BRAIN-LAYER-IMPLEMENTATION-GUIDE.md•26.1 kB
# Wake Brain Layer Implementation Guide
**Purpose**: Practical guide for implementing the 3-layer Wake Intelligence brain architecture in semantic-wake-intelligence-mcp.
**Target**: Developers implementing temporal intelligence patterns
---
## Quick Reference
| Layer | Current Status | Priority | Effort |
|-------|---------------|----------|--------|
| **Layer 1: Causality Engine** | 40% complete | HIGH | 1 week |
| **Layer 2: Memory Manager** | 90% complete | LOW | 3 days |
| **Layer 3: Propagation Engine** | 0% complete | HIGH | 1.5 weeks |
**Total Implementation Time**: ~3-4 weeks
---
## Layer 1: Causality Engine (Past)
### Current State
**What Exists**:
```typescript
// src/domain/models/ContextSnapshot.ts
export class ContextSnapshot {
public readonly timestamp: string // ✅ Temporal anchor
public readonly source: string // ✅ Provenance
// Missing: rationale, action type, dependencies
}
```
**What's Missing**: Causal tracking, rationale preservation, dependency graphs
---
### Implementation Steps
#### Step 1.1: Extend ContextSnapshot with Causality
**File**: `src/domain/models/ContextSnapshot.ts`
```typescript
/**
* LAYER 1: Causality tracking metadata
*/
export interface CausalityMetadata {
actionType: 'conversation' | 'decision' | 'file_edit' | 'tool_use' | 'research'
rationale: string // WHY this context was saved
dependencies: string[] // IDs of prior snapshots that influenced this
causedBy: string | null // Parent snapshot ID (causal chain)
}
export class ContextSnapshot implements IContextSnapshot {
constructor(
public readonly id: string,
public readonly project: string,
public readonly summary: string,
public readonly source: string,
public readonly metadata: string | null,
public readonly tags: string,
public readonly timestamp: string,
public readonly causality: CausalityMetadata | null // NEW
) {
this.validate();
}
static create(data: {
project: string;
summary: string;
source?: string;
metadata?: Record<string, unknown>;
tags: string;
causality?: CausalityMetadata; // NEW: Optional causality tracking
}): ContextSnapshot {
return new ContextSnapshot(
crypto.randomUUID(),
data.project,
data.summary,
data.source || 'mcp',
data.metadata ? JSON.stringify(data.metadata) : null,
data.tags,
new Date().toISOString(),
data.causality || null // NEW
);
}
}
```
---
#### Step 1.2: Create CausalityService
**File**: `src/domain/services/CausalityService.ts` (NEW)
```typescript
/**
* 🎯 LAYER 1: Causality Engine
*
* PURPOSE: Track action history and causal relationships
*
* RESPONSIBILITIES:
* - Record actions with rationale
* - Build causal chains
* - Reconstruct decision reasoning
* - Detect dependencies
*/
import type { IContextRepository } from '../../application/ports/IContextRepository';
import { ContextSnapshot } from '../models/ContextSnapshot';
export interface CausalChain {
snapshot: ContextSnapshot;
rationale: string;
dependencies: ContextSnapshot[];
causedBy: ContextSnapshot | null;
}
export class CausalityService {
constructor(private readonly repository: IContextRepository) {}
/**
* Reconstruct the reasoning behind a decision
*
* Returns full causal chain: Why → What → Dependencies
*/
async reconstructReasoning(snapshotId: string): Promise<CausalChain> {
const snapshot = await this.repository.findById(snapshotId);
if (!snapshot) throw new Error(`Snapshot ${snapshotId} not found`);
const causality = snapshot.causality;
if (!causality) {
return {
snapshot,
rationale: 'No rationale recorded',
dependencies: [],
causedBy: null
};
}
// Load dependencies
const dependencies = await Promise.all(
causality.dependencies.map(id => this.repository.findById(id))
).then(results => results.filter(Boolean) as ContextSnapshot[]);
// Load parent (if exists)
const causedBy = causality.causedBy
? await this.repository.findById(causality.causedBy)
: null;
return {
snapshot,
rationale: causality.rationale,
dependencies,
causedBy
};
}
/**
* Build full causal chain from root to specified snapshot
*
* Returns array of snapshots in temporal order
*/
async buildCausalChain(endSnapshotId: string): Promise<ContextSnapshot[]> {
const chain: ContextSnapshot[] = [];
let currentId: string | null = endSnapshotId;
while (currentId) {
const snapshot = await this.repository.findById(currentId);
if (!snapshot) break;
chain.unshift(snapshot); // Add to front (chronological order)
currentId = snapshot.causality?.causedBy || null;
}
return chain;
}
/**
* Detect which prior snapshots influenced this decision
*
* Uses temporal proximity + content similarity
*/
async detectDependencies(
project: string,
currentTimestamp: string
): Promise<string[]> {
// Get recent snapshots (last 24 hours)
const recentSnapshots = await this.repository.findRecent(project, currentTimestamp, 24);
// Simple heuristic: last 3 snapshots are dependencies
// TODO: Enhance with semantic similarity matching
return recentSnapshots.slice(0, 3).map(s => s.id);
}
}
```
---
#### Step 1.3: Database Migration
**File**: `migrations/0002_add_causality.sql` (NEW)
```sql
-- LAYER 1: Causality Engine schema
-- Adds causal tracking to contexts table
ALTER TABLE contexts ADD COLUMN action_type TEXT;
ALTER TABLE contexts ADD COLUMN rationale TEXT;
ALTER TABLE contexts ADD COLUMN dependencies TEXT; -- JSON array of snapshot IDs
ALTER TABLE contexts ADD COLUMN caused_by TEXT REFERENCES contexts(id);
-- Index for causal chain traversal
CREATE INDEX idx_contexts_caused_by ON contexts(caused_by);
-- Index for dependency lookups
CREATE INDEX idx_contexts_project_timestamp ON contexts(project, timestamp DESC);
```
**Run Migration**:
```bash
wrangler d1 execute mcp-context --file=./migrations/0002_add_causality.sql
```
---
#### Step 1.4: Update Repository Interface
**File**: `src/application/ports/IContextRepository.ts`
```typescript
export interface IContextRepository {
// ... existing methods
// NEW: Layer 1 methods
findById(id: string): Promise<ContextSnapshot | null>;
findRecent(project: string, beforeTimestamp: string, hoursBack: number): Promise<ContextSnapshot[]>;
}
```
**File**: `src/infrastructure/adapters/D1ContextRepository.ts`
```typescript
export class D1ContextRepository implements IContextRepository {
// ... existing implementation
async findById(id: string): Promise<ContextSnapshot | null> {
const result = await this.db
.prepare('SELECT * FROM contexts WHERE id = ?')
.bind(id)
.first();
return result ? ContextSnapshot.fromDatabase(result as IContextSnapshot) : null;
}
async findRecent(
project: string,
beforeTimestamp: string,
hoursBack: number
): Promise<ContextSnapshot[]> {
const cutoff = new Date(new Date(beforeTimestamp).getTime() - hoursBack * 3600000)
.toISOString();
const results = await this.db
.prepare(`
SELECT * FROM contexts
WHERE project = ?
AND timestamp >= ?
AND timestamp < ?
ORDER BY timestamp DESC
LIMIT 10
`)
.bind(project, cutoff, beforeTimestamp)
.all();
return results.results.map(r => ContextSnapshot.fromDatabase(r as IContextSnapshot));
}
}
```
---
#### Step 1.5: Update ContextService
**File**: `src/domain/services/ContextService.ts`
```typescript
export class ContextService {
constructor(
private readonly repository: IContextRepository,
private readonly aiProvider: IAIProvider,
private readonly causalityService: CausalityService // NEW: Inject causality
) {}
async saveContext(input: SaveContextInput & {
causality?: {
actionType: string;
rationale: string;
causedBy?: string;
}
}): Promise<ContextSnapshot> {
// Step 1: AI Enhancement
const summary = await this.aiProvider.generateSummary(input.content);
const tags = await this.aiProvider.generateTags(summary);
// Step 2: Detect dependencies (Layer 1)
const dependencies = input.causality
? await this.causalityService.detectDependencies(input.project, new Date().toISOString())
: [];
// Step 3: Create snapshot with causality
const snapshot = ContextSnapshot.create({
project: input.project,
summary,
source: input.source,
metadata: input.metadata,
tags,
causality: input.causality ? {
actionType: input.causality.actionType as any,
rationale: input.causality.rationale,
dependencies,
causedBy: input.causality.causedBy || null
} : null
});
// Step 4: Persist
await this.repository.save(snapshot);
return snapshot;
}
}
```
---
## Layer 2: Memory Manager (Present)
### Current State
**What Exists**: ✅ Core functionality complete
- `saveContext()` - Snapshot preservation
- `loadContext()` - Context retrieval
- `searchContext()` - Semantic search
**What's Missing**: Memory tiers, LRU tracking, pruning
---
### Implementation Steps
#### Step 2.1: Add Memory Tiers
**File**: `src/domain/models/ContextSnapshot.ts`
```typescript
/**
* LAYER 2: Memory hierarchy
*/
export enum MemoryTier {
ACTIVE = 'active', // Last 1 hour
RECENT = 'recent', // 1-24 hours
ARCHIVED = 'archived', // 1-30 days
EXPIRED = 'expired' // > 30 days (marked for deletion)
}
export class ContextSnapshot {
constructor(
// ... existing fields
public readonly memoryTier: MemoryTier, // NEW
public readonly lastAccessed: string | null, // NEW: LRU tracking
public readonly accessCount: number // NEW: Frequency
) {}
/**
* Calculate memory tier based on age
*/
static calculateMemoryTier(timestamp: string): MemoryTier {
const ageInHours = (Date.now() - new Date(timestamp).getTime()) / (1000 * 60 * 60);
if (ageInHours < 1) return MemoryTier.ACTIVE;
if (ageInHours < 24) return MemoryTier.RECENT;
if (ageInHours < 720) return MemoryTier.ARCHIVED; // 30 days
return MemoryTier.EXPIRED;
}
/**
* Mark snapshot as accessed (LRU)
*/
markAccessed(): ContextSnapshot {
return new ContextSnapshot(
this.id,
this.project,
this.summary,
this.source,
this.metadata,
this.tags,
this.timestamp,
this.causality,
this.memoryTier,
new Date().toISOString(), // Update last accessed
this.accessCount + 1 // Increment count
);
}
}
```
---
#### Step 2.2: Add Pruning Logic
**File**: `src/domain/services/ContextService.ts`
```typescript
export class ContextService {
/**
* LAYER 2: Update memory tiers based on age
*
* Runs periodically (e.g., via cron trigger)
*/
async updateMemoryTiers(): Promise<number> {
const allSnapshots = await this.repository.findAll();
let updated = 0;
for (const snapshot of allSnapshots) {
const newTier = ContextSnapshot.calculateMemoryTier(snapshot.timestamp);
if (newTier !== snapshot.memoryTier) {
await this.repository.updateMemoryTier(snapshot.id, newTier);
updated++;
}
}
return updated;
}
/**
* LAYER 2: Prune expired contexts
*
* Deletes contexts with MemoryTier.EXPIRED
*/
async pruneExpiredContexts(): Promise<number> {
return await this.repository.deleteByMemoryTier(MemoryTier.EXPIRED);
}
/**
* LAYER 2: Mark context as accessed (LRU tracking)
*/
async recordAccess(snapshotId: string): Promise<void> {
const snapshot = await this.repository.findById(snapshotId);
if (!snapshot) return;
const updated = snapshot.markAccessed();
await this.repository.update(updated);
}
}
```
---
#### Step 2.3: Database Migration
**File**: `migrations/0003_add_memory_tiers.sql` (NEW)
```sql
-- LAYER 2: Memory hierarchy schema
-- Adds memory tier classification and LRU tracking
ALTER TABLE contexts ADD COLUMN memory_tier TEXT DEFAULT 'recent';
ALTER TABLE contexts ADD COLUMN last_accessed TEXT;
ALTER TABLE contexts ADD COLUMN access_count INTEGER DEFAULT 0;
-- Index for tier-based queries
CREATE INDEX idx_contexts_memory_tier ON contexts(memory_tier);
-- Index for pruning expired contexts
CREATE INDEX idx_contexts_expired ON contexts(memory_tier) WHERE memory_tier = 'expired';
```
---
## Layer 3: Propagation Engine (Future)
### Current State
**What Exists**: ❌ Nothing - entirely new layer
**What's Needed**: Temporal decay, pattern detection, predictive surfacing
---
### Implementation Steps
#### Step 3.1: Create PropagationEngine
**File**: `src/domain/services/PropagationEngine.ts` (NEW)
```typescript
/**
* 🎯 LAYER 3: Propagation Engine
*
* PURPOSE: Future-oriented context intelligence
*
* RESPONSIBILITIES:
* - Calculate temporal relevance decay
* - Detect user patterns
* - Prime context for next interactions
* - Predictive context surfacing
*/
import type { IContextRepository } from '../../application/ports/IContextRepository';
import { ContextSnapshot, MemoryTier } from '../models/ContextSnapshot';
export interface Pattern {
type: 'sequential' | 'conditional' | 'periodic';
description: string;
confidence: number;
examples: string[]; // Snapshot IDs demonstrating pattern
}
export class PropagationEngine {
constructor(private readonly repository: IContextRepository) {}
/**
* Calculate context relevance with temporal decay
*
* Formula: Relevance = e^(-age / half-life) × (1 + AccessBoost × 0.3)
*/
calculateRelevance(snapshot: ContextSnapshot, currentTime: Date): number {
const ageInHours = this.getAgeInHours(snapshot.timestamp, currentTime);
const halfLife = this.getHalfLife(snapshot.memoryTier);
// Exponential temporal decay
const temporalRelevance = Math.exp(-ageInHours / halfLife);
// LRU boost
const accessBoost = snapshot.lastAccessed
? this.calculateAccessBoost(snapshot.lastAccessed, currentTime)
: 0;
return temporalRelevance * (1 + accessBoost * 0.3);
}
/**
* Get half-life for temporal decay based on memory tier
*
* Half-life = time for relevance to decay to 50%
*/
private getHalfLife(tier: MemoryTier): number {
switch (tier) {
case MemoryTier.ACTIVE: return 12; // 12 hours
case MemoryTier.RECENT: return 72; // 3 days
case MemoryTier.ARCHIVED: return 336; // 14 days
case MemoryTier.EXPIRED: return 1; // 1 hour (rapid decay)
}
}
/**
* Calculate LRU boost based on recent access
*/
private calculateAccessBoost(lastAccessed: string, currentTime: Date): number {
const hoursSinceAccess = this.getAgeInHours(lastAccessed, currentTime);
const accessHalfLife = 12; // 12 hours
return Math.exp(-hoursSinceAccess / accessHalfLife);
}
private getAgeInHours(timestamp: string, currentTime: Date): number {
return (currentTime.getTime() - new Date(timestamp).getTime()) / (1000 * 60 * 60);
}
/**
* Detect patterns in context history
*
* Examples:
* - Sequential: "User always follows file edits with tests"
* - Conditional: "When OAuth is mentioned, user needs token configs"
* - Periodic: "User returns to auth-service every Monday"
*/
async detectPatterns(project: string): Promise<Pattern[]> {
const snapshots = await this.repository.findByProject(project, 100);
const patterns: Pattern[] = [];
// Pattern 1: Sequential actions (simple bigram model)
const sequences = this.detectSequentialPatterns(snapshots);
patterns.push(...sequences);
// Pattern 2: Conditional context (co-occurrence)
const conditionals = this.detectConditionalPatterns(snapshots);
patterns.push(...conditionals);
// TODO: Pattern 3: Periodic patterns (time-based)
return patterns;
}
private detectSequentialPatterns(snapshots: ContextSnapshot[]): Pattern[] {
// Simplified: Look for repeated action sequences
// Example: "conversation" → "file_edit" → "tool_use" (test)
const sequences = new Map<string, number>();
for (let i = 0; i < snapshots.length - 1; i++) {
const current = snapshots[i].causality?.actionType || 'unknown';
const next = snapshots[i + 1].causality?.actionType || 'unknown';
const sequence = `${current} → ${next}`;
sequences.set(sequence, (sequences.get(sequence) || 0) + 1);
}
// Convert to patterns (threshold: 3+ occurrences)
return Array.from(sequences.entries())
.filter(([_, count]) => count >= 3)
.map(([sequence, count]) => ({
type: 'sequential' as const,
description: `User typically follows ${sequence}`,
confidence: Math.min(count / 10, 0.95),
examples: [] // TODO: Add snapshot IDs
}));
}
private detectConditionalPatterns(snapshots: ContextSnapshot[]): Pattern[] {
// Simplified: Look for tag co-occurrence
// Example: If "OAuth" tag present, "token" tag often follows
const cooccurrence = new Map<string, Map<string, number>>();
for (const snapshot of snapshots) {
const tags = snapshot.tags.split(',').map(t => t.trim());
for (let i = 0; i < tags.length; i++) {
for (let j = i + 1; j < tags.length; j++) {
const tagA = tags[i];
const tagB = tags[j];
if (!cooccurrence.has(tagA)) cooccurrence.set(tagA, new Map());
const map = cooccurrence.get(tagA)!;
map.set(tagB, (map.get(tagB) || 0) + 1);
}
}
}
// Convert to patterns (threshold: 5+ co-occurrences)
const patterns: Pattern[] = [];
for (const [tagA, relations] of cooccurrence.entries()) {
for (const [tagB, count] of relations.entries()) {
if (count >= 5) {
patterns.push({
type: 'conditional' as const,
description: `When working on "${tagA}", user often needs "${tagB}"`,
confidence: Math.min(count / 20, 0.90),
examples: []
});
}
}
}
return patterns;
}
/**
* Prime context for next interaction
*
* Returns contexts likely to be needed based on:
* - Temporal relevance (decay)
* - Pattern matching (learned behaviors)
* - Causal chains (related decisions)
*/
async primeContext(
project: string,
currentSnapshot: ContextSnapshot | null
): Promise<ContextSnapshot[]> {
const allSnapshots = await this.repository.findByProject(project, 50);
const currentTime = new Date();
// Calculate relevance for each snapshot
const scored = allSnapshots.map(snapshot => ({
snapshot,
relevance: this.calculateRelevance(snapshot, currentTime)
}));
// Filter by threshold and sort
const relevant = scored
.filter(s => s.relevance > 0.1) // Pruning threshold
.sort((a, b) => b.relevance - a.relevance)
.slice(0, 10);
return relevant.map(s => s.snapshot);
}
}
```
---
#### Step 3.2: Integrate into ContextService
**File**: `src/domain/services/ContextService.ts`
```typescript
export class ContextService {
constructor(
private readonly repository: IContextRepository,
private readonly aiProvider: IAIProvider,
private readonly causalityService: CausalityService,
private readonly propagationEngine: PropagationEngine // NEW: Layer 3
) {}
/**
* LAYER 3: Load context with temporal relevance weighting
*/
async loadContextWithRelevance(input: LoadContextInput): Promise<{
snapshot: ContextSnapshot;
relevance: number;
}[]> {
const snapshots = await this.loadContext(input);
const currentTime = new Date();
return snapshots.map(snapshot => ({
snapshot,
relevance: this.propagationEngine.calculateRelevance(snapshot, currentTime)
}))
.filter(item => item.relevance > 0.1) // Prune low-relevance
.sort((a, b) => b.relevance - a.relevance);
}
/**
* LAYER 3: Get patterns for project
*/
async getPatterns(project: string): Promise<Pattern[]> {
return await this.propagationEngine.detectPatterns(project);
}
/**
* LAYER 3: Prime context for next interaction
*/
async primeForNext(
project: string,
currentSnapshotId?: string
): Promise<ContextSnapshot[]> {
const current = currentSnapshotId
? await this.repository.findById(currentSnapshotId)
: null;
return await this.propagationEngine.primeContext(project, current);
}
}
```
---
#### Step 3.3: Add MCP Tools
**File**: `src/application/handlers/ToolExecutionHandler.ts`
```typescript
export class ToolExecutionHandler {
// ... existing tools
/**
* NEW TOOL: get_context_with_relevance
*
* Load context with temporal decay weighting
*/
async getContextWithRelevance(args: {
project: string;
limit?: number;
}): Promise<unknown> {
const results = await this.contextService.loadContextWithRelevance({
project: args.project,
limit: args.limit || 10
});
return {
contexts: results.map(r => ({
...r.snapshot,
relevance: r.relevance.toFixed(3)
}))
};
}
/**
* NEW TOOL: detect_patterns
*
* Identify user patterns for project
*/
async detectPatterns(args: { project: string }): Promise<unknown> {
const patterns = await this.contextService.getPatterns(args.project);
return {
patterns: patterns.map(p => ({
type: p.type,
description: p.description,
confidence: p.confidence.toFixed(2)
}))
};
}
/**
* NEW TOOL: prime_context
*
* Predictively surface relevant contexts
*/
async primeContext(args: {
project: string;
currentSnapshotId?: string;
}): Promise<unknown> {
const primed = await this.contextService.primeForNext(
args.project,
args.currentSnapshotId
);
return {
suggested_contexts: primed.map(s => ({
id: s.id,
summary: s.summary,
tags: s.tags,
reason: 'High temporal relevance + pattern match'
}))
};
}
}
```
---
## Testing Strategy
### Layer 1: Causality Engine
```typescript
// src/domain/services/CausalityService.test.ts
describe('CausalityService', () => {
it('should reconstruct reasoning with dependencies', async () => {
// Arrange: Create snapshots with causal links
// Act: reconstructReasoning(snapshotId)
// Assert: Returns full causal chain
});
it('should build causal chain from root', async () => {
// Arrange: Create chain A → B → C
// Act: buildCausalChain(C.id)
// Assert: Returns [A, B, C]
});
it('should detect dependencies from temporal proximity', async () => {
// Arrange: Create snapshots in sequence
// Act: detectDependencies(project, timestamp)
// Assert: Returns recent snapshot IDs
});
});
```
### Layer 2: Memory Manager
```typescript
// src/domain/services/ContextService.test.ts
describe('ContextService - Memory Management', () => {
it('should calculate memory tier based on age', () => {
// Arrange: Snapshots with various ages
// Act: ContextSnapshot.calculateMemoryTier()
// Assert: Correct tier assignment
});
it('should mark snapshot as accessed (LRU)', async () => {
// Arrange: Existing snapshot
// Act: recordAccess(snapshotId)
// Assert: lastAccessed updated, accessCount incremented
});
it('should prune expired contexts', async () => {
// Arrange: Mix of ACTIVE, RECENT, EXPIRED
// Act: pruneExpiredContexts()
// Assert: Only EXPIRED deleted
});
});
```
### Layer 3: Propagation Engine
```typescript
// src/domain/services/PropagationEngine.test.ts
describe('PropagationEngine', () => {
it('should calculate temporal relevance with exponential decay', () => {
// Arrange: Snapshot with age = 12 hours, tier = ACTIVE
// Act: calculateRelevance(snapshot, now)
// Assert: Relevance ≈ 0.5 (half-life decay)
});
it('should detect sequential patterns', async () => {
// Arrange: 5 snapshots with sequence "conversation → file_edit"
// Act: detectPatterns(project)
// Assert: Returns pattern with confidence > 0.5
});
it('should prime context with high relevance', async () => {
// Arrange: Mix of old/new/accessed snapshots
// Act: primeContext(project, null)
// Assert: Returns top 10 by relevance, sorted DESC
});
});
```
---
## Deployment Checklist
### Pre-Deployment
- [ ] Run all tests: `npm test`
- [ ] Type check: `npm run type-check`
- [ ] Run migrations locally: `wrangler d1 execute mcp-context --local --file=./migrations/000X_*.sql`
- [ ] Test locally: `npm run dev` → verify MCP tools work
### Production Deployment
- [ ] Run migrations on production D1: `wrangler d1 execute mcp-context --file=./migrations/000X_*.sql`
- [ ] Deploy worker: `npm run deploy`
- [ ] Verify MCP server responds: `curl https://semantic-wake-intelligence-mcp.your-account.workers.dev/sse`
- [ ] Test new MCP tools from Claude Desktop or Cloudflare AI Playground
### Post-Deployment
- [ ] Monitor Cloudflare Workers logs for errors
- [ ] Test full flow: save → load with relevance → detect patterns → prime context
- [ ] Update documentation: README.md, CHANGELOG.md
- [ ] Tag release: `git tag v2.0.0-wake-brain`
---
## Summary
**Implementation Priority**:
1. **Layer 1 (Causality)** - HIGH (foundation for Layer 3)
2. **Layer 3 (Propagation)** - HIGH (biggest value add)
3. **Layer 2 (Memory tiers)** - LOW (nice-to-have enhancement)
**Expected Timeline**:
- Week 1: Layer 1 (causality tracking)
- Week 2-3: Layer 3 (propagation engine)
- Week 4: Layer 2 enhancements + testing
**Outcome**: Full 3-layer Wake Intelligence brain architecture, ready for wakeiqx.com launch.
---
**Next Steps**: Start with Layer 1 implementation → database migration → test → move to Layer 3.