and traced the information back to a suspicious payment. CassandraDAO was blacklisted from the platform within 48 hours. Their entire prediction history was flagged. Their reputation, built over three years, evaporated overnight.

The speed of the correction was the point. The system was self-policing because accuracy was the only currency. You couldn't fake a track record. You couldn't buy credibility you hadn't earned. And if you sold out, the market would find you.

By December 2028, Oracles had 4.2 million active users. The top 1,000 forecasters were watched more closely than most financial analysts. Their collective probability estimates on AI progress, geopolitical events, and technological timelines became a kind of consensus reality—not because anyone trusted any single predictor, but because the aggregation of calibrated beliefs kept proving accurate.

On the Mortgage Question

Citrini raised the mortgage question: are prime mortgages money good? The $13 trillion market built on assumptions about income stability that AI disruption challenged.

Here's what we observe: stress remained concentrated. San Francisco, Seattle, Manhattan, Austin—markets heavily exposed to tech employment. National delinquency rose but stayed well below 2008.

The mechanism preventing contagion: geographic mobility plus service deflation.

Displaced workers who couldn't afford $4,500/month mortgages in San Francisco relocated where $1,800/month bought equivalent housing. Secondary cities—Boise, Austin suburbs, Tampa, Charlotte—absorbed tech workers at dramatically lower cost structures.

The Zillow data tells two stories: 11% decline YoY in San Francisco, 4% increase in Boise, 6% increase in Tampa.

The "mortgage crisis" was coastal premium deflation, not national housing collapse. Some prime mortgages weren't money good. The system didn't break because borrowers moved rather than defaulting, and destinations had solvent buyers.

On the Policy Question

Citrini described government paralysis: policy response moving at pace of ideology, not reality.

Different read: policy was slow, but it wasn't the binding constraint.

Market-level adjustments—entrepreneurial explosion, service deflation, geographic mobility, civic rebuilding—happened faster than policy could have responded anyway.

The Transition Economy Act eventually passed in Q3 2028, providing transfers to displaced workers funded partly by AI inference compute taxation. By the time it passed, acute crisis had largely resolved through organic mechanisms. The Act functioned as consolidation, not rescue.

This is the optimistic read: the economy restructured faster than government could intervene. The economy has more adaptive capacity than bear models assumed.

The Repricing

Citrini was right: human intelligence is being repriced. The premium on cognitive labor has compressed. Work requiring expensive professionals is now commoditized.

Where we differ: we don't think the repricing is catastrophic. We think it's liberating.

For most of human history, survival required selling time. You worked or you starved. The arrangement was coercive by construction. "Dignity of work" was partly cope—people making meaning out of necessity.

When AI collapses the price of cognitive labor, it doesn't destroy value. It democratizes access to capabilities previously reserved for the wealthy.

The $180k/year consultant's advice is now available to someone making $45k.

The bespoke legal work is affordable for small businesses.

The financial planning is accessible to median households.

The former consultants, lawyers, advisors are not useless. They're doing different things: starting companies, building products, participating in civic life, creating art, raising children. Many earn less in dollar terms. Most report higher life satisfaction.

We are running a natural experiment in decoupling income from wellbeing. Early results are encouraging.

What's Actually Happening

Here is what we observe as 2028 closes:

The entrepreneurial explosion is real.
The service deflation is real.
The Rebuilders are real.
The hardware renaissance is real.
The ambitious works are real.
The creative flourishing is real.
The peptide revolution is real.
The step changes in technology are real.
The fertility uptick is real.

These are not hand-waves. They're specific, observable developments adding up to something significant: a civilization learning to use its new tools well.

The pessimistic frame was not wrong about the magnitude of change. It was wrong about the sign.

We are not in a crisis. We are in a renaissance.

• • •

But you're not reading this in December 2028. You're reading this in March 2026.

The trajectory is not guaranteed. The abundance thesis requires building: building businesses, building civic infrastructure, building health interventions, building creative economies. Passively waiting for the positive scenario would guarantee the negative one.

The good news: building has never been cheaper. The tools are here. The capabilities are real.

The question is whether we use them.

The canary is still alive. And it's starting to sing.

March 2026. A response to Citrini Research's "The 2028 Global Intelligence Crisis."