Work
What is the purpose of work? When the org chart dies, what will work look like? How will work bee incentivized?
| Org Chart | Work Chart |
|---|---|
| Who reports to whom? | What work needs doing? |
| Where do you sit? | What can you do? |
| Career = climbing boxes | Career = expanding capabilities |
| Fixed roles | Fluid activities |
The Signal
Work Charts are the leading indicator of AI's impact on work. Not speculation—observable shifts in who does what, activity by activity.
WORK CHART = Activity × (Human Role + AI Role + AI % + Trend)
Track this and you see the future arriving.
Who Delegates to Whom?
Every activity involves delegation. The question is: in which direction?
| Direction | What It Means | Trend |
|---|---|---|
| Human → Human | Traditional delegation | Stable |
| Human → AI | Automation, augmentation | ↑↑ Accelerating |
| AI → Human | AI identifies what humans should handle | ↑ Emerging |
| AI → AI | Autonomous orchestration | Early signals |
The 2027 prediction thesis: When AI to AI delegation becomes standard, the loop becomes self-reinforcing, the prompters will become the prompted.
The Template
Map any function with this structure:
| Activity | Human Role | AI Role | AI % | Trend |
|---|---|---|---|---|
| [Specific task] | [What humans do best] | [What AI handles] | [Current split] | ↑ → ↓ |
Aggregate AI % = leading indicator for the function. Watch the trend, not the absolute number.
Example: Content Pipeline
From the content development process:
| Stage | Human Role | AI Role | AI % | Trend |
|---|---|---|---|---|
| ICP Definition | Defines psychology, validates insights | Researches behavior, synthesizes data | 40% | ↑ |
| Idea Capture | Judges idea value, selects what matters | Generates variations, expands concepts | 30% | → |
| Transform | Selects perspectives, directs voice | Writes drafts from each lens | 70% | ↑↑ |
| Qualify | Final judgment, merge decisions | Runs checklists, scores drafts | 50% | ↑ |
| Question | Decides ship vs iterate | Identifies gaps, suggests improvements | 35% | ↑ |
| Ship | Approves, owns distribution | Generates assets, formats, validates | 60% | ↑ |
Aggregate AI %: 47% — and rising.
Human edge: Judgment on what's worth saying, voice calibration, final quality gate.
AI edge: Volume, consistency, checklist execution, multi-perspective drafting.
The Human Edge
As AI handles more routine cognition, the human edge shifts:
| Era | Edge | Durable? |
|---|---|---|
| Yesterday | Knowledge (what you know) | Eroding fast |
| Today | Judgment (what you decide) | Still valuable |
| Tomorrow | Character (who you are) | Irreplaceable |
What remains when AI can do everything trainable?
- Selling — Trust requires skin in the game
- Purpose — Meaning can't be computed
- Ethics — Accountability needs a who, not a what
- Taste — Judgment about what's worth doing
Reading the Work Chart
Where should you focus?
HIGH DEMAND + HIGH HUMAN EDGE = Point of difference
HIGH DEMAND + HIGH AI EDGE = Learn to orchestrate
LOW DEMAND + HIGH AI EDGE = Automate or exit
LOW DEMAND + HIGH HUMAN EDGE = Niche or hobby
| Capability | Human Edge | AI Edge | Demand | Strategy |
|---|---|---|---|---|
| Strategy | Judgment, trade-offs | Scenario modeling | High | Lead |
| Sales | Trust, relationships | Lead gen, outreach | High | Lead |
| Product | Empathy, taste | Code, testing | High | Lead |
| Operations | Exceptions, judgment | Process automation | Medium | Orchestrate |
| Administration | Compliance oversight | Bookkeeping | Low | Automate |
Archetype × Quadrant
Which archetype thrives in which strategic quadrant?
LOW AI EDGE HIGH AI EDGE
┌──────────────────────────┬──────────────────────────┐
│ │ │
HIGH │ DIFFERENTIATE │ ORCHESTRATE │
HUMAN │ Dreamer + Coach │ Engineer + Philosopher │
EDGE │ Vision + relationship │ Systems + first principles│
│ │ │
├──────────────────────────┼──────────────────────────┤
│ │ │
LOW │ REINVENT │ AUTOMATE │
HUMAN │ Realist │ No archetype needed │
EDGE │ Face what is, adapt │ AI handles it │
│ │ │
└──────────────────────────┴──────────────────────────┘
Industry Work Charts
AI takeover varies by vertical. Context-dependent work resists automation longer.
| Vertical | Fastest AI Takeover | Slowest AI Takeover | Aggregate AI % | Trend |
|---|---|---|---|---|
| Health | Documentation, scheduling | Diagnosis judgment, bedside manner | 35% | ↑ |
| Real Estate | Valuation models, listing copy | Relationship sales, negotiation | 40% | ↑ |
| Construction | Schedule optimization, docs | Site judgment, crew coordination | 25% | ↑ |
| Energy | Load forecasting, trading | Grid emergency response | 45% | ↑↑ |
| Finance | Fraud detection, underwriting | Complex deal structuring | 50% | ↑↑ |
The pattern: Horizontal activities automate first (same across industries). Vertical activities retain human edge longer (context-dependent, relationship-based).
See Vertical SaaS for full industry analysis.
The Skill Shift
Old model: Learn a skill, then maybe use AI to help.
New model: Learn WITH AI from the start.
| Old Skill | AI-Native Skill |
|---|---|
| Write code | Direct AI to write, review, iterate |
| Research topics | Frame questions, synthesize AI-gathered sources |
| Draft documents | Set constraints, evaluate AI drafts, refine |
| Solve problems | Define the problem, evaluate AI solutions |
The meta-skill: knowing when to think and when to delegate thinking.
Building Your Work Chart
Step 1: Map Activities
List every activity in your function. Be specific—not "marketing" but "write email subject lines" and "analyze campaign performance."
Step 2: Current State
For each activity:
- What do humans currently do?
- What does AI currently do?
- Estimate AI % (even roughly)
Step 3: Trend Direction
For each activity:
- Is AI % increasing (↑), stable (→), or decreasing (↓)?
- How fast?
Step 4: Strategic Response
Based on the map:
- Where do you double down on human edge?
- Where do you learn to orchestrate AI?
- Where do you automate and move on?
Why This Matters
The work chart is a prediction market for labor. It tells you:
- Where AI is actually landing (not hype—observable)
- Which skills are appreciating or depreciating
- Where human edge still creates value
- How fast the shift is happening
Track work charts across functions and you see the 2027 thesis playing out in real time.
Start Here
| If you want to... | Go to... |
|---|---|
| Build AI-native skills | Capabilities |
| Understand the T-shape | Dream Engineer |
| See AI agents in action | Phygital Beings |
| See domain work charts | Marketing, Engineering |
| Track predictions | Predictions |
The Three Buckets Test
Before betting on where human edge persists, validate against three buckets of evidence:
| Bucket | Timespan | What It Says About Human Edge |
|---|---|---|
| Inorganic | 13.7B years | Physics doesn't care about feelings—hard constraints remain |
| Biology | 3.5B years | Reciprocity, trust, and status-seeking are deep patterns |
| Human History | 20k years | Selling, judgment, and relationships never automated |
The robust claim: If an activity has required human judgment across all three buckets, it's unlikely to fully automate by 2027.
The T-Shape Is Fractal
The same pattern at every level:
━━━━━━━━━━━━━━━━━━━━━ ← HORIZONTAL: Reach / General / Cross-domain
┃
┃ ← VERTICAL: Depth / Specific / Domain expertise
| Level | Horizontal | Vertical | SSOT Page |
|---|---|---|---|
| Humans | Soft skills | Hard skills | Dream Engineer |
| Software | Horizontal SaaS | Vertical SaaS | Products |
| AI Agents | AI frameworks | Domain specialization | Phygital Beings |
| Work | Orchestration | Domain judgment | This page |
Context
- Dream Engineer — WHY and HOW to build your T
- Capabilities — WHAT capabilities exist (the menu)
- Orchestration — The meta-skill for AI collaboration
- Horizontal SaaS — Tools that amplify capabilities
- Vertical SaaS — Industry-specific outcomes
- Phygital Beings — AI agents following the same T-shape
- Principles — The truths that guide decisions
"The question isn't whether you'll work alongside AI—it's whether you'll lead the collaboration or follow it."
Where is your point of difference?