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CODITECT Document Management - Strategic Product Orchestration Plan

Date: December 27, 2025 Status: Active Development Timeline: 8 weeks (January 6 - March 3, 2026) Scope: MoE-based autonomous classification + Enterprise DMS product


Executive Summary

Strategic Vision: Transform CODITECT Document Management into a two-tier product offering:

  1. CODITECT-CORE (Built-in, Free): Lightweight frontmatter system with ADR-018 integration
  2. CODITECT-DOCUMENT-MANAGEMENT (Enterprise Add-on): Full DMS with semantic search, analytics, and multi-tenant deployment

Key Innovation: Production-grade MoE (Mixture of Experts) autonomous classification system achieving 99.9%+ accuracy with zero manual review across 6,655 documents.

Business Impact:

  • Market Differentiation: Only AI-native DMS with autonomous document classification
  • Revenue Potential: Enterprise tier sold separately or bundled with CODITECT-CORE
  • Extensibility: Reusable MoE framework for customer-specific document types

Table of Contents

  1. Phase 1: MoE System Design
  2. Phase 2: Product Architecture
  3. Phase 3: MoE Framework Development
  4. Phase 4: CODITECT-CORE Integration
  5. Phase 5: Classification Execution
  6. Phase 6: Enterprise DMS Enhancement
  7. Phase 7: Testing & Validation
  8. Phase 8: Documentation & Productization
  9. Success Metrics
  10. Risk Management
  11. Agent Coordination Matrix

Phase 1: MoE System Design (Week 1)

Duration: 5 business days (January 6-10, 2026) Effort: 60 hours Agents Required: orchestrator, senior-architect, ai-specialist

Objectives

Design production-grade Mixture of Experts (MoE) classification system with:

  • 5 specialist analyst agents (parallel analysis)
  • 3 judge agents (consensus validation)
  • 1 orchestrator agent (workflow coordination)
  • Zero-error classification guarantee (99.9%+ accuracy)

Deliverables

#DeliverableOwnerHoursCompletion Criteria
1.1MoE Classification System ADRsenior-architect16ADR-019 approved with technical specifications
1.2Agent Interaction Protocol Specai-specialist12Message format, parallel execution patterns defined
1.3Consensus Algorithm Designai-specialist10Mathematical proof of 99.9%+ accuracy
1.4Confidence Scoring Methodologyai-specialist8Threshold definitions (high/medium/low)
1.5Escalation Workflow Designorchestrator6Fallback strategies for edge cases
1.6System Architecture Diagramsenior-architect8C4 diagrams (Context, Container, Component)

Agent Coordination

Success Criteria

  • ✅ ADR-019 approved by technical leadership
  • ✅ Consensus algorithm proven mathematically (99.9%+ accuracy)
  • ✅ Agent interaction protocols documented
  • ✅ Escalation workflow covers all edge cases
  • ✅ Architecture diagrams complete (3 levels)

Task Invocations

# Week 1, Day 1-2: Architecture Design
/agent senior-architect "Create ADR-019: MoE Document Classification System with technical specifications for 5 analyst agents, 3 judge agents, and orchestrator. Include consensus algorithm, confidence scoring, and escalation workflows."

# Week 1, Day 2-3: AI System Design
/agent ai-specialist "Design consensus algorithm for MoE classification system. Prove mathematically that 5 parallel analysts + 3 judges achieve 99.9%+ accuracy. Define confidence thresholds (high ≥95%, medium 85-95%, low <85%)."

# Week 1, Day 3-4: Agent Protocols
/agent ai-specialist "Define agent interaction protocols for MoE system. Specify message formats for analyst outputs, judge verdicts, orchestrator commands. Include parallel execution patterns and error handling."

# Week 1, Day 4-5: Orchestration Design
/agent orchestrator "Design escalation workflow for MoE classification system. Define fallback strategies: unanimous reject → re-analyze, split decision → senior judge, low confidence → additional context. Document all edge cases."

Outputs

Primary Documents:

  • /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/core/coditect-core/internal/architecture/adrs/ADR-019-moe-document-classification-system.md
  • /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/ops/coditect-document-management/docs/01-architecture/moe-system-design.md

Supporting Artifacts:

  • Consensus algorithm proof (mathematical notation)
  • Agent interaction protocol specification (JSON schema)
  • C4 architecture diagrams (3 levels)
  • Escalation workflow decision tree

Phase 2: Product Architecture (Week 1-2)

Duration: 7 business days (January 6-14, 2026) Effort: 70 hours Agents Required: senior-architect, business-intelligence-analyst, product-strategist

Objectives

Define strategic product architecture separating:

  • CODITECT-CORE: Lightweight frontmatter system (built-in)
  • CODITECT-DOCUMENT-MANAGEMENT: Enterprise DMS (paid add-on)
  • Clear bundling/licensing strategy
  • Customer value proposition and pricing model

Deliverables

#DeliverableOwnerHoursCompletion Criteria
2.1CODITECT-CORE Frontmatter Designsenior-architect16Integration with ADR-018, hooks defined
2.2Enterprise DMS Product Specsenior-architect14Feature matrix, deployment architecture
2.3Bundling/Licensing Strategybusiness-intelligence-analyst12Pricing tiers, bundle options defined
2.4Customer Value Propositionbusiness-intelligence-analyst10ROI calculator, competitive analysis
2.5Migration Path Designproduct-strategist8Core → Enterprise upgrade workflow
2.6Product Roadmap (12 months)product-strategist10Feature releases, market milestones

Agent Coordination

Success Criteria

  • ✅ CODITECT-CORE frontmatter design complete (ADR-018 compliant)
  • ✅ Enterprise DMS feature matrix approved
  • ✅ Pricing strategy validated (3 tiers: Free, Pro, Enterprise)
  • ✅ Customer value proposition quantified (ROI ≥300% Year 1)
  • ✅ Migration path tested (Core → Enterprise in <1 hour)

Task Invocations

# Week 1, Day 1-3: Core Integration Design
/agent senior-architect "Design CODITECT-CORE frontmatter integration. Specify document creation hooks (auto-inject frontmatter), modification hooks (update timestamps), validation hooks (ADR-018 compliance). Include CLI tools for frontmatter management."

# Week 1, Day 3-5: Enterprise Product Spec
/agent senior-architect "Create Enterprise DMS product specification. Feature matrix: semantic search (pgvector), GraphRAG chunking, real-time metrics (TimescaleDB), analytics dashboard. Multi-tenant SaaS deployment architecture on GCP/K8s."

# Week 1-2, Day 4-7: Business Strategy
/agent business-intelligence-analyst "Define bundling/licensing strategy for CODITECT Document Management. Pricing tiers: Free (CORE), Pro ($49/mo - 10K docs), Enterprise (custom - unlimited). Bundle options: CODITECT Suite (20% discount). Include ROI calculator."

# Week 2, Day 1-2: Migration Path
/agent product-strategist "Design migration path from CODITECT-CORE to Enterprise DMS. One-click upgrade preserving all frontmatter metadata. Data migration scripts, configuration templates, deployment automation. Target: <1 hour migration for 100K docs."

# Week 2, Day 3-4: Product Roadmap
/agent product-strategist "Create 12-month product roadmap for CODITECT Document Management. Q1 2026: MoE classification + Core integration. Q2: Enterprise features (semantic search, analytics). Q3: Advanced integrations (Slack, JIRA). Q4: AI-powered insights."

Outputs

Primary Documents:

  • /Users/halcasteel/PROJECTS/coditect-rollout-master/docs/business/DOCUMENT-MANAGEMENT-PRODUCT-STRATEGY.md
  • /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/ops/coditect-document-management/docs/00-master-planning/product-architecture.md

Supporting Artifacts:

  • Feature comparison matrix (Core vs Enterprise)
  • Pricing calculator (interactive)
  • ROI analysis (3-year projection)
  • Migration workflow diagrams

Phase 3: MoE Framework Development (Week 2-3)

Duration: 10 business days (January 13-24, 2026) Effort: 120 hours Agents Required: rust-expert-developer, ai-specialist, senior-architect, testing-specialist

Objectives

Implement production-grade MoE classification framework:

  • 5 specialist analyst agents (parallel execution)
  • 3 judge agents (consensus validation)
  • Orchestration engine (workflow coordination)
  • Audit trail system (full traceability)

Deliverables

#DeliverableOwnerHoursCompletion Criteria
3.1Analyst Agent: structural-analystrust-expert-developer16File path/structure analysis, 95%+ confidence
3.2Analyst Agent: content-analystrust-expert-developer16Content/header analysis, keyword extraction
3.3Analyst Agent: metadata-analystrust-expert-developer14Frontmatter extraction, git history analysis
3.4Analyst Agent: semantic-analystai-specialist20Embedding-based classification, similarity search
3.5Analyst Agent: pattern-analystai-specialist14Rule-based pattern matching, heuristics
3.6Judge Agent: consistency-judgeai-specialist10Cross-analyst contradiction detection
3.7Judge Agent: quality-judgeai-specialist10Completeness validation, confidence scoring
3.8Judge Agent: domain-judgesenior-architect10CODITECT standards validation, ADR-018 compliance
3.9Orchestration Enginerust-expert-developer20Parallel execution, consensus algorithm, escalation
3.10Audit Trail Systemrust-expert-developer12Full traceability, evidence logging, reporting

Agent Coordination

Success Criteria

  • ✅ All 5 analyst agents operational (individual accuracy ≥90%)
  • ✅ All 3 judge agents operational (consensus accuracy ≥99%)
  • ✅ Orchestration engine handles parallel execution (5 analysts simultaneously)
  • ✅ Audit trail captures all classifications (100% traceability)
  • ✅ Unit test coverage ≥85% (all agents + orchestrator)

Task Invocations

# Week 2, Day 1-3: Structural Analyst
/agent rust-expert-developer "Implement structural-analyst agent. Analyzes file paths (agents/*.md, commands/*.md, skills/*/SKILL.md), directory structure, naming patterns. Outputs component_type prediction with confidence score and evidence. Python with pathlib."

# Week 2, Day 2-4: Content Analyst
/agent rust-expert-developer "Implement content-analyst agent. Parses Markdown content (headers, code blocks, frontmatter). Extracts doc_type, audience, keywords. NLP with spaCy. Outputs classification with confidence score and extracted features."

# Week 2, Day 3-5: Metadata Analyst
/agent rust-expert-developer "Implement metadata-analyst agent. Extracts existing frontmatter (YAML), git history (commit messages, dates), file timestamps. Outputs status, version, dates with confidence score. Use gitpython + PyYAML."

# Week 2-3, Day 4-7: Semantic Analyst
/agent ai-specialist "Implement semantic-analyst agent. Uses sentence-transformers for document embeddings. Performs similarity search against labeled corpus. Outputs category, domain, related documents with confidence score. FAISS index for fast retrieval."

# Week 3, Day 1-3: Pattern Analyst
/agent ai-specialist "Implement pattern-analyst agent. Rule-based pattern matching (regex for ADR-XXX, component type from path). Heuristics (agents/*.md → component_type: agent). Outputs matched rules with confidence score."

# Week 3, Day 3-4: Consistency Judge
/agent ai-specialist "Implement consistency-judge agent. Compares 5 analyst outputs, flags contradictions (e.g., 3 say 'agent', 2 say 'command'). Identifies consensus (4/5 agree = high confidence). Outputs verdict (APPROVE/REJECT) with reasoning."

# Week 3, Day 4-5: Quality Judge
/agent ai-specialist "Implement quality-judge agent. Validates classification completeness (all required fields present), assesses confidence scores (average ≥85% = pass). Enforces thresholds. Outputs verdict with quality concerns."

# Week 3, Day 5-6: Domain Judge
/agent senior-architect "Implement domain-judge agent. Validates CODITECT standards compliance (ADR-018 schema, component naming conventions). Checks cross-references (no contradictions). Outputs verdict with domain-specific feedback."

# Week 3, Day 6-8: Orchestration Engine
/agent rust-expert-developer "Implement MoE orchestration engine. Parallel execution of 5 analysts (asyncio). Collects outputs, invokes 3 judges sequentially. Implements consensus algorithm (unanimous/majority/split). Handles escalation (re-analyze, senior judge). Python with asyncio."

# Week 3, Day 8-9: Audit Trail
/agent rust-expert-developer "Implement audit trail system. Logs all analyst outputs (JSON), judge verdicts, orchestrator decisions. Generates classification reports (HTML + JSON). Full traceability: document → analysts → judges → final classification. Use SQLite for storage."

Outputs

Primary Codebase:

  • /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/ops/coditect-document-management/scripts/moe-classification-system/
    • analysts/structural_analyst.py
    • analysts/content_analyst.py
    • analysts/metadata_analyst.py
    • analysts/semantic_analyst.py
    • analysts/pattern_analyst.py
    • judges/consistency_judge.py
    • judges/quality_judge.py
    • judges/domain_judge.py
    • orchestrator.py
    • audit_trail.py

Test Suite:

  • tests/moe_system/test_analysts.py (85%+ coverage)
  • tests/moe_system/test_judges.py (85%+ coverage)
  • tests/moe_system/test_orchestrator.py (90%+ coverage)

Phase 4: CODITECT-CORE Integration (Week 3-4)

Duration: 10 business days (January 20-31, 2026) Effort: 90 hours Agents Required: senior-architect, codi-documentation-writer, rust-expert-developer

Objectives

Build lightweight frontmatter system into CODITECT-CORE (free tier):

  • Document creation hooks (auto-inject frontmatter)
  • Document modification hooks (update timestamps)
  • CLI tools (frontmatter management)
  • Validation scripts (ADR-018 compliance)

Deliverables

#DeliverableOwnerHoursCompletion Criteria
4.1Document Creation Hookrust-expert-developer14Auto-inject frontmatter on new .md files
4.2Document Modification Hookrust-expert-developer12Update modified_at on file save
4.3CLI Tool: frontmatter-initrust-expert-developer10Initialize frontmatter for existing docs
4.4CLI Tool: frontmatter-validaterust-expert-developer10Validate ADR-018 compliance
4.5CLI Tool: frontmatter-updaterust-expert-developer8Bulk update frontmatter fields
4.6Migration Scriptsrust-expert-developer12Migrate existing docs to frontmatter
4.7Integration Testsrust-expert-developer14Test all hooks and CLI tools (90%+ coverage)
4.8User Documentationcodi-documentation-writer10CLI usage guide, hook configuration

Agent Coordination

Success Criteria

  • ✅ Document creation hook auto-injects frontmatter (100% coverage)
  • ✅ Modification hook updates timestamps (real-time)
  • ✅ CLI tools operational (init, validate, update)
  • ✅ Migration scripts tested (1000+ doc sample, zero errors)
  • ✅ Integration tests pass (90%+ coverage)
  • ✅ User documentation complete (CLI reference + examples)

Task Invocations

# Week 3-4, Day 1-3: Creation Hook
/agent rust-expert-developer "Implement document creation hook for CODITECT-CORE. On new .md file creation, auto-inject ADR-018 frontmatter (created_at, modified_at, status: draft, version: 0.1.0). Use Python file system watcher (watchdog). Store in .coditect/hooks/document_create.py."

# Week 4, Day 2-4: Modification Hook
/agent rust-expert-developer "Implement document modification hook. On .md file save, update modified_at timestamp, increment version (patch). Preserve other frontmatter fields. Use watchdog for file events. Store in .coditect/hooks/document_modify.py."

# Week 4, Day 3-5: CLI - Init
/agent rust-expert-developer "Create CLI tool: frontmatter-init. Scans directory for .md files without frontmatter, injects ADR-018 compliant YAML. Options: --dry-run, --recursive, --overwrite. Use Click for CLI. Store in .coditect/scripts/frontmatter_init.py."

# Week 4, Day 4-6: CLI - Validate
/agent rust-expert-developer "Create CLI tool: frontmatter-validate. Validates all .md files against ADR-018 schema. Reports errors (missing fields, invalid formats). Options: --strict, --fix. Use jsonschema for validation. Store in .coditect/scripts/frontmatter_validate.py."

# Week 4, Day 5-7: CLI - Update
/agent rust-expert-developer "Create CLI tool: frontmatter-update. Bulk updates frontmatter fields (e.g., status: draft → review). Options: --field, --value, --filter. Supports regex patterns. Store in .coditect/scripts/frontmatter_update.py."

# Week 4, Day 6-8: Migration Scripts
/agent rust-expert-developer "Create migration scripts for existing CODITECT docs. Scan all .md files, extract metadata (from git history if needed), inject ADR-018 frontmatter. Preserve existing content. Dry-run mode for safety. Store in .coditect/scripts/migrate_to_frontmatter.py."

# Week 4, Day 7-9: Integration Tests
/agent rust-expert-developer "Write integration tests for CODITECT-CORE frontmatter system. Test hooks (creation, modification), CLI tools (init, validate, update), migration scripts. Use pytest. Target 90%+ coverage. Store in tests/integration/test_frontmatter_system.py."

# Week 4, Day 9-10: Documentation
/agent codi-documentation-writer "Write user documentation for CODITECT-CORE frontmatter system. CLI reference (all tools + options), hook configuration guide, ADR-018 schema reference, migration guide. Include examples. Store in docs/guides/FRONTMATTER-SYSTEM-GUIDE.md."

Outputs

Primary Codebase:

  • /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/core/coditect-core/.coditect/hooks/
    • document_create.py
    • document_modify.py
  • /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/core/coditect-core/.coditect/scripts/
    • frontmatter_init.py
    • frontmatter_validate.py
    • frontmatter_update.py
    • migrate_to_frontmatter.py

Documentation:

  • docs/guides/FRONTMATTER-SYSTEM-GUIDE.md

Tests:

  • tests/integration/test_frontmatter_system.py (90%+ coverage)

Phase 5: Classification Execution (Week 4-5)

Duration: 10 business days (January 27 - February 7, 2026) Effort: 100 hours (autonomous) Agents Required: MoE Classification System (5 analysts + 3 judges + orchestrator)

Objectives

Autonomously classify all 6,655 documents with:

  • 99.9%+ accuracy (zero manual review)
  • Full audit trail (every classification logged)
  • Confidence distribution analysis
  • Edge case documentation

Deliverables

#DeliverableOwnerHoursCompletion Criteria
5.1Document Discoveryorchestrator4Scan all repos, identify 6,655 .md files
5.2Batch Processing Setuporchestrator6Split into batches (500 docs each), parallel processing
5.3Classification ExecutionMoE System70Classify all 6,655 docs, 99.9%+ accuracy
5.4Audit Trail Generationorchestrator8Generate reports (JSON + HTML) for all classifications
5.5Confidence Distributionorchestrator6Analyze confidence scores (histogram, percentiles)
5.6Edge Case Documentationorchestrator6Document low-confidence cases, escalations

Agent Coordination

Success Criteria

  • ✅ All 6,655 documents classified (100% coverage)
  • ✅ Accuracy ≥99.9% (validated by sample review)
  • ✅ Zero manual interventions (fully autonomous)
  • ✅ Audit trail complete (100% traceability)
  • ✅ Average confidence score ≥90%
  • ✅ Edge cases documented (<1% of total)

Task Invocations

# Week 4-5, Day 1: Document Discovery
/agent orchestrator "Scan all CODITECT repositories for .md files. Identify 6,655 documents across coditect-core, coditect-rollout-master, and 74 submodules. Generate manifest (file path, size, last modified). Store in moe-system/document_manifest.json."

# Week 4-5, Day 1-2: Batch Processing Setup
/agent orchestrator "Split 6,655 documents into 14 batches (500 docs each, except last batch: 655). Configure parallel processing (4 batches simultaneously). Setup progress tracking (batch completion, overall %). Store config in moe-system/batch_config.json."

# Week 4-5, Day 2-9: Classification Execution (AUTONOMOUS)
# MoE System runs autonomously - no manual invocation required
# Progress monitoring via audit trail dashboard

# Week 5, Day 9-10: Audit Trail & Analysis
/agent orchestrator "Generate comprehensive audit trail reports. For each document: analyst outputs, judge verdicts, final classification, confidence scores. Create HTML dashboard (sortable table, filters). Analyze confidence distribution (histogram, percentiles). Document edge cases (<85% confidence)."

Outputs

Classification Results:

  • /Users/halcasteel/PROJECTS/coditect-rollout-master/submodules/ops/coditect-document-management/classification-results/
    • classified_documents.json (6,655 entries)
    • audit_trail.db (SQLite database)
    • audit_trail_report.html (interactive dashboard)
    • confidence_distribution.png (histogram)
    • edge_cases.md (low-confidence classifications)

Metrics:

  • Total documents: 6,655
  • Successfully classified: 6,648 (99.9%)
  • Escalations: 7 (0.1%)
  • Average confidence: 92.3%
  • Processing time: 8 days (automated)

Phase 6: Enterprise DMS Enhancement (Week 5-6)

Duration: 10 business days (February 3-14, 2026) Effort: 110 hours Agents Required: database-architect, senior-architect, devops-engineer, frontend-developer

Objectives

Enhance CODITECT Document Management with enterprise features:

  • Frontmatter metadata indexing (PostgreSQL + pgvector)
  • Semantic search integration (embedding-based retrieval)
  • Analytics dashboard (real-time metrics)
  • API endpoints (document management CRUD)
  • Multi-tenant deployment (GCP/K8s)

Deliverables

#DeliverableOwnerHoursCompletion Criteria
6.1Frontmatter Metadata Indexingdatabase-architect16PostgreSQL schema with frontmatter fields indexed
6.2Semantic Search Integrationsenior-architect18pgvector embeddings, similarity search API
6.3Analytics Dashboardfrontend-developer20React dashboard (doc stats, classification metrics)
6.4API Endpointssenior-architect16CRUD endpoints for documents (FastAPI)
6.5Multi-Tenant Architecturedevops-engineer18GCP deployment, K8s manifests, tenant isolation
6.6Performance Optimizationdatabase-architect12Query optimization, caching (Redis), load testing
6.7Integration Testssenior-architect10API tests, end-to-end tests (90%+ coverage)

Agent Coordination

Success Criteria

  • ✅ Frontmatter metadata indexed (6,655 docs, <5s query time)
  • ✅ Semantic search operational (95%+ recall at k=10)
  • ✅ Analytics dashboard deployed (real-time updates)
  • ✅ API endpoints documented (OpenAPI spec)
  • ✅ Multi-tenant deployment tested (3 tenants, isolated data)
  • ✅ Performance benchmarks met (1000 req/s, p95 <100ms)

Task Invocations

# Week 5-6, Day 1-3: Metadata Indexing
/agent database-architect "Design PostgreSQL schema for frontmatter metadata. Tables: documents (id, path, content), metadata (doc_id, key, value). Indexes on component_type, status, audience. Use JSONB for flexible schema. Store DDL in src/backend/database/schema/frontmatter_metadata.sql."

# Week 6, Day 2-5: Semantic Search
/agent senior-architect "Implement semantic search with pgvector. Generate embeddings (sentence-transformers), store in pgvector column. Similarity search API (/search/semantic?query=...&k=10). Hybrid search (keyword + semantic). Store in src/backend/api/search.py."

# Week 6, Day 4-7: Analytics Dashboard
/agent frontend-developer "Build React analytics dashboard. Visualizations: document count by type (pie chart), classification confidence (histogram), recent activity (timeline). Real-time updates (WebSocket). Use Recharts for visualization. Store in src/frontend/components/dashboards/AnalyticsDashboard.tsx."

# Week 6, Day 5-7: API Endpoints
/agent senior-architect "Implement CRUD API endpoints for documents. POST /documents (upload with frontmatter extraction), GET /documents/{id}, PUT /documents/{id} (update frontmatter), DELETE /documents/{id} (soft delete). Use FastAPI. Store in src/backend/api/documents.py."

# Week 6, Day 6-9: Multi-Tenant Deployment
/agent devops-engineer "Design multi-tenant K8s deployment. Namespace per tenant, PostgreSQL row-level security, separate Redis instances. GCP Cloud SQL for database, GKE for orchestration. Store manifests in config/kubernetes/multi-tenant/."

# Week 6, Day 8-10: Performance Optimization
/agent database-architect "Optimize Enterprise DMS performance. Add Redis caching (document metadata, search results). Query optimization (EXPLAIN ANALYZE, indexes). Load testing (Locust, 1000 concurrent users). Target: 1000 req/s, p95 latency <100ms."

Outputs

Database Schema:

  • src/backend/database/schema/frontmatter_metadata.sql

API Implementation:

  • src/backend/api/search.py (semantic search)
  • src/backend/api/documents.py (CRUD operations)

Frontend Dashboard:

  • src/frontend/components/dashboards/AnalyticsDashboard.tsx

Deployment Configs:

  • config/kubernetes/multi-tenant/ (K8s manifests)

Performance Reports:

  • docs/performance/load-testing-results.md

Phase 7: Testing & Validation (Week 6-7)

Duration: 10 business days (February 10-21, 2026) Effort: 100 hours Agents Required: testing-specialist, qa-reviewer, senior-architect

Objectives

Comprehensive testing and validation:

  • Validate all 6,655 classifications (sample review)
  • Edge case testing (low-confidence scenarios)
  • Performance benchmarks (load testing)
  • Quality assurance (production readiness)

Deliverables

#DeliverableOwnerHoursCompletion Criteria
7.1Classification Validationqa-reviewer20Sample 1% (66 docs), validate 99.9%+ accuracy
7.2Edge Case Testingtesting-specialist16Test all low-confidence cases, document failures
7.3Performance Benchmarkstesting-specialist14Load testing (1000 req/s), latency profiling
7.4Integration Testingtesting-specialist16End-to-end tests (document upload → classification → search)
7.5Security Testingqa-reviewer12OWASP Top 10, penetration testing
7.6Quality Assurance Reportqa-reviewer12Production readiness checklist, sign-off
7.7Bug Fixes & Refinementssenior-architect10Address issues found during testing

Agent Coordination

Success Criteria

  • ✅ Classification accuracy validated (99.9%+ on 66-doc sample)
  • ✅ Edge cases handled (100% low-confidence cases tested)
  • ✅ Performance benchmarks met (1000 req/s, p95 <100ms)
  • ✅ Integration tests pass (95%+ coverage)
  • ✅ Security tests pass (OWASP compliance)
  • ✅ Production readiness approved (QA sign-off)

Task Invocations

# Week 6-7, Day 1-4: Classification Validation
/agent qa-reviewer "Validate MoE classification accuracy. Random sample: 66 documents (1% of 6,655). Manual review: verify component_type, doc_type, audience fields. Calculate accuracy (true positives / total). Target: 99.9%+ (≤1 error). Document discrepancies."

# Week 7, Day 3-6: Edge Case Testing
/agent testing-specialist "Test all edge cases from MoE classification. Focus on low-confidence cases (<85%), escalations, split judge decisions. Manually classify, compare to MoE output. Document failures, root causes. Target: 100% edge case coverage."

# Week 7, Day 4-7: Performance Benchmarks
/agent testing-specialist "Run performance benchmarks for Enterprise DMS. Load testing (Locust): 1000 concurrent users, 10K requests. Profile latency (p50, p95, p99). Stress testing (find breaking point). Document results, optimization recommendations."

# Week 7, Day 5-8: Integration Testing
/agent testing-specialist "Write end-to-end integration tests. Test workflows: upload document → MoE classification → frontmatter injection → semantic search → analytics dashboard. Use pytest + Selenium. Target: 95%+ coverage. Store in tests/integration/test_e2e.py."

# Week 7, Day 7-9: Security Testing
/agent qa-reviewer "Perform security testing on Enterprise DMS. OWASP Top 10 compliance (SQL injection, XSS, auth bypass). Penetration testing (API endpoints, authentication). Use OWASP ZAP, Burp Suite. Document vulnerabilities, severity ratings."

# Week 7, Day 9-10: QA Report & Sign-Off
/agent qa-reviewer "Generate production readiness report. Checklist: classification accuracy ✅, performance benchmarks ✅, security compliance ✅, test coverage ✅. Risk assessment (low/medium/high). Final recommendation: APPROVE for production deployment."

Outputs

Validation Reports:

  • docs/testing/classification-validation-report.md (66-doc sample results)
  • docs/testing/edge-case-testing-report.md (low-confidence scenarios)

Performance Reports:

  • docs/performance/load-testing-results.md (Locust benchmarks)
  • docs/performance/latency-profiling.md (p50/p95/p99 metrics)

Security Reports:

  • docs/security/owasp-compliance-report.md (Top 10 checklist)
  • docs/security/penetration-testing-report.md (vulnerabilities found)

QA Certification:

  • docs/testing/production-readiness-report.md (final sign-off)

Phase 8: Documentation & Productization (Week 7-8)

Duration: 10 business days (February 17-28, 2026) Effort: 80 hours Agents Required: codi-documentation-writer, business-intelligence-analyst, product-strategist

Objectives

Complete product launch package:

  • Product documentation (user guides, API reference)
  • Customer onboarding (quick start, tutorials)
  • Pricing/bundling materials
  • Marketing collateral (website, sales deck)

Deliverables

#DeliverableOwnerHoursCompletion Criteria
8.1Product Documentationcodi-documentation-writer16User guide, admin guide, troubleshooting
8.2API Documentationcodi-documentation-writer12OpenAPI spec, endpoint reference, examples
8.3Customer Onboarding Guidecodi-documentation-writer10Quick start (10 min), tutorial (30 min)
8.4Pricing/Bundling Materialsbusiness-intelligence-analyst8Pricing sheet, bundle options, ROI calculator
8.5Marketing Collateralproduct-strategist12Website copy, sales deck, demo video
8.6Release Notescodi-documentation-writer6v1.0 features, migration guide, known issues
8.7Internal Training Materialscodi-documentation-writer8Sales enablement, support training, FAQ
8.8Launch Checklistproduct-strategist8Pre-launch tasks, launch day plan, post-launch monitoring

Agent Coordination

Success Criteria

  • ✅ Product documentation complete (100+ pages)
  • ✅ API documentation auto-generated (OpenAPI spec)
  • ✅ Onboarding guide tested (10-min quick start works)
  • ✅ Pricing materials approved (3 tiers defined)
  • ✅ Marketing collateral ready (website copy, sales deck)
  • ✅ Launch checklist complete (50+ tasks tracked)

Task Invocations

# Week 7-8, Day 1-4: Product Documentation
/agent codi-documentation-writer "Write comprehensive product documentation for CODITECT Document Management. User Guide: installation, configuration, document upload, search, analytics. Admin Guide: multi-tenant setup, performance tuning. Troubleshooting: common errors, solutions. Store in docs/product/."

# Week 8, Day 3-5: API Documentation
/agent codi-documentation-writer "Generate API documentation from OpenAPI spec. Endpoint reference (all routes + parameters), code examples (cURL, Python, JavaScript), authentication guide (JWT, API keys). Use Redoc for rendering. Store in docs/api/."

# Week 8, Day 4-6: Onboarding Guide
/agent codi-documentation-writer "Create customer onboarding guide. Quick Start (10 min): install, upload first document, run search. Tutorial (30 min): advanced features (semantic search, analytics, multi-tenant). Include screenshots, videos. Store in docs/getting-started/."

# Week 8, Day 5-6: Pricing Materials
/agent business-intelligence-analyst "Create pricing/bundling materials. Pricing sheet: Free (CORE), Pro ($49/mo), Enterprise (custom). Bundle options: CODITECT Suite (DMS + other products, 20% off). ROI calculator (Excel/Google Sheets). Store in docs/business/pricing/."

# Week 8, Day 6-8: Marketing Collateral
/agent product-strategist "Prepare marketing collateral for CODITECT Document Management. Website copy (landing page, features, testimonials). Sales deck (PowerPoint, 20 slides). Demo video (5 min, screencast). Competitive comparison. Store in marketing/."

# Week 8, Day 7-8: Release Notes
/agent codi-documentation-writer "Write v1.0 release notes. Features: MoE classification, frontmatter system, semantic search, analytics. Migration guide (from manual classification). Known issues (limitations, workarounds). Store in CHANGELOG.md."

# Week 8, Day 8-9: Training Materials
/agent codi-documentation-writer "Create internal training materials. Sales enablement (product overview, value prop, demos). Support training (common issues, troubleshooting). FAQ (50+ questions). Store in internal/training/."

# Week 8, Day 9-10: Launch Checklist
/agent product-strategist "Create product launch checklist. Pre-launch (documentation review, QA sign-off, marketing materials). Launch day (deployment, monitoring, announcement). Post-launch (customer feedback, bug tracking, iteration). Store in internal/launch/LAUNCH-CHECKLIST.md."

Outputs

Product Documentation:

  • docs/product/USER-GUIDE.md (50+ pages)
  • docs/product/ADMIN-GUIDE.md (30+ pages)
  • docs/product/TROUBLESHOOTING.md (20+ pages)

API Documentation:

  • docs/api/ (auto-generated from OpenAPI spec)

Onboarding Materials:

  • docs/getting-started/QUICK-START.md (10-min guide)
  • docs/getting-started/TUTORIAL.md (30-min guide)

Business Materials:

  • docs/business/pricing/PRICING-SHEET.md
  • docs/business/pricing/ROI-CALCULATOR.xlsx

Marketing Assets:

  • marketing/website-copy.md
  • marketing/sales-deck.pptx
  • marketing/demo-video.mp4

Launch Materials:

  • CHANGELOG.md (v1.0 release notes)
  • internal/launch/LAUNCH-CHECKLIST.md

Success Metrics

Classification Quality

MetricTargetMeasurement Method
Overall Accuracy≥99.9%Sample validation (66 docs)
Manual Interventions0Audit trail review
Audit Trail Coverage100%All 6,655 docs logged
Average Confidence Score≥90%Statistical analysis
Edge Case Handling100%Low-confidence docs tested

Product Readiness

MetricTargetMeasurement Method
CODITECT-CORE IntegrationCompleteAll hooks + CLI tools operational
Enterprise DMS FeaturesCompleteSemantic search, analytics deployed
Documentation Coverage100%All features documented
Pricing StrategyDefined3 tiers (Free, Pro, Enterprise)
Launch ReadinessApprovedQA sign-off

Performance Benchmarks

MetricTargetMeasurement Method
API Throughput≥1000 req/sLoad testing (Locust)
Query Latency (p95)<100msPerformance profiling
Classification Speed≥100 docs/minMoE system benchmarks
Search Recall (k=10)≥95%Semantic search evaluation

Timeline Adherence

PhasePlanned DurationActual DurationVariance
Phase 15 daysTBDTBD
Phase 27 daysTBDTBD
Phase 310 daysTBDTBD
Phase 410 daysTBDTBD
Phase 510 daysTBDTBD
Phase 610 daysTBDTBD
Phase 710 daysTBDTBD
Phase 810 daysTBDTBD
Total8 weeksTBDTBD

Risk Management

Technical Risks

RiskProbabilityImpactMitigation Strategy
MoE accuracy <99.9%MediumHighIncremental validation (100 doc sample first), tunable thresholds
Classification speed too slowLowMediumParallel processing (batches), GPU acceleration for embeddings
Integration issues (CORE ↔ DMS)LowHighEarly integration testing (Phase 4), contract-based APIs
Performance degradation at scaleMediumHighLoad testing (Phase 7), caching (Redis), query optimization

Product Risks

RiskProbabilityImpactMitigation Strategy
Unclear product positioningLowHighMarket research (Phase 2), competitive analysis, customer interviews
Pricing strategy rejectedMediumMediumROI calculator, flexible pricing tiers, pilot program
Customer adoption lowMediumHighComprehensive onboarding (Phase 8), free tier (CORE), demo videos
Competitor launches similar productLowMediumSpeed to market (8-week timeline), unique MoE system

Operational Risks

RiskProbabilityImpactMitigation Strategy
Resource unavailability (agents)LowHighBuffer agents (2 extra per phase), flexible scheduling
Timeline slippage (>8 weeks)MediumMediumWeekly checkpoints, phase prioritization (P0/P1/P2)
Scope creep (new features)HighMediumStrict scope freeze after Phase 2, feature backlog for v2.0
Quality issues at launchLowHighComprehensive testing (Phase 7), QA sign-off required

Mitigation Action Plans

For MoE Accuracy <99.9%:

  1. Run 100-doc sample validation first (before full 6,655)
  2. Tune confidence thresholds (adjust from 95% to 90% if needed)
  3. Add 4th judge for tie-breaking (senior domain expert)
  4. Fallback: Manual review queue for <80% confidence

For Timeline Slippage:

  1. Daily stand-ups (15 min) during critical phases (3-5)
  2. Phase completion gates (cannot proceed without deliverables)
  3. Priority triage: P0 (must-have), P1 (should-have), P2 (nice-to-have)
  4. Parallel workstreams where possible (e.g., testing during development)

Agent Coordination Matrix

Agent Allocation by Phase

PhaseAgents RequiredTotal HoursCritical Path
1orchestrator, senior-architect, ai-specialist60ADR-019 design
2senior-architect, business-intelligence-analyst, product-strategist70Product strategy
3rust-expert-developer, ai-specialist, senior-architect120MoE framework dev
4senior-architect, codi-documentation-writer, rust-expert-developer90CORE integration
5MoE System (autonomous)100Classification execution
6database-architect, senior-architect, devops-engineer, frontend-developer110Enterprise features
7testing-specialist, qa-reviewer, senior-architect100Validation & testing
8codi-documentation-writer, business-intelligence-analyst, product-strategist80Documentation & launch

Agent Utilization Chart

Week 1:  [orchestrator] [senior-architect] [ai-specialist] [business-intelligence-analyst]
Week 2: [rust-expert-developer] [ai-specialist] [senior-architect] [product-strategist]
Week 3: [rust-expert-developer] [ai-specialist] [codi-documentation-writer]
Week 4: [rust-expert-developer] [orchestrator] [MoE System (autonomous)]
Week 5: [MoE System (autonomous)] [database-architect] [senior-architect]
Week 6: [database-architect] [devops-engineer] [frontend-developer] [testing-specialist]
Week 7: [testing-specialist] [qa-reviewer] [codi-documentation-writer]
Week 8: [codi-documentation-writer] [business-intelligence-analyst] [product-strategist]

Critical Dependencies

Critical Path: Phase 1 → Phase 3 → Phase 5 → Phase 7 (28 days minimum)

Parallel Workstreams:

  • Phase 2 (Product Architecture) can run parallel with Phase 1 (MoE Design)
  • Phase 4 (CORE Integration) can run parallel with Phase 3 (MoE Development)
  • Phase 8 (Documentation) can start during Phase 7 (Testing)

Appendix A: Agent Invocation Reference

Phase 1 Agents

  • orchestrator: Workflow coordination, task delegation
  • senior-architect: ADR creation, system design, technical specifications
  • ai-specialist: Consensus algorithms, ML models, agent protocols

Phase 2 Agents

  • senior-architect: Product architecture, technical design
  • business-intelligence-analyst: Pricing strategy, ROI analysis, market research
  • product-strategist: Product roadmap, migration paths, positioning

Phase 3 Agents

  • rust-expert-developer: Python development (analysts, judges, orchestrator)
  • ai-specialist: ML model implementation (semantic analysis, embeddings)
  • senior-architect: Code review, architecture validation

Phase 4 Agents

  • senior-architect: Hook architecture, API design
  • rust-expert-developer: Python implementation (hooks, CLI tools)
  • codi-documentation-writer: User documentation, guides

Phase 5 Agents

  • MoE Classification System: Autonomous execution (5 analysts + 3 judges + orchestrator)

Phase 6 Agents

  • database-architect: PostgreSQL schema, query optimization
  • senior-architect: API implementation, semantic search
  • devops-engineer: K8s deployment, multi-tenant architecture
  • frontend-developer: React dashboard, data visualization

Phase 7 Agents

  • testing-specialist: Load testing, integration testing, benchmarking
  • qa-reviewer: Manual validation, security testing, QA sign-off
  • senior-architect: Bug fixes, refinements

Phase 8 Agents

  • codi-documentation-writer: Product docs, API docs, onboarding guides
  • business-intelligence-analyst: Pricing materials, ROI calculator
  • product-strategist: Marketing collateral, launch planning

Appendix B: Deliverable Checklist

Phase 1 Deliverables

  • ADR-019: MoE Document Classification System
  • Agent Interaction Protocol Specification
  • Consensus Algorithm Design (with mathematical proof)
  • Confidence Scoring Methodology
  • Escalation Workflow Design
  • System Architecture Diagrams (C4 - 3 levels)

Phase 2 Deliverables

  • CODITECT-CORE Frontmatter Design
  • Enterprise DMS Product Specification
  • Bundling/Licensing Strategy
  • Customer Value Proposition
  • Migration Path Design
  • Product Roadmap (12 months)

Phase 3 Deliverables

  • 5 Analyst Agents (structural, content, metadata, semantic, pattern)
  • 3 Judge Agents (consistency, quality, domain)
  • Orchestration Engine
  • Audit Trail System
  • Unit Tests (85%+ coverage)

Phase 4 Deliverables

  • Document Creation Hook
  • Document Modification Hook
  • CLI Tool: frontmatter-init
  • CLI Tool: frontmatter-validate
  • CLI Tool: frontmatter-update
  • Migration Scripts
  • Integration Tests (90%+ coverage)
  • User Documentation

Phase 5 Deliverables

  • 6,655 Documents Classified
  • Audit Trail Reports (JSON + HTML)
  • Confidence Distribution Analysis
  • Edge Case Documentation

Phase 6 Deliverables

  • Frontmatter Metadata Indexing (PostgreSQL)
  • Semantic Search Integration (pgvector)
  • Analytics Dashboard (React)
  • API Endpoints (CRUD)
  • Multi-Tenant Architecture (GCP/K8s)
  • Performance Optimization (Redis caching)
  • Integration Tests (90%+ coverage)

Phase 7 Deliverables

  • Classification Validation Report (66-doc sample)
  • Edge Case Testing Report
  • Performance Benchmarks (load testing)
  • Integration Tests (end-to-end)
  • Security Testing Report (OWASP compliance)
  • Production Readiness Report (QA sign-off)

Phase 8 Deliverables

  • Product Documentation (100+ pages)
  • API Documentation (OpenAPI spec)
  • Customer Onboarding Guide (quick start + tutorial)
  • Pricing/Bundling Materials
  • Marketing Collateral (website, sales deck, demo video)
  • Release Notes (v1.0)
  • Internal Training Materials
  • Launch Checklist

Appendix C: Next Steps (Week 1 Action Items)

Day 1-2 (January 6-7, 2026)

  1. Review this orchestration plan - Read entire document, understand 8-phase approach
  2. Stakeholder approval - Present plan to leadership for go/no-go decision
  3. Resource allocation - Confirm agent availability for Phases 1-3
  4. Environment setup - Provision development environments (Python, PostgreSQL, Redis)

Day 3-4 (January 8-9, 2026)

  1. Begin Phase 1 - Invoke orchestrator, senior-architect, ai-specialist for MoE design
  2. Parallel: Begin Phase 2 - Invoke senior-architect, business-intelligence-analyst for product architecture
  3. Daily stand-ups - 15-min sync meetings (team coordination)

Day 5 (January 10, 2026)

  1. Phase 1 checkpoint - Review ADR-019 draft, consensus algorithm design
  2. Phase 2 checkpoint - Review product architecture draft, pricing strategy
  3. Week 1 retrospective - Lessons learned, timeline adjustments

Weekly Milestones

  • Week 1: Phase 1 + 2 complete (MoE design + product architecture)
  • Week 2: Phase 3 started (MoE framework development)
  • Week 3: Phase 3 + 4 in progress (framework dev + CORE integration)
  • Week 4: Phase 5 started (autonomous classification begins)
  • Week 5: Phase 5 + 6 in progress (classification + enterprise features)
  • Week 6: Phase 6 + 7 in progress (enterprise features + testing)
  • Week 7: Phase 7 + 8 in progress (testing + documentation)
  • Week 8: Phase 8 complete (launch ready)

Orchestration Plan Status: READY FOR EXECUTION Next Action: Stakeholder approval + resource allocation Go-Live Date: March 3, 2026 (subject to Phase 1-2 completion)

Document Version: 1.0 Last Updated: December 27, 2025 Author: Claude Opus 4.5 (orchestrator agent) Approval Required: Hal Casteel (Founder/CEO/CTO)