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Vision to MVP Mapping

Version: 1.0 Status: Active Framework Last Updated: 2025-10-13

Purpose

This document bridges our ambitious 2-3 year vision with our pragmatic 8-12 week MVP. It prevents scope creep while maintaining clear sight of our destination.

Mapping Framework

Feature Categories

Vision Feature MVP Implementation Evolution Trigger Priority
AI agent system No AI - Rule-based processing only Customer demand + revenue Post-MVP
ML pattern recognition Hardcoded patterns 500+ questions in bank Year 2
Intelligent question inference Simple DB lookups & key-value reuse 50+ active customers 6 months
Advanced risk intelligence Basic risk identification 100+ risk assessments Year 2
Enterprise integrations Kinde + Supabase only Enterprise customer demand Year 2
Global compliance frameworks Australian focus only International customer Year 3

MVP Features (Launch Day)

1. Board Governance Pack

MVP: Template-generated from structured data (no AI) Vision: Auto-updates from all system data Trigger: When data sources > 5

2. Domain Discovery

MVP: 20-second basic DNS/SSL/subdomain scan Vision: Deep organizational intelligence gathering Trigger: ML model trained on 1000+ scans

3. Unified Question Bank

MVP: 50-100 questions with manual mappings to policies/controls, simple database lookup for reuse Vision: AI auto-categorization, intelligent routing, ML inference for crossover Trigger: Question bank > 500 items + 50+ active customers Key Point: Database structure IS in MVP (it's not AI), but "intelligence" features are post-MVP

4. Framework Tags

MVP: Static tags ([E8], [s180]) Vision: Dynamic risk scoring per tag Trigger: Sufficient compliance data

5. WhatsApp Integration

MVP: Not included - Use email for critical notifications Vision: Full conversational interface with AI capabilities Trigger: User demand + proven notification value + infrastructure in place Priority: Post-MVP (Month 3-6)

6. Essential Eight Assessment

MVP: Structured questionnaire + simple pre-fill from DB lookups Vision: Automated evidence collection Trigger: Integration partnerships

7. Policy Management

MVP: Template selection + variable find-replace (no AI generation) Vision: AI policy generation Trigger: Legal review + 100 policies + customer demand

8. Risk Register

MVP: Manual entry with templates Vision: Auto-population from assessments Trigger: Risk pattern recognition

Graduation Criteria

Features graduate from MVP to Vision when:

Technical Triggers

  • Performance bottlenecks emerge
  • Scale requires architecture change
  • Integration opportunities arise

Business Triggers

  • Customer explicitly requests
  • Competitive pressure
  • Revenue supports complexity

Data Triggers

  • Sufficient training data
  • Clear usage patterns
  • Validated assumptions

Anti-Patterns to Avoid

❌ Feature Creep

  • "Just add ML real quick"
  • "Make it smart from day one"
  • "Build for scale immediately"

✅ Progressive Enhancement

  • Start simple, measure everything
  • Add intelligence where proven valuable
  • Scale when metrics demand it

Decision Framework

When considering a feature:

1. Can we deliver value without it in MVP?
   → Yes: Move to Vision
   → No: Include in MVP (minimally)

2. Will customers pay more for it?
   → Yes: Fast-track post-MVP
   → No: Keep in Vision

3. Does it 10x an existing feature?
   → Yes: Priority enhancement
   → No: Standard roadmap

4. Do we have data to build it right?
   → Yes: Consider for roadmap
   → No: Definitely Vision

Timeline Overview

Phase 1: MVP (Weeks 1-12)

  • 8 core features
  • Single agent architecture
  • Australian market focus
  • 3-person team

Phase 2: Enhancement (Months 3-6)

  • Question intelligence
  • Better UI/UX
  • Performance optimization
  • 5-person team

Phase 3: Intelligence (Months 6-12)

  • ML pattern recognition
  • Multi-source integration
  • Advanced automation
  • 8-person team

Phase 4: Scale (Year 2+)

  • Multi-agent architecture
  • Enterprise features
  • Global expansion
  • 15+ person team

Measurement Points

Track these to validate graduation timing:

User Metrics

  • Feature adoption rates
  • Task completion times
  • Support ticket themes
  • Feature request frequency

System Metrics

  • Response latency
  • Queue depths
  • Error rates
  • Data volumes

Business Metrics

  • Customer acquisition cost
  • Feature-driven upgrades
  • Churn by feature usage
  • Revenue per feature

Communication Guidelines

To Customers

  • Share MVP roadmap openly
  • Vision as "exploring for future"
  • No timeline commitments
  • Feature voting/feedback

To Investors

  • Clear MVP/Vision separation
  • Metrics-driven evolution
  • Disciplined feature graduation
  • Focus on capital efficiency

To Team

  • MVP is not "lesser"
  • Vision guides but doesn't distract
  • Celebrate constraint creativity
  • Document learnings

Review Cadence

  • Weekly: Check evolution triggers
  • Monthly: Review graduation candidates
  • Quarterly: Update vision mapping
  • Yearly: Major strategy revision

Remember

"The vision shows where we're going. The MVP gets us started. The triggers tell us when to evolve."

Every feature in vision will eventually graduate - but only when the time is right.