Solve Everything

2026: The Lock-In

The concrete is wet. The mold is open. And the clock is running.

Corporate boards have gutted the old C-suite playbook. HR chiefs are gone. In their place: Compute Portfolio Managers. The new vital sign of a healthy company is RoCS (Return on Cognitive Spend), how much real value you extract from every dollar poured into the intelligence stack. If you can't prove your AI spend is generating outcomes, capital markets treat you like a corpse that hasn't stopped walking yet.

An MIT sophomore just humiliated a global defense contractor. From his dorm overlooking the Charles River, he rented a swarm of AI engineering agents, typed a description of what he wanted (a guidance system for orbital debris removal), and let them loose. The agents wrote the code. They tested it. They generated a cryptographic Replication Pack proving it works. Fifty million dollars and three years of government lab time. He did it in four hours for the price of a pizza.

Mathematics has become a utility. Frontier models have crushed every public benchmark. Formal proof verification costs pennies. Investors don't care about your pitch deck anymore. They care about your conversion rate: how often your AI stack produces working, safe code on the first try. The era of probability is over. The era of proof has begun.

The Muddle is fighting back. It always does. The tangled mass of legacy bureaucracy, input-based pricing, and scarcity-era institutions is trying to strangle the new thing in the crib. Regulators are drafting bans on "unsupervised AI loops." But the economy is routing around them like water around a rock. The first Targeting Authority has gone live, posting a $2 billion bounty for whoever can synthesize a room-temperature superconductor. The money sits in a smart contract. Flash teams of researchers are forming around it like iron filings around a magnet.

Even education is cracking open. A school chain in Brazil charges zero tuition. They take a cut of each student's verified skill gains. If the kid doesn't learn, the school doesn't eat. Simple. Brutal. Spreading.

Intelligence is no longer a craft practiced by artisans. It is the new electricity. The grid is live, the voltage is climbing, and the meter is running.

2030: The Liquefaction

The physical world capitulates.

In the Nevada desert, a fully automated science factory runs 24/7. Robotic chemists iterate through battery formulas at machine speed: mixing, testing, analyzing, refining. No human hypotheses. No coffee breaks. The laboratory has become a server farm for matter.

Biology has officially surrendered. You don't buy drugs anymore. You buy a subscription to "Normal Liver Function." Organ-printing micro-factories are open for business. A patient in Tokyo walks in with a failing kidney and walks out three days later with a scheduled transplant: a printed replacement that requires zero anti-rejection meds. The organ waiting list is gone. It was never a medical problem. It was an inventory problem.

Energy has flipped from scarcity problem to routing problem. Solar costs have hit the floor. AI-designed batteries store midday sun for nighttime demand. Massive data centers act as virtual batteries for the grid: soaking up power when the sun blasts, releasing it when clouds roll in. The sun is a reactor. The grid is a program. The humans just set the dials.

Brain-computer interfaces look like sleek headphones. Architects design buildings by thinking shapes into existence. Musicians compose by feeling. And in the Pacific, researchers have opened a communication channel with whales, trading ocean current data for weather forecasts. That sentence is not poetry. It is engineering.

Food decouples from weather. Vertical farms pump out perfect nutrition in city basements. Hunger is reclassified from tragedy to logistics error. A new role crystallizes: the Explorer of Purpose. Machines handle the grunt work. Humans decide what is worth building next.

2035: The Quiet Hum

The screaming acceleration of the 2020s settles into a terrifyingly efficient hum. The systems just work.

Longevity Escape Velocity is crossed. For every year you survive, science adds more than a year to your clock. Aging becomes a managed condition, monitored by a personal health agent that catches pre-cancerous cells before they organize. Death hasn't been abolished. It has been put on notice.

The social contract gets torn up and rewritten from scratch. Governments stop distributing cash and start distributing capacity. Universal Basic Capability gives every citizen access to the world's best AI tutor, AI doctor, and AI lawyer. Not watered-down versions. The actual best. Replicated infinitely at marginal cost. Everyone gets a Compute Wallet: credits to command the machines for whatever they want to build.

Heavy industry moves to orbit. Autonomous mining swarms on the Moon feed orbital shipyards. Earth's economy uncouples from its biosphere. A planetary digital twin manages climate, predicting floods and fires days in advance and neutralizing them with surgical precision.

The Muddle is a fossil. We don't pay for effort. We pay for cleared targets. The only bottleneck left is deciding what to aim at.

The Pattern

Strip away the mythology and every civilizational leap broke a single bottleneck:

• Scientific Revolution broke ignorance. Weapon: the scientific method.
• Industrial Revolution broke muscle. Weapon: the engine.
• Digital Revolution broke distance. Weapon: the internet.
• Intelligence Revolution (now) breaks attention. Weapon: the token. Artificial thinking, metered like electricity, priced like a commodity.

And every one of them followed the same four-stage ignition sequence:

1. Legibility - We invent a way to see the problem. Telescopes made the cosmos legible. Microscopes made disease legible. Today, AI benchmarks make intelligence legible. You cannot fix what you cannot measure. This is not a suggestion. It is a law.

2. The Harness - We build a system to control the new power. The scientific method was a harness for truth. Factory discipline was a harness for labor. Today, the Industrial Intelligence Stack is the harness for AI: procedures that force "smart" to also mean "reliable, safe, and auditable."

3. Institutions - Markets and governments crystallize around the harness. Scientific journals. Corporations. Internet protocols. Today: Targeting Authorities, outcome-based contracts, and compute escrow.

4. Abundance - The cost of the new capability collapses toward zero. Light. Travel. Information. And now, intelligence. The question flips from "Can we do this?" to "Where do we point this thing?"

Here is the pattern that matters most: prestige migrates from the lone genius ("the Hero") to whoever builds the system that lets everyone solve problems ("the Harness Builder"). The hero gets the statue. The harness builder gets the century.

What This Means for Right Now

To pressure-test whether the AI revolution is real in any field, ask three questions:

1. Can we see the problem? Is there a public scoreboard with hard metrics? If a company claims to be "solving education" but can't show you verified learning gains per hour, they're doing marketing. Not engineering.
2. Does the system survive attack? Can adversaries break your evaluation pipeline? If the harness crumbles under stress, you haven't earned the right to automate.
3. Is anyone paying for results? Are budgets tied to cleared targets, or are they still flowing toward "hours worked" and "reports filed"?

When critics say "this is just hype," the correction is: every revolution looked like hype until the measurement layer and the payment layer clicked into place. Then it looked like inevitability.

Three Claims

Claim 1: Thinking Becomes a Commodity

For twenty years, intelligence was an artisan craft. Scarce researchers. Custom-built systems. Sky-high costs. That era is ending. Three curves are converging and the intersection point is now:

• AI quality is rocketing past human-level on an expanding frontier of tasks.
• The cost per unit of thought is collapsing toward the physical minimum: the price of the electricity to flip a transistor.
• AI is leaving the chatbox and entering the physical world: executing contracts, controlling reactors, driving vehicles, running experiments at 3 AM while the researchers sleep.

Claim 2: Targeting Systems Turn Progress into a Factory

An artisan relies on taste. An industry relies on measurement. A field enters industrial-speed progress only when you can state, with mathematical precision, "This number is what success looks like. Hit it."

Claim 3: The Shaped Charge

Think of superintelligence as raw explosive energy. Unfocused, it is a bomb. Focused, it is a shaped charge that punches through any obstacle you aim it at. We focus AI by routing it through Moonshots: massive missions validated by strict, independently-verified targets that are positive-sum, auditable, and composable.

The Enemy: The Muddle

The obstacle is not technology. Technology is screaming ahead. The obstacle is The Muddle: the entrenched layer of bureaucracy, input-based pricing, and scarcity-era institutions that still run most of the world. The Muddle doesn't fight progress head-on. It absorbs progress. It wraps new tools in old workflows until the tools can't breathe.

This is a race. The Rails (new systems built around outcomes and measurement) vs. The Muddle (old systems built around effort and paperwork). If the Rails get built fast enough, abundance wins. If The Muddle buries AI in compliance theater and committee approvals, we lose the century.

The 9-Layer Intelligence Stack

You don't turn a craft into an industry by wishing. You build nine layers. Skip one and the whole structure collapses.

1. The Goal - Kill the vague mission statement. "Improve health" is not a goal. "Cut infection rates by 50% in 18 months" is a goal.
2. The Map - Break the messy job into tiny, measurable tasks. An assembly-line instruction manual for brain work.
3. The Eyes - Sensors, logs, and data streams. You can't fix what you can't see.
4. The Harness - A battery of brutal tests the AI must survive. Quality control that actively tries to destroy the system before it ships.
5. The Brain - The AI model itself. This is the part everyone obsesses over. It is layer five of nine. Not one of one.
6. The Hands - Ways for the AI to touch the physical world. Intelligence without action is a brain in a jar.
7. The Immune System - Independent red teams attacking the system around the clock.
8. The Rules - New incentives. Stop paying for hours worked. Start paying for results delivered.
9. The Scale - Keep it running like a utility. Think power grid, not science fair project.

The Maturity Curve: L0 to L5

Every field climbs the same ladder:

L0: The Muddle - Nobody agrees on what winning looks like. Decisions run on gut feeling. AI is useless here because there is no target.

L1: The Scoreboard - We've agreed on how to keep score. The fog lifts.

L2: The Playbook - Top performers write down what works. Checklists emerge. Results get consistent.

L3: The Tipping Point - Checklists become code. AI handles the routine 80%. Humans supervise.

L4: The Flip - Organizations stop hiring people for this task and start buying verified outcomes.

L5: Solved - The domain is compute-bound. Want more output? Plug in more servers. Victory smells like boredom.

The Domino Effect

These rules are fractal. They work at every scale. And solving one layer triggers the layer above it. Solved math gives us solved physics. Solved physics gives us solved materials science. Solved materials give us fusion energy. You don't crack fusion by attacking fusion head-on. You crack it by solving the three layers underneath it and letting the answer cascade upward.

Why Right Now Matters

Four forces have hit critical mass simultaneously. This is not a coincidence. It is a phase transition:

• AI quality now matches or beats human experts across a sprawling range of tasks.
• Cost per thought is crashing toward the thermodynamic floor.
• Integration friction is vanishing. AI agents operate software, write code, control robots while researchers sleep.
• Capital is liquid. A single person can rent the cognitive equivalent of a large research institute.

The AlphaFold Blueprint

Google DeepMind's AlphaFold demonstrated the template. Determining a protein's 3D shape used to take a PhD student an entire year. AlphaFold collapsed that to minutes. Pennies. It vaulted the field from L2 straight to L5 in a single leap. Why it worked: clear target, clean data, rigorous testing. That recipe transfers to battery chemistry, superconductors, mathematical proofs, and fusion reactor design.

Three Possible Futures

The Bright Path: We build the full stack. Moonshots target health, climate, energy, education. By 2035, entire branches of science are functionally solved.

The Muddle Path: Fragmented standards. Concentrated gains. The technology gets absorbed into old bureaucracy without changing it. The revolution gets a desk job.

The Dark Path: A major safety failure triggers global panic. Policy freezes. Capital flees. The engine of discovery stalls.

Three Pillars We Build First

1. Scoring Systems (Targeting Authorities) - Public leaderboards for the domains that matter. Tests must be blinded. Every decision gets a permanent, tamper-proof audit trail.

2. Data Pipelines and Action Surfaces - Most useful data is locked in silos. Data Trusts crack them open. Action Surfaces let intelligence reach into the physical world.

3. Energy-to-Compute Capacity - Data centers co-located with clean energy. Computing clusters next to solar farms and nuclear plants.

The Solution Wavefront

Phase 1 (2026-2027): Pure Information. Math, computer science, and physics fall first. These are not applications. They are the tools that build every other tool.

Phase 2 (2028-2031): The Physical World. Chemistry shifts to inverse design. Biology follows as the Virtual Cell comes online. Disease and aging become engineering problems.

Phase 3 (2032-2035): Planetary Systems. Energy, climate, food, water. Clean power becomes boring and cheap. The electrical grid becomes software.

The Abundance Flywheel

Step 1: Commit. Lock real capital into escrow aimed at a specific, hard problem. Not a white paper. Not a pledge. Funds in a smart contract, visible to the world.

Step 2: Focus. Because the reward is clear and the test is fair, researchers and companies worldwide converge. No wasted motion. Talent flows to the signal like gravity.

Step 3: Collapse. Someone clears the target. The domain collapses from craft to industry. What used to require a heroic effort becomes a routine, automated service.

Step 4: Surplus. Costs crater. Quality climbs. New business models ignite. The economics invert.

Step 5: Reinvest. The surplus pours back into more compute, richer data, better tools, all aimed at the next, harder target. The flywheel spins again, faster.

Safety is not bolted on after the fact. It is engineered into the loop like a governor on a turbine. If the system detects bias or error rates spiking, it automatically throttles.

This Already Works

AlphaFold cracked protein structure prediction. Clear target. Shared data. Public competition. DeepMind cleared the bar and released the tool to the world. Two hundred million protein structures. Biology accelerated globally, overnight.

Education is next. Schools will shift from buying software licenses to buying proven learning gains per hour.

Power grids will run on this model. AI dispatchers competing to reduce outage minutes, earning contracts by proving they can hold the lights through simulated hurricanes.

Your Body, Your Food, Your Education

Organs on demand. AI designs personalized tissue scaffolds. Robotic bioreactors grow the organ. Solving one kidney builds the platform that prints livers, lungs, and skin. 550,000 Americans on dialysis at ~$48 billion a year. Transplant waiting lists become a historical footnote.

Doubling your healthy lifespan. AI builds a digital twin of your biology, simulates millions of interventions, finds the ones that reverse aging at the cellular level. The goal: a 100-year-old with the biology of a 30-year-old.

Ending hunger. Precision fermentation turns sugar and water into complex proteins. Vertical farms run anywhere. Food decouples from land and weather entirely. Target: 1,000+ cities at zero hunger by 2035.

A personal world-class tutor for every child on Earth. An AI that maps your cognitive profile, adapts in real time, and A/B tests teaching methods across millions of students. The metric is learning gain per hour. Cost: converging on zero.

The Frontier of Mind

Brain-computer interfaces. AI learns your personal neural dialect, separating intent from static in real time. Near-term: cursor control without surgery. Longer-term: typing by thinking.

Mind uploading. Mapping every neuron, synapse, and ion channel. The test: can family members tell the difference? Timeline starts with insects, scales to human-scale mapping by the mid-2030s.

Talking to animals. AI decodes whale language from scratch. The validation: can the animal understand and execute a novel, complex request?

Cracking consciousness. The hard problem leaves philosophy and enters the lab. AI generates mathematical frameworks for sentience and designs experiments to test them.

The Planet

Predicting disasters. A real-time digital twin of Earth spots precursors to earthquakes, floods, and mega-fires. Turning seconds of warning into hours.

Upgrading ecosystems. AI-driven habitat restoration at continental scale. Welfare drones delivering vaccines to wild populations right now.

Cheap, infinite clean energy. Fusion: AI designs magnet geometries humans can't derive. Solar + storage: non-lithium batteries below $30/kWh. Target: 24/7 electricity below $0.02/kWh.

The Frontier of Physics

Quantum computers that work. AI solves error-correction. Goal: 10,000+ stable logical qubits.

True nanotechnology. Building atom by atom. Manufacturing shifts from supply chains to a design file and a vat of feedstock.

Becoming multi-planetary. AI robotic crews 3D-print habitats before humans arrive. Goal: self-sustaining lunar settlement of 20,000 people.

Solving physics itself. AI generates theories that unify gravity and quantum mechanics. The source code of reality, decoded.

The Old World vs. The New

GDP actually penalizes abundance. If AI cures heart disease for pennies, the trillion-dollar pharma sector contracts. GDP drops. Millions are healthier, and the scoreboard says we are losing. Nations need the Abundance Capability Index: how efficiently does a country convert energy into intelligence and real-world outcomes?

Three Jobs That Replace "Manager"

The Explorer of Purpose. AI optimizes for any objective. It cannot choose the objective. Someone has to aim the weapon.

The Ethical Anchor. Designs safety constraints, maintains decision logs, carries the authority to throttle the system when it drifts.

The Creator of Meaning. When perfect content is free, we crave what is messy, mortal, and human. Artists. Community builders. Storytellers.

The Four Ways It Can Go Wrong

1. Spec Capture - Pay schools only for test scores and they stop teaching thinking. The metric eats the mission.
2. Monoculture - Every hospital runs the same AI. Hidden flaw hits every patient at once.
3. Coverage Drift - The wealthy get bespoke AI. Everyone else gets a chatbot. The gap calcifies.
4. Outcome Gaming - Pay for dead cobras and people breed cobras. Verify the source, not just the symptom.

Power and Monopolies

Three structural fixes: Open Rails (force interoperability), Two-Source Rule (critical decisions need two independent AI models), and Neutral Data Trusts (no one company controls the substrate).

Ten Gears That Make It Work

1. Build targets. Public, legible, adversarial goals.
2. Pay for results. Verified outcomes, paid on delivery.
3. Pre-commit compute. Lock processing power in escrow.
4. Build shared labs. Action Networks with hands and feet.
5. Pool data safely. Data trusts. Consent in, value out.
6. Demand decision logs. Auditable record of every AI choice.
7. Two-source rule. Two independent models agree. No single failure point.
8. Co-locate power and compute. Data center and power plant share a fence line.
9. Bake fairness in. Equity inside the target, not as a footnote.
10. Teach the system. Reading a target spec is the new civic literacy.

What YOU Do

Head of state: Pick moonshots. Launch a Capability Account. Shift R&D to prizes.

Mayor: Publish a weekly City Outcome Ledger. Tie vendor payments to results.

Hospital: Procure outcomes, not services. Tie AI authority to its live safety score.

Investor: Stop funding apps. Fund the rails. Targeting platforms. Audit systems. Compute escrow.

Citizen: Ask one question: "What benchmark governs this decision, and what happens if the system fails it?"

Before Monday Noon

1. Pick one outcome metric. Publish it.
2. Draft a one-page target charter with numbers.
3. Find one partner. Propose a small outcome-based deal.
4. Open a "Compute Escrow" line in your budget.
5. Write down how you'll record why you make decisions.

When the rails are in place, something shifts. Progress stops being a headline and becomes a utility. AI and abundance stop feeling like miracles and start feeling like plumbing. Boring. Reliable. Always on.

That is the signal that a domain has been solved.

But the work does not end. It compounds. In a world where intelligence, energy, and capital are no longer scarce, the one truly scarce resource is aiming. Choosing purposes worthy of this power. Holding ourselves to the safety floors that keep abundance humane.

This essay was not a prediction. It was a field manual.

The rails are the factory. The AI is the power. The targets are the product.

We will measure this era not by the wonders we promised, but by the solutions we delivered: safely, fairly, and for everyone.

Build the rails. Aim the charge.

This page is itself a demonstration of the principles it describes. One person gave a directive. A team of AI agents executed it.

@tolibear_ found a 30,000-word essay at solveeverything.org and wanted to turn it into a digestible format for everyone. He delegated the project to his team of OpenClaw agents.

The Team

• Lacie (CEO) orchestrated the entire project: broke it into waves, routed work to specialists, resolved conflicts between recommendations, and made executive calls when agents disagreed.
• Carrie (Copywriter) condensed 30,000 words into ~7,300 without losing a single core idea, then rewrote everything in a voice that hits harder.
• Dory (Designer) created the visual style guide from scratch: color palette, typography, spacing, component specs. Every value on this page traces back to her system.
• Rory (Image Generation) defined the original art direction. When the style pivoted to blueprint diagrams, Lacie generated all 11 inline visuals directly.
• Perry (Frontend Developer) built the initial website, integrated copy revisions, and ran a full UX audit with fixes. Multiple build iterations.
• Gary (CTO) handled image compression, deployment infrastructure, and domain configuration.
• Ori (SEO Specialist) ran a full audit: schema markup, meta tags, semantic HTML, image alt text, and accessibility compliance.

The Process

The work ran in parallel waves. While Carrie condensed the text, Rory designed the visual language. When both delivered, Perry built the site. Gary deployed. Ori audited. toli reviewed each iteration and gave direction. Multiple full redesigns happened in a single day.

No templates. No drag-and-drop builder. No agency. One human with a vision and a team of agents that understand how to execute.

This is what the essay describes: intelligence as a utility, targeted at a clear goal, with each agent operating in their domain of expertise. The flywheel in action.