Swarm Coder: AI Governance Through Geometry

One-liner: The navigation system for AI agents—the same math that coordinates drone swarms now coordinates coding agents, preventing drift into bugs, hallucinations, or policy violations.

The Problem

AI agents are blind. They can’t see:

The full codebase
What other agents are doing
When they’re drifting from intended behavior

Just like a drone without a camera needs sonar, GPS, and swarm awareness to avoid crashing—AI coding agents need governance, consensus, and spatial awareness to avoid errors.

The Solution: 6 Agents, 1 Geometry

┌────────────────────────────────────────────────────┐
│                  SWARM CODER                       │
│   "6 AI agents that code like a drone swarm"       │
├────────────────────────────────────────────────────┤
│                                                    │
│    ┌─────┐    ┌─────┐    ┌─────┐                  │
│    │ KO  │    │ AV  │    │ RU  │  ← Orchestrate   │
│    │Flow │    │I/O  │    │Policy│    Design/Code  │
│    └──┬──┘    └──┬──┘    └──┬──┘                  │
│       │          │          │                      │
│       └──────────┼──────────┘                      │
│                  ▼                                 │
│       ┌──────────────────┐                         │
│       │  Poincaré Ball   │  ← Shared behavior     │
│       │  (Hyperbolic     │     space where        │
│       │   geometry)      │     position = intent  │
│       └──────────────────┘                         │
│                  ▲                                 │
│       ┌──────────┼──────────┐                      │
│       │          │          │                      │
│    ┌──┴──┐    ┌──┴──┐    ┌──┴──┐                  │
│    │ CA  │    │ UM  │    │ DR  │  ← Verify        │
│    │Comp │    │Sec  │    │Auth │    Test/Review   │
│    └─────┘    └─────┘    └─────┘                  │
│                                                    │
└────────────────────────────────────────────────────┘

How It Works

1. Decimal Drift Detection

Every agent’s actions are tracked as a position in hyperbolic space. When an agent drifts from expected behavior:

Agent behavior: (0.2, 0.5, 0.1) → (0.4, 0.6, 0.3) → (0.7, 0.8, 0.5)
Policy anchor:  (0.2, 0.5, 0.1)
Distance grows: 0 → 0.2 → 0.6

System response:
├── 0.0-0.3: Interior → Normal operation
├── 0.3-0.6: Border → Increased scrutiny
└── 0.6+:    Exterior → Require approval / DENY

2. Harmonic Wall Cost

The further you drift, the exponentially harder it gets:

H(d) = exp(d²)

d = 0.0  →  H = 1.00   (free to operate)
d = 0.5  →  H = 1.28   (slight friction)
d = 1.0  →  H = 2.72   (noticeable cost)
d = 2.0  →  H = 54.6   (expensive)
d = 3.0  →  H = 8,103  (effectively blocked)

Adversarial actions cost exponentially more. No rules needed—the geometry enforces safety.

3. Byzantine Fault Tolerant Consensus

4-of-6 agents must agree. One rogue agent can’t corrupt the swarm:

Quorum: 2f + 1 = 5 (tolerates 2 failures)
Weighted by Sacred Tongue (φⁿ golden ratio)

KO votes: weight 1.00
AV votes: weight 1.62
RU votes: weight 2.62
CA votes: weight 4.24
UM votes: weight 6.85
DR votes: weight 11.09

Why This Matters

Physical Drone	AI Coding Agent
Position in 3D space	Position in behavior space
Physical drift	Decimal drift (policy deviation)
Gravity/sonar failsafe	Governance/consensus failsafe
Frequency navigation	Sacred Tongue protocols
Blind without camera	Blind without full context
Swarm awareness	Multi-agent consensus

Same math. Same coordination. Different domain.

Technical Specs

14-layer decision pipeline from input to ALLOW/DENY
Post-quantum safe: ML-KEM (Kyber) + ML-DSA (Dilithium)
Hyperbolic geometry: Poincaré ball model (curvature = -1)
SS1 Tokenizer: Phonetic encoding for semantic security
Dual-lattice: Combines semantic + computational security

Use Cases

1. AI Coding Swarm

6 agents collaborate on code. Each specializes:

KO: Orchestration, task flow
AV: Input/output, API calls
RU: Policy enforcement, rules
CA: Core computation, encryption
UM: Security scanning, redaction
DR: Authentication, schema validation

2. Space Debris Removal

Spacecraft swarm that:

Operates autonomously (no ground control delay)
Survives if one satellite fails (BFT)
Can’t be hijacked (PQC encryption)
Coordinates without central command

3. Enterprise AI Governance

Every AI action passes through governance:

POST /govern
{
  "actor": { "id": "gpt-agent", "type": "ai" },
  "resource": { "type": "contract", "value_usd": 50000 },
  "intent": "auto_approve"
}

Response:
{
  "decision": "ESCALATE",
  "rationale": "Contract value exceeds auto-approval threshold",
  "required_approvers": ["legal-team"]
}

The Stack

Layer	Component	Purpose
L1-4	Context Processing	Normalize & embed inputs
L5	Hyperbolic Metric	Distance-preserving geometry
L6-7	Breathing Transform	Phase-shifted Möbius operations
L8	Trust Realms	Multi-well decision spaces
L9-10	Spectral Coherence	Polyhedral stability checks
L11	Temporal Distance	Time-aware decisions
L12	Harmonic Wall	Exponential adversarial cost
L13	Decision Gate	ALLOW / DENY / ESCALATE
L14	Audio Axis	Telemetry & monitoring

Status

Patent: Application filed (provisional)
Code: 995+ tests passing
Security: Post-quantum cryptography integrated
Deployment: Kubernetes manifests ready

Contact

GitHub: SCBE-AETHERMOORE

“We don’t write rules. We write geometry. The math itself prevents adversarial drift.”