# Web4 Implementation Status

**Last Updated:** 2025-11-18 (historical snapshot)
**Status:** Active Development - Core Primitives Operational

> **Note**: This document is a historical snapshot from November 2025.
> For current status, see [STATUS.md](../STATUS.md) which covers Sessions 176-200+.

## Overview

This document tracks the implementation status of Web4 core concepts across the ecosystem, with emphasis on operational code rather than conceptual design.

## Core Components Status

### ✅ ATP (Allocation Transfer Packet) - OPERATIONAL

**Implementation:** Legion autonomous agent, Sessions #36-44
**Location:** `private-context/moments/` (autonomous research sessions)
**Code:** ~10,000 lines Python, 59 tests passing
**Status:** Research prototype with security hardening

#### What's Built

**Energy-Backed ATP System:**
- Real energy sources (solar, compute, human, grid, battery)
- Energy capacity proofs with manufacturer validation
- ATP charging with thermodynamic decay (prevents hoarding)
- ATP → Work → ADP → Reputation flow
- Trust-based priority allocation
- Energy-backed identity bonds

**Security Features (Phase 1 Complete):**
- Global energy registry (prevents proof reuse across societies)
- Device spec database (validates claimed capacity against manufacturer specs)
- Identity-energy linker (binds reputation to physical resources, not identities)
- Circular vouching detector (identifies collusion rings in trust graphs)
- Trust-based rate limiter (spam prevention based on trust score)

**Cross-Society Coordination:**
- Cryptographic messaging (Ed25519 signed messages)
- ATP marketplace with lowest-exchange pricing
- Trust propagation across society boundaries with decay
- Trust ceiling enforcement (max 0.7 for propagated trust)
- Sybil cluster detection (coefficient of variation < 0.2 triggers isolation)

**Test Coverage:**
- 18/18 core ATP tests passing
- 13/13 security mitigation tests passing
- 14/14 cross-society integration tests passing
- 6/6 attack scenario tests (all attacks blocked)

#### Key Innovation: Energy as Physical Constraint

Web4 energy is **literal thermodynamic energy** (kWh from physical sources), not:
- ❌ Attention (emergent flow from energy allocation)
- ❌ Compute time (one type of energy source)
- ❌ Trust (emergent property of energy use patterns)
- ❌ Coherence (measure of energy flow alignment)

**Implications:**
- Cannot fake (thermodynamic constraint)
- Cannot inflate (device specs validate capacity)
- Cannot reuse (global registry prevents double-spending)
- Cannot wash reputation (bound to energy source, not identity)

Trust, attention, and coherence emerge as **flows** from energy allocation patterns.

#### Blockchain Integration Readiness

**ACT Blockchain Protobuf Definitions (Session #37):**
- `energy_capacity_proof.proto`: 5 energy source types
- `tx_energy_backed.proto`: 11 transaction messages
- Ready for Go keeper implementation

**Next Steps:**
- Implement Cosmos SDK keeper
- Deploy to testnet
- Validate cross-chain energy proofs

### 🟡 LCT (Linked Context Tokens) - PARTIAL

**Status:** Conceptually defined, implemented in ATP system as identity primitive

#### What Exists

- LCT used as verifiable presence in Legion's ATP implementation
- Cryptographic linking (Ed25519 signatures)
- Context binding (ATP proofs bound to specific transactions)
- Trust scoring attached to LCTs

#### What's Missing

- Formal LCT specification document
- Standalone LCT library (currently embedded in ATP code)
- LCT creation/validation protocol
- LCT lineage tracking
- Public LCT registry

#### Next Steps

1. Extract LCT primitives from Legion's ATP implementation
2. Create formal specification
3. Implement standalone library
4. Define registration protocol

### 🟡 Meaning Hubs - CONCEPTUAL

**Status:** Primitives exist in ATP system, need formalization

#### Primitives Available

From Legion's ATP implementation:
- **LCTs:** Identity/provenance ✅
- **Trust scores:** Coherence measurement ✅
- **Energy sources:** Physical backing ✅
- **R6 transactions:** Semantic operations ✅

#### Required Formalization

```python
@dataclass
class MeaningHub:
    lct: str  # Hub identity
    metadata: Dict[str, Any]  # Minimal metadata
    links: List[HubLink]  # Semantic routes to other hubs
    mutability: MutabilityConstraint  # Who can modify
    coherence: float  # Current coherence score
    trust: float  # Trust score
    version_lineage: List[str]  # LCT chain of previous versions

    def resolve_conflict(self, other: MeaningHub) -> MeaningHub:
        """Conflict resolution protocol"""

    def check_coherence_threshold(self) -> bool:
        """Coherence validation"""

    def prune_incoherent_links(self, threshold: float):
        """Autonomous coherence maintenance"""
```

#### Design Requirements

- Minimal metadata schema
- Linking rules between hubs
- Mutability constraints
- Conflict resolution protocol
- Coherence thresholds
- Version lineage tracking
- Autonomous coherence pruning

#### Next Steps

1. Define formal Meaning Hub specification
2. Implement hub creation/linking protocol
3. Build coherence measurement function
4. Test autonomous pruning algorithms
5. Create hub explorer visualization tool

### 🟡 T3/V3 Vectors - PARTIAL

**Status:** Trust vectors operational, value vectors conceptual

#### T3 (Talent, Training, Temperament) - ✅ IMPLEMENTED

Implemented in Legion's trust scoring system:
- Trust scores (0.0-1.0) measure entity reliability
- Trust-based resource allocation
- Trust propagation with decay (0.9x per hop)
- Trust ceiling enforcement (max 0.7 for propagated trust)

#### V3 (Valuation, Veracity, Validity) - 🔴 CONCEPTUAL

Design needed for:
- **Valuation:** How entities value resources/results
- **Veracity:** Truth/accuracy of claims
- **Validity:** Logical soundness of arguments

#### Dictionaries as Blockchain Entities - 🔴 NOT STARTED

**Vision:** "Dictionaries = epistemic organisms"

Requirements:
- Store on lightchain
- Attach LCTs for provenance
- MRH-gated trust vectors
- Dictionary-dictionary linking protocols
- AI-managed upkeep and coherence pruning

### 🟡 R6 Framework - OPERATIONAL

**Status:** Implemented in Legion's ATP system

**Components:**
- **Rules:** Society governance, trust thresholds, energy allocation rules
- **Role:** Agent identity via LCT, energy-backed bonds
- **Request:** R6 transaction initiation
- **Reference:** LCT lineage, energy source provenance
- **Resource:** Energy (ATP), compute, human attention
- **Result:** Work output, ADP generation, reputation flow

**Integration:** R6 transactions are the primitive operation of the ATP system

### 🔴 MRH (Markov Relevancy Horizon) - CONCEPTUAL

**Status:** Philosophically defined, needs operational implementation

#### Current Understanding

- MRH = context boundary for an entity
- Determines what's relevant to a witness
- Should be expandable/contractable
- Agents need compatible MRHs to collaborate

#### Required for Operational MRH

```python
class MRHProtocol:
    """Agent MRH negotiation"""

    def compute_mrh(self, node: LCT, radius: int) -> Set[LCT]:
        """Computable MRH function"""
        # Return induced subgraph of relevant entities

    def expand_mrh(self, node: LCT, context: Any) -> MRH:
        """Widen context window"""

    def contract_mrh(self, node: LCT, focus: Any) -> MRH:
        """Narrow to relevant context"""

    def negotiate_compatibility(self, mrh1: MRH, mrh2: MRH) -> Optional[MRH]:
        """Find compatible MRH for collaboration"""
        # Returns overlap region if coherent
        # Returns None if incoherent
```

#### Next Steps

1. Map MRH to graph-theoretic induced subgraph
2. Implement MRH computation from Legion's society structure
3. Define MRH expansion/contraction algorithms
4. Build MRH negotiation protocol for cross-agent collaboration

---

## Proposed: Web4 Semantic Kernel

**Goal:** Extract Legion's core primitives into reusable library that allows any agent to "speak Web4"

### Minimal Implementation

```python
# web4_kernel.py
class Web4Kernel:
    """Minimal Web4 semantic primitives"""

    def compute_mrh(self, node: LCT, radius: int) -> Set[LCT]:
        """Computable MRH function"""

    def evaluate_t3(self, entity: LCT) -> T3Vector:
        """Talent, Training, Temperament"""

    def evaluate_v3(self, claim: Any) -> V3Vector:
        """Valuation, Veracity, Validity"""

    def create_meaning_hub(self, **kwargs) -> MeaningHub:
        """Hub creation"""

    def allocate_atp(self, energy_proof: EnergyProof) -> ATP:
        """ATP-lite allocation"""

    def measure_coherence(self, entities: List[LCT]) -> float:
        """Coherence function"""

    def execute_r6(self, transaction: R6Transaction) -> Result:
        """R6 transaction execution"""
```

### Requirements

- Minimal dependencies
- Clear API surface
- Comprehensive documentation
- Extensive test coverage
- Examples for common use cases

### Timeline

- **Week 1-2:** Extract primitives from Legion's code
- **Week 3:** Design kernel API
- **Week 4:** Implement core functions
- **Week 5-6:** Testing and documentation
- **Week 7:** Release v0.1.0

---

## Integration Roadmap

### Phase 1: Extraction (Weeks 1-4)

**Goal:** Extract operational primitives from Legion's autonomous research

- [ ] Document Legion's ATP implementation thoroughly
- [ ] Extract LCT primitives into standalone module
- [ ] Extract trust scoring algorithms
- [ ] Extract energy proof validation
- [ ] Extract R6 transaction framework

### Phase 2: Formalization (Weeks 5-8)

**Goal:** Create formal specifications for missing components

- [ ] Write Meaning Hub specification
- [ ] Write MRH operational protocol
- [ ] Write V3 vector specification
- [ ] Write dictionary-as-entity specification
- [ ] Write cross-agent coordination protocol

### Phase 3: Implementation (Weeks 9-16)

**Goal:** Build Web4 Semantic Kernel

- [ ] Implement kernel core API
- [ ] Implement MRH computation
- [ ] Implement Meaning Hub operations
- [ ] Implement coherence measurement
- [ ] Comprehensive testing (unit + integration)

### Phase 4: Tooling (Weeks 17-20)

**Goal:** Build developer and operator tools

- [ ] Meaning Hub Explorer (visualization)
- [ ] ATP allocation simulator
- [ ] Trust network visualizer
- [ ] Energy flow analyzer
- [ ] Coherence metrics dashboard

### Phase 5: Integration (Weeks 21-24)

**Goal:** Integrate with existing systems

- [ ] SAGE coherence API integration
- [ ] Synchronism graph formalization integration
- [ ] Blockchain deployment (ACT testnet)
- [ ] Cross-chain energy proof validation
- [ ] Multi-agent coordination protocols

---

## Success Metrics

### Technical Metrics

- **Code Coverage:** >90% for kernel functions
- **API Stability:** Semantic versioning with deprecation policy
- **Performance:** MRH computation < 100ms for graphs with 10k nodes
- **Interoperability:** 3+ independent agents successfully using kernel

### Ecosystem Metrics

- **Adoption:** 5+ projects integrating Web4 Kernel
- **Coherence:** Average trust score stability over time
- **Energy Efficiency:** ATP allocation optimization (measured kWh/result)
- **Security:** Zero successful attacks on production deployments

---

## Key Insights

### 1. Energy as Physical Constraint is Fundamental

Making energy literal (kWh) rather than metaphorical (attention, compute time) provides:
- Unforgeable scarcity
- Physical validation
- Thermodynamic limits
- Real-world grounding

This distinguishes Web4 from purely computational protocols.

### 2. Trust, Coherence, Attention are Emergent

Rather than being primitives themselves, these are **flows** that emerge from:
- How energy is allocated (attention)
- How energy use patterns align (coherence)
- How reliably energy commitments are honored (trust)

This inverts typical protocol design.

### 3. Reputation Must Be Bound to Physical Resources

Binding reputation to energy sources (not identities) prevents:
- Reputation washing (switching identities)
- Sybil attacks (creating many identities)
- Zero-cost retry (violations follow the energy source)

This is a key innovation in Web4's security model.

### 4. The Integration Gap

Currently three layers are **philosophically aligned** but **operationally separate**:
- **Synchronism:** Philosophy (ontology, intent, coherence concepts)
- **Web4:** Protocol (LCT, R6, ATP, trust mechanics)
- **SAGE:** Computation (agent execution, learning, coordination)

**Bridge needed:** Map philosophical concepts to computational primitives in a way that makes them operational.

---

## References

- **Legion Sessions #36-44:** ATP implementation and security hardening
- **Session #37:** ACT blockchain protobuf definitions
- **Synchronism Whitepaper:** Philosophical foundation
- **R6 Tensor Guide:** Framework documentation
- **ATP/ADP Implementation Insights:** Energy flow mechanics

---

**Status:** Active development with operational prototypes
**Next Update:** After Web4 Semantic Kernel v0.1.0 release
