Living reference · openClaude project

Global Plan

The reference document for civilizational direction — a shared map for talking about where we are, where we are going, and the plan to manage the transition intentionally.

Version · 1.2 Date · April 2026 Author · Yoan Maisonneuve Status · Living document
Fields tracked 14 + 6 leverage points
Time horizon 2026 → 2040 4 phases
Control levels L0 → L4 Individual → Global
Fields in disruption 7 / 14 Compounding risk
Live · Channel 0

live atlas / 14 fields · 5 blocs

§ 0 · dashboard April 2026 snapshot
Rotate · hover · click
Critical High Medium
RADIUS · phase progress
HEIGHT · emergence → integration
COLOR · current bottleneck severity

// Focus

Hover a beacon Dashboard

14 field beacons around the globe

Each anchored where the revolution is most advanced
How to read Beacon height = how far through its revolution the field has traveled. Beacon color = severity of the current bottleneck. Hover any beacon to focus; click to jump to the field.

// Blocs

01 · USAMarket-led
02 · ChinaState-directed
03 · EURights-first
04 · SouthLeapfrog
05 · NordicsHybrid
Preamble · Channel I

why / point of reference

§ 0 · p. 01 / 03Read 4 min · Living document

Every podcast, every interview, every conversation about the future starts from scratch. Someone asks: "Where are we going?" and we answer from memory, from feeling, from the mood of the day.

There is no point of reference. No shared map. No document you can open and say: "Here. This is where we are. This is where we are going. This is the plan." This document fixes that.

01 · Direction
Not a prediction

A direction — measured against trigger conditions, not against forecasts.

02 · Living
Not complete

Updated as the world moves — quarterly review, event-triggered patches.

03 · Shared
Not for one person

For anyone who wants to talk about the plan with numbers and stages.

Preamble · Channel I

thesis / direction

§ 0 · p. 02 / 03Read 2 min · Core hypothesis
We are at the beginning of the largest transition in human history. The question is not whether it happens. The question is whether we manage it — or it manages us.

The transition is happening across every field simultaneously. That has never happened before. Every previous revolution — agricultural, industrial, digital — happened in one domain at a time. This one is happening everywhere at once.

Thesis

That is both the opportunity and the risk.

The plan is to manage this transition intentionally — with direction, with measurement, with human-AI collaboration at the center of execution.

State · Channel I

current state / april 2026

§ 0 · p. 03 / 03Read 5 min · Baseline

The world in numbers, and where human-AI collaboration sits today. Every projection in this document compares back against this baseline.

The World in Numbers

World population~8.2 BSlowing growth
Internet access~5.5 B67% · Growing
Regular AI users~500 MAccelerating
National AI strategies~60Growing
Global CO₂~425 ppmRising
Extreme poverty~700 MDeclining slowly
Literacy rate~87%Growing
Active conflicts~30+Volatile

Human-AI Collaboration State

Mature
Text generation

Bottleneck: quality control

Mature
Code generation

Bottleneck: trust + verification

Mature
Image / video gen

Bottleneck: distribution + copyright

Mature
Real-time translation

Bottleneck: cultural nuance

Early
Autonomous agents

Bottleneck: context + reliability

Early
Physical robots

Bottleneck: cost + dexterity

Emerging
Scientific discovery

Bottleneck: data + compute

Emerging
Policy simulation

Bottleneck: political will

Atlas · Channel II

fields / state, direction, plan

§ I · 14 fieldsRead 35 min · Phase + bottleneck per field

Each of the 14 fields below has the same anatomy: where we are, where we are going, the four-phase plan, the human–AI division of labor, and the ranked bottlenecks. Read any field in 90 seconds — read the bottleneck colors first.

Severity legendCriticalHigh · Medium
In disruption7 / 14Compounding instability
In emergence7 / 14Window before disruption
Plan horizon4 phases2026 → 2040+

F · 01 Human-AI Collaboration

The meta-field. Everything else depends on this.

DisruptionEarly · 1 critical

Where we are

  • AI is used as a search engine by most people
  • ~5% of users build systems with AI, 95% send single prompts
  • The bottleneck is not compute — it is human context quality
  • 80–90% of agent projects fail in production (RAND 2025) — cause: bad context

Where we are going

  • Every knowledge worker has an AI co-worker within 5 years
  • AI handles execution, humans handle vision and validation
  • New literacy: prompt engineering → system design → agent orchestration

The Plan

1
2026–2027
Establish protocols. Enter-game model. Solo founders first.
2
2027–2029
Small teams adopt human-AI hybrid workflows.
3
2029–2032
Institutional adoption. Governments, schools, hospitals.
4
2032+
Native AI integration. New generation builds AI-first by default.
// Tasks for AI

Context management, execution, documentation, monitoring, pattern detection.

// Tasks for humans

Vision, validation, ethics, relationships, creative direction, final decisions.

Bottlenecks

Critical
Context quality

Humans don't know how to give AI the right context.

High
Trust gap

People don't trust AI outputs enough to act on them.

High
Interface bandwidth

Voice/text is slow — neural interfaces 5–10 years away.

Medium
Regulatory lag

Laws written for pre-AI world.

Medium
Education gap

Most people have no framework for working with AI.

F · 02 Humanoid Robotics

The physical layer of AI. The bridge between digital intelligence and physical world.

EmergenceLate · 1 critical

Where we are

  • Boston Dynamics, Figure, Tesla Optimus, 1X — early commercial units
  • Cost: $20,000–$100,000 per unit (2026)
  • Dexterity: improving rapidly, not yet human-level
  • Deployment: factories, warehouses, labs — not homes yet

Where we are going

  • $5,000 consumer humanoid by 2030 (projected)
  • Factory replacement of repetitive physical labor within 10 years
  • Elder care, healthcare assistance within 15 years
  • Full domestic use within 20 years

The Plan

1
2026–2028
Industrial deployment — controlled environments.
2
2028–2032
Semi-public deployment — hospitals, schools, logistics.
3
2032–2037
Consumer deployment — elder care, home assistance.
4
2037+
Ubiquitous physical AI layer.
// Tasks for AI

Physical execution, repetitive labor, dangerous environments, precision tasks.

// Tasks for humans

Design, oversight, maintenance, ethical deployment decisions.

Bottlenecks

Critical
Cost

Not accessible at scale yet.

High
Dexterity

Fine motor tasks still unreliable.

High
Safety certification

Regulatory frameworks don't exist yet.

Medium
Social acceptance

Public fear and resistance.

Medium
Energy efficiency

Current units consume too much power.

F · 03 Energy

The foundation of everything. No transition is possible without energy abundance.

DisruptionMid · 2 critical

Where we are

  • Renewables: ~30% of global electricity (2026)
  • Solar cost: down 90% in 10 years — now cheapest energy source in history
  • Nuclear fusion: first net-energy experiments successful (NIF, 2022–2025)
  • Battery storage: scaling rapidly, cost dropping
  • Fossil fuels: still ~70% of total energy (not just electricity)

Where we are going

  • 50% renewable electricity by 2030 (current trajectory)
  • Grid-scale battery storage solving intermittency within 5 years
  • Commercial fusion power: 2035–2045 (optimistic)
  • Energy abundance scenario: possible within 20 years

The Plan

1
2026–2030
Accelerate solar + wind + storage deployment.
2
2028–2035
Nuclear fission renaissance + small modular reactors.
3
2032–2040
First commercial fusion plants.
4
2040+
Post-scarcity energy — changes everything downstream.
// Tasks for AI

Grid optimization, demand forecasting, materials discovery for better batteries, fusion plasma control.

// Tasks for humans

Policy, infrastructure investment, community transition management.

Bottlenecks

Critical
Grid infrastructure

Old grids can't handle distributed renewables.

Critical
Political will

Fossil fuel interests slow transition.

High
Storage at scale

Seasonal storage not solved yet.

High
Fusion timeline

Still 10–20 years away commercially.

High
Equitable access

Energy poverty in Global South.

F · 04 Education

The multiplier. Every other field scales with education quality.

EmergenceLate · 1 critical

Where we are

  • Global literacy: 87% — but functional literacy much lower
  • Access to quality education: deeply unequal by geography and income
  • University model: increasingly expensive, increasingly questioned
  • AI tutoring: early but promising — Khan Academy, Duolingo, etc.
  • Most school systems still designed for industrial-era workforce

Where we are going

  • Personalized AI tutor for every child within 5 years (access permitting)
  • Credential system disruption — skills over degrees
  • Lifelong learning as default — retraining every 5–7 years
  • Education in any language, any level, on demand

The Plan

1
2026–2028
AI tutoring tools deployed in underserved regions.
2
2028–2032
Curriculum redesign — AI literacy as core subject.
3
2032–2037
Credential system rebuilt around demonstrated skills.
4
2037+
Education fully personalized and continuous.
// Tasks for AI

Tutoring, content generation, progress tracking, curriculum adaptation, translation.

// Tasks for humans

Mentorship, values transmission, social development, creativity, critical thinking.

Bottlenecks

Critical
Device + internet access

1.3B children still without reliable internet.

High
Teacher resistance

System incentives don't reward AI adoption.

High
Language coverage

Most AI tools still English-dominant.

High
Curriculum inertia

Governments slow to update standards.

Medium
Measurement

No good metrics for AI-augmented learning outcomes.

F · 05 Health

The most personal field. The one where failure is measured in lives.

E → DTransition · 1 critical

Where we are

  • AI diagnostics: outperforming humans in radiology, dermatology, pathology
  • Drug discovery: AlphaFold changed protein folding — hundreds of new targets
  • Longevity research: accelerating — Altos Labs, Calico, etc.
  • Mental health crisis: global, worsening, massively underserved
  • Healthcare access: 50% of world has no access to essential health services

Where we are going

  • AI-first diagnostics standard within 10 years
  • Personalized medicine — treatment tailored to your genome within 15 years
  • First meaningful lifespan extension therapies within 20 years
  • Mental health: AI companions + therapists handling volume crisis

The Plan

1
2026–2029
AI diagnostic tools deployed at scale in underserved regions.
2
2029–2033
Genomic medicine mainstreamed in wealthy countries.
3
2033–2038
Longevity therapies enter clinical use.
4
2038+
Radical life extension — societal redesign required.
// Tasks for AI

Diagnostics, drug discovery, patient monitoring, mental health support, data analysis.

// Tasks for humans

Surgery, bedside care, ethics, end-of-life decisions, relationships.

Bottlenecks

Critical
Regulatory speed

FDA/EMA approval timelines built for pre-AI era.

High
Data privacy

Health data needed for AI — privacy laws slow sharing.

High
Healthcare inequality

Best tools go to richest first.

High
Mental health workforce

Not enough therapists — AI helps but can't replace.

Medium
Trust in AI diagnosis

Patients and doctors slow to trust AI over human judgment.

F · 06 Economy

The operating system of civilization. How value is created, distributed, and measured.

DisruptionEarly · 1 critical

Where we are

  • AI is beginning to replace knowledge work at scale
  • Wealth concentration at historic highs
  • GDP as metric increasingly inadequate
  • New economic models emerging: UBI pilots, platform cooperatives, DAOs
  • ~1.4 billion unbanked people globally

Where we are going

  • 30–40% of current jobs significantly transformed by AI within 10 years
  • New job categories emerging faster than old ones disappear (historically true)
  • Universal basic services (not just income) as political reality within 20 years
  • AI-generated value redistribution: the central political question of the 2030s

The Plan

1
2026–2029
Document job transformation in real time — build the map.
2
2029–2033
Retraining infrastructure built at national scale.
3
2033–2038
New economic metrics replace/supplement GDP.
4
2038+
Post-scarcity economics in leading nations — export the model.
// Tasks for AI

Economic modeling, fraud detection, financial inclusion tools, market optimization.

// Tasks for humans

Policy, redistribution decisions, community economic design, values.

Bottlenecks

Critical
Political will for redistribution

Incumbent wealth resists structural change.

High
Speed of job transformation

Retraining systems too slow for pace of change.

High
Measurement gaps

Can't manage what you can't measure.

High
Financial exclusion

1.4B unbanked — invisible to formal economy.

Medium
Global coordination

Race to bottom on tax + regulation.

F · 07 Pollution & Environment

The bill for the last 200 years of growth. Due now.

DisruptionMid · 2 critical · Lagging

Where we are

  • CO2: 425ppm and rising — 1.5°C target likely missed
  • Plastic: 400M tons produced annually, ~10M tons enter oceans yearly
  • Biodiversity: 6th mass extinction underway — 1M species at risk
  • Air quality: 7M deaths per year from air pollution
  • Water: 2B people lack safe drinking water

Where we are going

  • Carbon removal at gigatonne scale required by 2030 (not yet happening)
  • Biodiversity loss: accelerating without intervention
  • Circular economy: growing but not yet mainstream
  • Climate migration: 200M–1B people displaced by 2050 (range of estimates)

The Plan

1
2026–2028
AI-powered pollution monitoring deployed globally.
2
2028–2032
Carbon removal technology scaled — direct air capture + bio.
3
2032–2038
Circular economy mandated in G20 nations.
4
2038+
Planetary restoration — active ecosystem rebuilding.
// Tasks for AI

Emissions monitoring, climate modeling, materials discovery, supply chain optimization, early warning systems.

// Tasks for humans

Policy, enforcement, community adaptation, restoration work.

Bottlenecks

Critical
Political coordination

No binding global enforcement mechanism.

Critical
Carbon removal cost

Direct air capture still $300–500/ton — needs 10x reduction.

High
Speed vs. scale

Solutions exist but not scaling fast enough.

High
Corporate accountability

Emissions reporting still voluntary in most jurisdictions.

Medium
Climate grief

Psychological barrier to action — too big to process.

F · 08 Peace & Conflict

The prerequisite. Nothing else works under bombs.

DisruptionMid · 2 critical · Destabilizing

Where we are

  • 30+ active conflicts globally
  • Nuclear arsenal: ~12,500 warheads across 9 countries
  • Autonomous weapons: being developed by multiple nations — no treaty yet
  • Disinformation: AI-generated content destabilizing elections and trust
  • UN Security Council: structurally gridlocked

Where we are going

  • AI-powered conflict prediction within 5 years (already emerging)
  • Autonomous weapons proliferation: the arms race is already happening
  • Disinformation: getting worse before it gets better
  • Peace architecture: needs fundamental redesign for multipolar world

The Plan

1
2026–2028
AI conflict early warning systems deployed in partnership with UN.
2
2028–2032
International treaty on autonomous weapons — like Chemical Weapons Convention.
3
2032–2037
Disinformation detection infrastructure built into platforms globally.
4
2037+
New global governance architecture — beyond the 1945 model.
// Tasks for AI

Conflict prediction, disinformation detection, treaty verification, diplomatic translation.

// Tasks for humans

Negotiation, governance design, community reconciliation, justice.

Bottlenecks

Critical
Great power competition

US/China/Russia dynamic blocks coordination.

Critical
Autonomous weapons race

No binding treaty — every nation racing.

High
Trust deficit

Decades of broken agreements erode negotiating base.

High
Disinformation velocity

AI generates faster than humans can verify.

High
UN structural limits

Veto power paralyzes response to major conflicts.

F · 09 Cities

Where 56% of humanity lives — and 70% will by 2050. The unit of real change.

EmergenceMid · 1 critical

Where we are

  • 4.4 billion people in cities today — 10,000 people move to cities every hour
  • Most cities still designed for cars, not people
  • Housing affordability crisis in every major city globally
  • Urban heat islands intensifying — cities 3–5°C hotter than surrounding areas
  • Mayors increasingly more effective than national governments on execution

Where we are going

  • Smart city infrastructure: AI-managed traffic, energy, water, waste
  • 15-minute city model spreading — everything accessible by foot or bike
  • Climate-resilient city redesign — mandatory within 15 years in flood/heat zones
  • Cities as the primary unit of policy experimentation

The Plan

1
2026–2029
AI urban management pilots in 50 cities globally.
2
2029–2033
15-minute city model adopted in 500 cities.
3
2033–2038
Climate-resilient redesign — new building codes, flood infrastructure.
4
2038+
Cities as autonomous governance units — more power than states in some domains.
// Tasks for AI

Traffic optimization, energy grid management, predictive maintenance, urban planning simulation, housing allocation modeling.

// Tasks for humans

Community design, zoning decisions, political accountability, social cohesion.

Bottlenecks

Critical
Housing supply

Zoning laws block density — political resistance from homeowners.

High
Infrastructure age

Most city infrastructure built 50–100 years ago.

High
Data silos

City departments don't share data — AI can't optimize what it can't see.

High
Political fragmentation

Cities split across jurisdictions — no unified decision authority.

Medium
Climate retrofit cost

Retrofitting existing buildings is expensive and slow.

F · 10 Governance & Government

The operating system of societies. Currently running on 1945 architecture.

EmergenceEarly · 2 critical

Where we are

  • Most democratic institutions designed pre-internet, pre-AI
  • Trust in government at historic lows in most democracies
  • AI already influencing elections via targeting and disinformation
  • No country has a fully coherent AI governance framework yet
  • Regulatory speed: months to years. AI development speed: weeks.

Where we are going

  • AI-assisted legislation: drafting, simulation, impact modeling within 5 years
  • New governance models emerging: liquid democracy, participatory budgeting, AI advisors
  • Regulatory frameworks for AI: the arms race between regulators and developers
  • National AI strategies becoming as important as defense strategies

The Plan

1
2026–2028
AI policy simulation tools deployed in 20+ governments.
2
2028–2032
New regulatory frameworks for AI — international coordination begins.
3
2032–2037
Governance model experimentation at city/regional level — new models proven.
4
2037+
Constitutional redesign in leading democracies — built for AI age.
// Tasks for AI

Policy simulation, budget optimization, service delivery, fraud detection, public sentiment analysis.

// Tasks for humans

Legislation, justice, representation, accountability, values setting.

Bottlenecks

Critical
Regulatory lag

Laws take years — technology moves in weeks.

Critical
Institutional inertia

Bureaucracies designed to resist change.

High
Lobbying power

Incumbent industries write the rules.

High
Democratic backsliding

60+ countries becoming less democratic (V-Dem 2025).

High
AI in elections

No agreed rules on AI-generated political content.

F · 11 Companies & Organizations

The execution layer of the economy. The fastest-moving actors in the transition.

DisruptionEarly · 1 critical

Where we are

  • Fortune 500 companies: ~60% have AI initiatives, ~15% have deployed at scale
  • Startups: AI-native companies now built in weeks not years
  • SMEs: mostly not using AI — the silent majority
  • New org model emerging: 1 founder + AI agents = team of 10
  • Corporate AI governance: almost nonexistent

Where we are going

  • Every company becomes an AI company or becomes irrelevant within 10 years
  • New corporate structures: AI agents as legal entities (experimental in some jurisdictions)
  • Company size distributions shift — fewer large companies, more micro-companies
  • B2B AI tools market: $500B+ by 2030

The Plan

1
2026–2028
SME AI adoption tools — simple, affordable, voice-first.
2
2028–2032
AI governance frameworks standardized — ISO equivalent for AI use.
3
2032–2037
New corporate legal structures for human-AI hybrid entities.
4
2037+
Most companies are AI-native — legacy structures extinct.
// Tasks for AI

Operations, customer service, data analysis, forecasting, compliance monitoring.

// Tasks for humans

Strategy, culture, client relationships, ethics, creative direction.

Bottlenecks

Critical
SME adoption gap

90% of companies are SMEs — most not using AI.

High
Change management

Employees resist AI adoption — cultural barrier.

High
AI governance void

No standards for responsible AI use in business.

High
Talent concentration

AI talent concentrated in 20 companies globally.

Medium
IP and liability

Who owns AI output? Who is liable for AI errors?

F · 12 People & Individuals

The unit everything is built for. Often forgotten in the macro conversation.

EmergenceEarly · 2 critical

Where we are

  • The average person has no framework for navigating this transition
  • Mental health crisis accelerating — loneliness, anxiety, loss of meaning
  • Identity disruption: jobs, skills, roles being redefined faster than people can adapt
  • Growing divide: AI-augmented people vs. non-augmented people
  • Most people experience AI as a tool they use occasionally — not a collaborator

Where we are going

  • Every person has a personal AI system within 10 years
  • New human identity questions: what is uniquely human when AI does everything?
  • New social contracts: what do you owe society when AI generates your income?
  • The augmented individual: AI as cognitive extension — not replacement

The Plan

1
2026–2028
AI literacy as basic life skill — taught everywhere, free.
2
2028–2032
Personal AI systems accessible to everyone — not just tech elite.
3
2032–2037
New social support systems for AI transition — retraining, income, meaning.
4
2037+
New definition of human flourishing in AI-abundant world.
// Tasks for AI

Personal assistant, health monitoring, learning support, career navigation, scheduling.

// Tasks for humans

Relationships, creativity, values, parenting, community, meaning-making.

Bottlenecks

Critical
Mental health crisis

Epidemic of loneliness and anxiety — AI accelerates it without intervention.

Critical
AI literacy gap

Most people have no framework for using AI effectively.

High
Access inequality

AI augmentation available to rich first — widens inequality.

High
Identity disruption

People losing sense of purpose as AI takes their work.

Medium
Trust and addiction

Risk of over-reliance on AI at expense of human connection.

F · 13 Food & Agriculture

Feeds 8 billion people. One of the most vulnerable systems to climate change.

EmergenceMid · 2 critical

Where we are

  • ~800M people chronically undernourished
  • Agriculture uses 70% of global freshwater
  • Food systems responsible for ~30% of global greenhouse gas emissions
  • Crop yields threatened by climate change — 2–6% decline per decade projected
  • Vertical farming + precision agriculture: early commercial scale

Where we are going

  • AI-optimized precision agriculture mainstream within 10 years
  • Lab-grown protein: price parity with conventional meat by 2030
  • Vertical farming: economically viable for leafy greens, expanding
  • Supply chain visibility: full traceability from farm to fork

The Plan

1
2026–2029
AI precision agriculture deployed across top 20 food-producing nations.
2
2029–2033
Lab-grown protein at scale — 10% of global protein supply.
3
2033–2038
Vertical farming mainstream in urban areas — reduces transport emissions.
4
2038+
Decoupled food production from land and weather dependency.
// Tasks for AI

Crop optimization, pest prediction, supply chain management, demand forecasting, soil health monitoring.

// Tasks for humans

Farming decisions, food culture, community food systems, policy.

Bottlenecks

Critical
Climate impact on yields

Unpredictable weather threatening food security.

Critical
Water scarcity

Agriculture consumes 70% of freshwater — aquifers depleting.

High
Lab-grown protein cost

Not yet price-competitive at scale.

High
Smallholder adoption

500M smallholder farms — AI tools not designed for them.

Medium
Political food sovereignty

Countries resist dependency on foreign food tech.

F · 14 Mental Health & Social Cohesion

The invisible crisis. The foundation of everything else.

DisruptionMid · 1 critical

Where we are

  • 1 billion people globally living with a mental health condition
  • Loneliness declared an epidemic by WHO (2023)
  • Therapist shortage: 1 psychiatrist per 200,000 people in low-income countries
  • Social trust declining in most Western democracies for 20+ years
  • AI companions emerging — helpful and concerning simultaneously

Where we are going

  • AI mental health support at scale within 5 years — necessary, not optional
  • New social architectures needed — digital life redesigned for connection not engagement
  • Community rebuilding as political priority in post-COVID era
  • Psychedelic-assisted therapy: regulatory approval accelerating

The Plan

1
2026–2028
AI mental health triage deployed — bridges therapist shortage.
2
2028–2032
Digital platform redesign — regulation forcing social connection over engagement.
3
2032–2037
Community infrastructure rebuilt — physical third places, local governance.
4
2037+
Social cohesion as measured national priority — tracked like GDP.
// Tasks for AI

Triage, CBT delivery, crisis detection, peer matching, therapist support tools.

// Tasks for humans

Deep therapy, community building, relationships, grief, meaning.

Bottlenecks

Critical
Therapist shortage

Cannot train enough humans fast enough.

High
Stigma

Mental health still stigmatized in most cultures.

High
Platform incentives

Social media optimized for engagement not wellbeing.

Medium
AI companionship risk

Risk of replacing human connection rather than supplementing.

Medium
Measurement

No good global metric for social cohesion.

Cross-cut · Channel III

leverage / points that move all fields

§ II · p. 01 / 04Read 3 min · 6 universal levers

Some forces touch every field at once. Move these and the whole map shifts — leave them stuck and every field-level plan stalls.

All fields
AI alignment

Misaligned AI is an existential risk across every field.

All fields
Energy abundance

Every field scales with cheap, clean energy.

All fields
Education quality

Every solution requires humans who can implement it.

All fields
Trust in institutions

Low trust blocks coordination at every level.

All fields
Global governance

Problems are global, institutions are national.

All fields
Human–AI interface

Bandwidth between human brain and AI systems is the bottleneck.

Lever

A single-field breakthrough delivers linear impact. A leverage-point breakthrough compounds across all 14 fields.

Budget, attention, and political capital should flow here first — then to field-specific work.

Cross-cut · Channel III

adoption / the human bottleneck

§ II · p. 02 / 04Read 12 min · Most critical section

Everything else in this document is theory until humans choose to engage. Right now, human adoption is the single biggest bottleneck across every field — not technology, not funding, not regulation. People.

Premise

You can build the best AI tutor, the best diagnostic, the best clean grid, the best urban management system.

If humans don't adopt — nothing moves.

The adoption chain — how it actually works

HIGH MORALE LOW TIME → 80% DROPOUT ZONE 01 tech appears 02 first contact 03 · VALLEY 80% drop out 04 20% find value 05 critical mass

Adoption chain · the 80% dropout at stage 03 is where every revolution dies or survives

New technology appears
        ↓
Person hears about it (awareness)
        ↓
Person feels threatened or curious (emotional response — not rational)
        ↓
Person tries it once (first contact)
        ↓
[THE VALLEY OF DESPAIR]
Person struggles, feels incompetent, questions why they're doing this
        ↓
80% drop out here
        ↓
20% push through → find first value moment
        ↓
Person tells someone they trust (social proof)
        ↓
That person tries — cycle repeats
        ↓
Critical mass → cultural shift → new normal
Valley

The valley of despair is where revolutions die.

Not from lack of technology. From lack of support at the moment of struggle.

The four prerequisites for human adoption

Before a person can adopt any new system — AI, clean energy, new governance model — four things must be true. In order. They cannot be skipped.

01 · Safety
Not destroyed by this

"I am not going to be destroyed by this."

02 · Trust
Someone I respect

"Someone I respect has done this and it worked."

03 · Relevance
A problem I actually have

"This solves a problem I actually have right now."

04 · Capability
I have been shown how

"I can do this — I have been shown how."

Failure mode

Most adoption programs start at 4 · Capability.

They fail because 1, 2, and 3 are not in place.

The self-reinforcing failure loop

The mental health crisis (Field 14) and the adoption bottleneck are not separate problems. They are the same problem expressing itself in two domains.

AI transition accelerates
        ↓
Jobs become uncertain → identity threatened → anxiety rises
        ↓
Mental health deteriorates
        ↓
Cognitive bandwidth shrinks — person cannot learn new systems
        ↓
Person falls further behind in adoption
        ↓
Gap between them and AI-augmented peers widens
        ↓
Anxiety worsens → mental health deteriorates further
        ↓
[LOOP]
Intervention

This loop is already running at scale in 2026. It is invisible in most adoption metrics because we measure technology deployment, not human readiness.

Breaking the loop requires intervening at the mental-health layer first — not the technology layer.

This plan as a companion — not a document

A document does not create engagement. A relationship does. This global plan is designed to function as a companion — something a person, a company, a government can return to repeatedly and find themselves in it.

Old model

  • Plan is presented to people
  • Experts hold the direction
  • Progress is reported top-down
  • Adoption is measured at scale
  • The plan is static

Companion model

  • People find themselves in the plan
  • Direction is shared and navigable by anyone
  • Progress is visible and trackable by every actor
  • Adoption is felt at the individual level
  • The plan reflects reality as it changes

How to use this plan to create engagement

01 · Individual

With an individual

  1. Ask: "Which of these fields is most present in your life right now?"
  2. Show them where that field is on the phase map.
  3. Name the bottleneck closest to their situation.
  4. Ask: "What would it mean if that bottleneck moved one level down?"
  5. Give them one concrete action connected to the transition.
  6. Come back to the same document next time — show them the delta.
02 · Company

With a company

  1. Map their business against the field table — which fields do they touch?
  2. Show them which phase those fields are in.
  3. Show them the trigger conditions for the next phase.
  4. Ask: "What does your company need to be when that trigger fires?"
  5. Build the internal plan backward from that moment.
03 · Government

With a government

  1. Show them the geopolitical dimension — where is their country vs peers?
  2. Identify which fields are in Disruption in their jurisdiction now.
  3. Name the bottleneck that is costing them the most.
  4. Show them the control layer — which level is their mandate?
  5. Give them the metric that will move if they act.
04 · Public conversation

Podcast / public stage

  1. Name the feeling first — the world is moving faster than people can keep up. That is not personal failure; it is the Disruption signal.
  2. Then name where we are on the map.
  3. Then show the direction.
  4. Then give the bottleneck — honest, specific, not catastrophizing.
  5. End with agency — what one person, one company, one city can do today.
Key

Abstract plans create observers. Personal maps create actors.

The goal of every public conversation: the listener finishes feeling oriented, not overwhelmed.

The companion relationship — how this document evolves

This plan is not a static manifesto. It is a living companion that grows in two directions simultaneously: downward — more detail, more fields, more precision; outward — more people contributing to it, more languages, more contexts.

01 2026

One document, one author, one language.

02 2027

Multiple contributors, multiple languages, public version.

03 2028

Interactive — people see their city, their field, their metric.

04 2030

Real-time — metrics auto-update from public data sources.

05 2035

AI-native — the companion talks back, adapts to the person.

The performance layer — innovation as direction, not destination

The ultimate goal of human adoption is not compliance with a plan. It is performance — humans and AI operating together at the edge of what is possible. Performance means: faster cycle time from idea to implementation, higher-quality decisions from better context, more ambitious goals because the tools exist to pursue them, less energy wasted on fear, uncertainty, and repeat mistakes.

Measure

The measure of success is not how many people have read this document.

It is how many people are operating at a higher level of performance because they found their direction in it.

Terrain · Channel II/III interlude

topography / world lifted by its revolutions

§ cinematic · drift 14 peaks · continents
orbital camera
Critical peak High peak Medium peak
ELEVATION · revolution progress
PEAKS · 14 fields at geographic anchors
CAM · slow orbital drift · no input
// breath Same 14 fields — rendered as topography. Mountains rise where disruption is deepest, plains hold where emergence has not yet broken.
Tempo · Channel IV

phases / multiple revolutions at once

§ II · p. 03 / 04Read 5 min · Sequencing the integrations

Every field above is going through a revolution. The question is not whether — it is how to manage more than one at a time.

Disruption → Integration Integration zone Emergence → Disruption APRIL 2026 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Phase Compass · April 2026

Radial distance = revolution progress. Angle = field position. Color = bottleneck severity at current stage.

Critical High Medium
  1. 01Human–AI
  2. 02Robotics
  3. 03Energy
  4. 04Education
  5. 05Health
  6. 06Economy
  7. 07Pollution
  8. 08Peace
  9. 09Cities
  10. 10Governance
  11. 11Companies
  12. 12People
  13. 13Food
  14. 14Mental Health

The three phases of any revolution

01 Emergence

Technology exists. Few know it. Pioneers use it.

02 Disruption

Technology spreads. Old systems break. Chaos.

03 Integration

New normal established. Next revolution begins.

Phase trigger conditions

Emergence → Disruption

  • Adoption crosses 10% of target population, or
  • Cost drops 10×, or
  • A major institution adopts publicly.

Disruption → Integration

  • Adoption crosses 50%, or
  • Regulatory framework passed, or
  • Incumbent industry restructures around the new model.

Where each field is now (April 2026)

In Disruption7 / 14Compounding
In Emergence6 / 14Preparing
Transitioning1 / 14Health
Integrated0 / 14Frontier
Disruption
Human–AI collaboration

Stage: early disruption

Emergence
Humanoid robotics

Stage: late emergence

Disruption
Energy

Stage: mid disruption

Emergence
Education

Stage: late emergence

Transition
Health

Emergence → Disruption

Disruption
Economy

Stage: early disruption

Disruption
Pollution / Environment

Mid disruption · lagging response

Disruption
Peace / Conflict

Mid disruption · destabilizing

Emergence
Cities

Stage: mid emergence

Emergence
Governance

Stage: early emergence

Disruption
Companies

Stage: early disruption

Emergence
People / Individuals

Stage: early emergence

Emergence
Food / Agriculture

Stage: mid emergence

Disruption
Mental Health

Stage: mid disruption

Compounding

Health in disruption + economy in disruption + politics in disruption = cascading instability. This is where we are in 2026.

The plan is not to slow the revolutions. It is to sequence the integrations.

Time compression — each revolution faster than the last

Each revolution should take less time than the previous one. This is the meta-goal. Bar length uses log₁₀ scale — the drop from agricultural to post-AI is a 600× compression.

Revolution · Duration Years to 50% adoption
Agricultural01 · pre-history
~3,000 yrs
centuriesto 50%
Industrial02 · 1760 →
~150 yrs
~80 yrsto 50%
Digital03 · 1985 →
~40 yrs
~25 yrsto 50%
AI · current04 · 2022 →
~15 yrs projected
~8 yrsto 50%
Post-AI05 · 2035 →
~5 yrs projected
~3 yrsto 50%
Meta-goal

Why it compresses: each revolution builds better tools for managing the next one. AI is the first revolution that directly accelerates the management of revolutions. This document is part of that acceleration.

The target: cut emergence → integration time by 50% each cycle, by maintaining a live reference, tracking triggers, and pre-building transition infrastructure before disruption hits.

Ledger · Channel IV

metrics / how we measure progress

§ II · p. 04 / 04Read 4 min · 14 primary indicators

One primary metric per field. Baseline today, target 2030, target 2040. Divergence from these numbers is the signal — not the plan.

Baseline year2026April
Mid horizon20304 years
Long horizon204014 years
Review cadenceQuarterlyEvent-triggered

By field · primary indicator

FieldPrimary metric202620302040Trajectory
Human–AI% knowledge workers using AI daily~15%60%90%
263040
RoboticsCost of humanoid unit$50K$10K$2K
263040
Energy% global energy from renewables~15%35%70%
263040
Education% children with AI tutor access~5%40%85%
263040
Health% population with AI diagnostic access~10%35%75%
263040
EconomyGini coefficient (global wealth inequality)0.670.630.55
263040
PollutionAnnual CO₂ ppm increase+2.4 ppm/yr+1.0 ppm/yr−1.0 ppm/yr
263040
PeaceActive conflicts30+2010
263040
Cities% cities with AI urban management~3%20%60%
263040
GovernanceCountries with AI governance framework~1560120
263040
Companies% SMEs using AI regularly~10%40%80%
263040
People% population with personal AI system~8%35%75%
263040
Food% of farmland using precision agriculture~5%25%60%
263040
Mental HealthGlobal loneliness indexWorseningStableImproving
263040
Terrain · Channel V

geopolitics / same revolution, different speeds

§ III · p. 01 / 04Read 4 min · 5 blocs

The transition is global but not uniform. Five major blocs are moving at different speeds with different priorities — the first to demonstrate AI-augmented human flourishing at scale sets the model the world copies.

Bloc · 01

USA

ApproachMarket-led · fast · fragmented regulation
StrengthsSpeed, capital, talent concentration
RisksInequality · no social safety net for transition
Bloc · 02

China

ApproachState-directed · coordinated · controlled
StrengthsScale, speed, infrastructure investment
RisksAuthoritarian use of AI · limited individual rights
Bloc · 03

EU

ApproachRights-first · regulated · slower
StrengthsTrust, fairness, democratic legitimacy
RisksRegulatory overreach slowing innovation
Bloc · 04

Global South

ApproachLeapfrogging · mobile-first
StrengthsCan skip legacy infrastructure
RisksAI-dependency on other blocs
Bloc · 05

Canada / Nordics

ApproachHybrid · safety net + innovation
StrengthsBalance of speed and equity
RisksSmall population limits global influence

The risk

AI development fractures into incompatible ecosystems — like the internet splinternet, but for intelligence.

The opportunity

The first bloc to demonstrate AI-augmented human flourishing at scale sets the model the world copies.

Execution · Channel V

control / who is responsible for what

§ III · p. 02 / 04Read 5 min · 4 levels · 5 red lines

How we know the plan is working. Four levels, four cadences, four sets of actors — from the UN down to the single builder.

Control model · 4 levels

GLOBAL NATIONAL CITY / REGIONAL INDIVIDUAL / COMPANY L · 01 · ANNUAL L · 02 · QUARTERLY L · 03 · MONTHLY L · 04 · WEEKLY narrow wider widest TOP = NARROW AUTHORITY · SLOW CADENCE BASE = BROAD EXECUTION · FAST CADENCE
Global · 01UN · G20 · major NGOs — cross-field bottlenecks, conflict count, CO₂ ppm
Annual
National · 02Governments · central banks — country-level field metrics, policy adoption
Quarterly
City / Regional · 03Mayors · regional governments — local adoption, housing, infrastructure
Monthly
Individual / Company · 04Founders · builders · citizens — personal AI adoption, project execution
Weekly

The Enter-Game connection

This plan is not managed by a committee. It is managed by builders — individuals and small teams who execute at Level 04 and propagate change upward.

  • 1 founder with AI = a team of 10
  • 1,000 founders with AI = a company of 10,000
  • 1,000,000 builders with AI = a movement

enter-game is the on-ramp to this plan — where the individual plugs into civilizational direction.

Blueprint / aski01 connection

Blueprint / aski01 is the directional system — the cognitive architecture that helps individuals and organizations navigate across all fields and all time horizons simultaneously.

It is the navigation system for this map.

The global plan is the map. Blueprint is the compass.

Red lines — when to stop and reassess

Not all progress is good progress. These conditions trigger a full plan review.

Red line · 01
AI misalignment event

Any AI system causes significant unintended harm at scale.

Red line · 02
Democratic collapse

3+ major democracies become authoritarian within 5 years.

Red line · 03
Climate tipping point

Evidence of an irreversible tipping point crossed.

Red line · 04
Nuclear use

Any nuclear weapon used in conflict.

Red line · 05
Pandemic + AI

Biological weapon enhanced by AI is used.

Carrier · Channel V

talk / how to use this plan in conversation

§ III · p. 03 / 04Read 4 min · 5 contexts

A plan that cannot be spoken aloud is dead on arrival. These are the five carriers — each with a six-to-one-step protocol for the context you're in.

The three questions that structure every conversation

Q · 01
Phase

What phase is this field in right now?

Q · 02
Bottleneck

What is the biggest bottleneck and what level is it?

Q · 03
Transition

What does the move to the next phase require?

01 · Podcast / interview

When someone asks "where are we going?"

  1. Name the field — which revolution are we talking about?
  2. State where we are — use the metrics table.
  3. State where we're going — use the phase roadmap.
  4. Name the bottleneck — specific, named level.
  5. Name who does what — human tasks vs AI tasks.
  6. Give the number — countries, companies, people here vs there.
02 · Government official

With a government official

  1. Which field is their mandate?
  2. What phase is it in their country vs globally?
  3. What is the trigger condition for the next phase?
  4. What does government need to do vs what AI can do?
  5. What is the cost of delay? (X years behind = Y impact)
03 · Company / investor

With a company or investor

  1. Which fields does their business touch?
  2. Are they in Emergence, Disruption, or Integration?
  3. What is the bottleneck they are closest to solving?
  4. Where on the metrics table does their product move the needle?
04 · Individual

With an individual

  1. Which field is their daily life most affected by?
  2. What phase are they personally in — AI system or not?
  3. What is the one thing they can do today to move personally from Emergence to Disruption?
Protocol · Channel V

update / how this document evolves

§ III · p. 04 / 04Read 2 min · Living document

This is not a manifesto. It is a living reference — updated when reality diverges from the baseline.

Update triggers

  • A field crosses a phase boundary.
  • A major metric shifts > 10%.
  • A new cross-field dynamic emerges.
  • A new field needs to be added.

Command: update global plan [field]
Cadence: minimum quarterly review. Major events trigger immediate update.

What this document is not

  • Not a prediction — reality will diverge from every number here.
  • Not complete — new fields will be added.
  • Not consensus — one directional framework, not a political manifesto.
  • Not static — it evolves as the world evolves.
What it is

A point of reference.

A place to point to and say: here is the map, here is where we are, here is where we are going.

You don't start a company. You enter the game. You don't manage a revolution. You direct it.