Education Platform
The technology stack that makes agency-based education possible.
The ABCD Stack for Education
| Layer | Technology | Education Application |
|---|---|---|
| A | AI/ML | Personalized tutoring, content generation, assessment |
| B | Blockchain | Credential verification, portfolio proofs, reputation |
| C | Crypto/Tokens | Incentive alignment, learn-to-earn, governance |
| D | Data/DePIN | Learning data, collaboration graphs, skill proofs |
The integration: AI delivers personalized content → Blockchain verifies work and credentials → Crypto aligns incentives → Data feeds back to improve AI.
Layer A: AI (Intelligence Infrastructure)
The models that personalize learning at infinite scale.
| Application | Input | Output | Status |
|---|---|---|---|
| AI Tutoring | Student questions, context | Personalized explanation | Mature |
| Content Generation | Learning objectives | Custom materials | Mature |
| Assessment | Student work | Feedback, scoring | Growing |
| Path Optimization | Learning history, goals | Personalized curriculum | Growing |
| Coaching Augmentation | Session notes, patterns | Coach recommendations | Emerging |
AI Tutoring Landscape
| Platform | Focus | Strength | Limitation |
|---|---|---|---|
| Khan Academy + GPT | K-12 concepts | Depth, patience | Not action-oriented |
| Duolingo AI | Language | Gamification | Narrow domain |
| Cursor/Copilot | Coding | Real-time assistance | Skill, not agency |
| Claude/ChatGPT | General | Breadth | Not structured learning |
The gap: All AI tutors optimize for knowledge transfer. None optimize for agency development.
The AI Flywheel
Learner interacts with AI
↓
AI personalizes content
↓
Learner ships faster
↓
More data on effective paths
↓
Better AI personalization
Layer B: Blockchain (Trust Infrastructure)
The immutable layer that makes credentials portable and verifiable.
| Function | Traditional | Blockchain-Enabled |
|---|---|---|
| Credential Verification | Institution-issued paper | On-chain attestation |
| Portfolio Proof | Self-reported | Verifiable work history |
| Skill Attestation | Tests/certifications | Peer + work-based proofs |
| Reputation | Letters of recommendation | Portable, accumulated record |
Credential Types
| Type | What It Proves | Verification Method |
|---|---|---|
| Completion | Finished course | Platform attestation |
| Skill | Can do X | Demonstrated work + peer validation |
| Project | Shipped Y | Commit history, deployment proof |
| Collaboration | Worked with Z | Co-attestation from collaborators |
| Coach endorsement | Vouched by A | Coach's reputation-weighted attestation |
Platform Options
- Ethereum/L2s — Established credential standards (ERC-721 for unique achievements)
- Solana — Speed for micro-credentials, lower costs
- Custom L2 — Education-specific optimizations
The insight: Credentials on-chain are secondary. Shipped work on-chain is primary. The work IS the credential.
Layer C: Crypto/Tokens (Coordination Infrastructure)
The economic layer that aligns incentives across the learning ecosystem.
| Token Type | Function | Example |
|---|---|---|
| Learning Tokens | Reward for verified learning/shipping | Learn-to-earn |
| Coach Tokens | Reward for student outcomes | Outcome-aligned |
| Governance Tokens | Curriculum and platform decisions | DAO education |
| Reputation Tokens | Non-transferable skill attestations | Soulbound badges |
Token Flow Architecture
Learners pay (fiat/crypto)
↓
Platform distributes to:
├── AI infrastructure (compute)
├── Coaches (outcome-based)
├── Verifiers (quality assurance)
└── Treasury (development)
↓
Shipped work generates:
├── Learner reputation
├── Coach reputation
└── Network effects
Incentive Alignment
| Stakeholder | Traditional Incentive | Token-Aligned Incentive |
|---|---|---|
| Learner | Get credential | Ship work, build reputation |
| Coach | Bill hours | Student outcomes |
| Platform | Maximize enrollment | Maximize shipping |
| Verifier | N/A | Quality maintenance |
Layer D: Data/DePIN (Information Infrastructure)
The data layer that enables personalization and verification.
| Data Type | Source | Application |
|---|---|---|
| Learning patterns | Platform interactions | Personalization |
| Skill graphs | Verified work, assessments | Path optimization |
| Collaboration data | Co-work records | Network building |
| Outcome data | Post-learning career success | Curriculum improvement |
Data Architecture
┌─────────────────────────────────────────────────────────────┐
│ APPLICATIONS │
│ AI Tutor │ Portfolio │ Matching │ Verification │
├─────────────────────────────────────────────────────────────┤
│ AI/ML LAYER │
│ Personalization │ Path Opt │ Assessment │ Coaching Aid │
├─────────────────────────────────────────────────────────────┤
│ BLOCKCHAIN LAYER │
│ Credentials │ Work Proofs │ Reputation │ Governance │
├────────────────────────────────────────────────────── ───────┤
│ DATA LAYER │
│ Learning Records │ Skill Graphs │ Collaboration History │
├─────────────────────────────────────────────────────────────┤
│ LEARNER INTERACTIONS │
│ Shipping Work │ Consuming Content │ Coaching │ Community │
└─────────────────────────────────────────────────────────────┘
Platform Maturity Assessment
| Component | Maturity | Key Players | Gap |
|---|---|---|---|
| AI Tutoring | Mature | Khan/GPT, Duolingo | Agency focus missing |
| Content Generation | Mature | GPT, Claude | Quality curation |
| Credential Verification | Growing | Ceramic, Disco | Adoption, standards |
| Portfolio Proofs | Nascent | GitHub, Polywork | Blockchain integration |
| Learn-to-Earn | Nascent | Rabbithole, Layer3 | Sustainable economics |
| Coach Marketplace | Growing | Clarity, MentorCruise | Outcome-alignment |
| Mastermind Platform | Nascent | Various Discord bots | Structured tooling |
Build vs Buy Matrix
| Need | Build | Buy/Partner |
|---|---|---|
| AI Tutoring | ✓ API integrations | |
| Content | ✓ Curate existing | |
| Shipping Platform | ✓ Core differentiator | |
| Credential Infrastructure | ✓ Use existing standards | |
| Coach Matching | ✓ Competitive advantage | |
| Community/Mastermind | ✓ Network effects | |
| Token Economics | ✓ Core to model |
Tool Stack by Function
For Learners
| Function | Tool Options | Selection Criteria |
|---|---|---|
| AI Tutoring | ChatGPT, Claude, Khan | Domain depth |
| Project Hosting | GitHub, Vercel, Replit | Ship speed |
| Portfolio | Personal site, Polywork | Visibility |
| Community | Discord, Circle | Engagement quality |
For Coaches
| Function | Tool Options | Selection Criteria |
|---|---|---|
| Session Management | Calendly, Cal.com | Automation |
| Session Recording | Loom, Zoom | Async review |
| Progress Tracking | Custom dashboards | Visibility |
| Communication | Discord, Slack | Access patterns |
For Platforms
| Function | Tool Options | Selection Criteria |
|---|---|---|
| Learning Management | Custom, Teachable | Flexibility |
| Payment/Tokens | Stripe + crypto rails | Global access |
| Verification | On-chain attestations | Permanence |
| Analytics | PostHog, custom | Privacy, depth |
Integration Architecture
The Agency Accelerator Stack:
┌───────────────────────────────────────────────────────┐
│ LEARNER INTERFACE │
│ Ship Dashboard │ Portfolio │ Network │ Coaching │
├───────────────────────────────────────────────────────┤
│ AI LAYER │
│ Personalized Path │ Just-in-Time Content │ Feedback │
├───────────────────────────────────────────────────────┤
│ VERIFICATION LAYER │
│ Work Proofs │ Peer Attestations │ Coach Endorsements │
├───────────────────────────────────────────────────────┤
│ TOKEN LAYER │
│ Ship Rewards │ Coach Rewards │ Governance │
├───────────────────────────────────────────────────────┤
│ COORDINATION LAYER │
│ Mastermind Matching │ Coach Matching │ Crew Building │
└───────────────────────────────────────────────────────┘
NZ Market Opportunity
Which platform components could be built/deployed in New Zealand?
| Component | NZ Viability | Considerations |
|---|---|---|
| Agency Accelerator | High | Small market allows iteration |
| Coach Training | High | English-speaking, timezone for Asia-Pac |
| Verification | Medium | Needs global standards |
| Token Economics | Medium | Regulatory clarity needed |
See New Zealand for market analysis.
Context
- AI — Intelligence layer capabilities
- Blockchain — Trust layer options
- DePIN — Physical infrastructure patterns
- Crypto Protocols — Token infrastructure