## 24. Summary & Implementation Priorities *For detailed tactical roadmap with monthly milestones, see [28_project_roadmap.md](28_project_roadmap.md)* *For high-level prototype roadmap with phase breakdowns, see [24_prototype_roadmap.md](24_prototype_roadmap.md)* ### Lessons Learned Integration **Critical Findings from 30+ Platform Analysis** (See [Section 30](../concept/30_lessons_learned_application_analysis.md) for full analysis): 1. **Critical Mass Requirements**: 50+ participants required (not 20-50) for meaningful network effects 2. **Local Clustering**: ≥70% participants within 5km radius (40% higher match rates) 3. **Data Quality Strategy**: Progressive refinement with scoring and incentives (prevents "data quality death spiral") 4. **Hybrid Automation**: 80% automated matches, 20% facilitated (prevents "facilitation dependency") 5. **Geographic Expansion**: Must achieve 50+ participants AND ≥20% match rate before expanding (prevents "geographic overreach") ### Implementation Priority 1. **Critical for MVP** (Revised based on lessons learned): - ADR framework - Go 1.25 stack setup (Gin/Fiber, Neo4j driver, NATS/Redis Streams) - Basic caching (Redis) - Security foundation (JWT, OAuth2) - **Data Quality Scoring System** (prevents data quality death spiral) - **Economic Calculations Integration** (must-have feature for match acceptance) - **Hybrid Automation Model Definition** (automated vs. facilitated routing) - **50+ Participants Target** (critical mass threshold) 2. **Important for Scale**: - Event-driven architecture with Go workers - Graph database optimization - Go 1.25 experimental features (JSON v2, GreenTea GC) - Monitoring (Prometheus, OpenTelemetry) - **IoT Integration Priority** (30%+ integration rate target by Phase 2) - **Facilitator Marketplace** (enables hybrid automation model) - **Data Quality Incentives** (progressive refinement requirements) 3. **Future Enhancements**: - GraphQL (gqlgen) - Mobile app (PWA) - Advanced analytics - gRPC microservices - AI/ML integration (Phase 3+, appropriately timed) ### Key Go 1.25 Advantages - **Performance**: 10-40% GC overhead reduction with GreenTea - **JSON**: 3-10x faster with JSON v2 - **Container**: Automatic CPU resource management - **Concurrency**: Goroutines for efficient parallel processing - **Deployment**: Single binary, smaller containers ### Technical Spine That's your **technical spine**. It's tractable, uses boring reliable tech (Neo4j + Go 1.25 + React), and scales linearly with data. You can build a credible demo in a quarter and have something real to sell to municipalities or industrial parks before you ever touch pipes or pumps. ### Tactical Execution Priorities (From User Feedback Integration) **MVP Focus Areas** (address cold start and adoption): 1. **Multi-Channel Data Acquisition**: - **Seed Data**: Import public registries, building footprints, utility maps, industry association data - **Forced Adoption**: Bundle with mandatory processes (CSRD, energy audits, municipal permits) - **Partner Ingestion**: Utilities/industrial parks provide anonymized facility data - **Incentive Rewards**: Priority matching for complete profiles, fee discounts for data contributors 2. **Privacy-First Design**: Public/network-only/private tiers with anonymized discovery 3. **Low-Capex Matches**: Focus on waste pickup, maintenance, shared services (no pipes required) 4. **Trust Building**: White-label municipal operation, industry association backing 5. **Facilitator Ecosystem**: Curate and train local engineering/ESG consultancies with platform templates **Revenue Model Evolution**: 1. **Free Tier**: See + Match (drive network effects) 2. **Basic**: Shared OPEX deals (€50/facility/month) 3. **Business**: Full symbiosis + facilitators (€150/facility/month) 4. **Enterprise**: Integration + white-label (€500/facility/month) **Channel Strategy**: - **Utility Partnerships**: They provide data, you provide UI - **Municipal Dashboards**: Charge cities, give companies free access - **Facilitator Marketplace**: 10-20% commission on intermediated deals **Success Metrics**: - 20 companies, ≥5 actionable matches, ≥3 implemented connections - ≥60% data completion rate, clear revenue path within 6 months Each recommendation should be evaluated against project constraints (time, budget, team expertise) and documented as an ADR when implemented.