Kade Heyborne
48c6ddc066
- Complete planning documentation for 5-phase development - UI design specifications and integration - Domain architecture and directory templates - Technical specifications and requirements - Knowledge incorporation strategies - Dana language reference and integration notes
227 lines
8.1 KiB
Markdown
227 lines
8.1 KiB
Markdown
# MVP Definitions and Success Criteria
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This document defines what constitutes a Minimum Viable Product (MVP) at different stages of development, providing clear success criteria and decision points for scope adjustment.
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## MVP Philosophy
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Our MVP approach focuses on delivering **tangible user value** at each milestone, allowing for early user feedback and course correction. We prioritize **core functionality** over advanced features, ensuring users can accomplish primary knowledge management tasks.
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## MVP Level 1: Foundation Validation (End of Phase 1)
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**Timeline**: Week 4
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**Goal**: Validate that core technical assumptions are sound
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### Success Criteria
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- [ ] Backend API serves all documented endpoints
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- [ ] File system monitoring detects changes reliably
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- [ ] Document processing extracts text and metadata accurately
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- [ ] Dana runtime executes basic agent code safely
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- [ ] Knowledge graph stores and retrieves data correctly
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- [ ] Embedding service generates vectors for similarity search
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- [ ] All services integrate without critical errors
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- [ ] API documentation is complete and accurate
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### User Value Delivered
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- **None directly** - This is infrastructure validation
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- **Developer Value**: Confidence that technical foundation is solid
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### Go/No-Go Decision
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- **GO**: Proceed to Phase 2 UI development
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- **NO-GO**: Reassess technical approach, consider alternative technologies
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## MVP Level 2: Functional Knowledge Browser (End of Phase 2)
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**Timeline**: Week 8
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**Goal**: Deliver a working knowledge management interface
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### Success Criteria
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- [ ] Users can navigate local file directories
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- [ ] Documents (PDF, Markdown, text) display correctly
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- [ ] Basic file tree navigation works
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- [ ] Content renders in readable format
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- [ ] Dashboard shows domain overview
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- [ ] Global navigation functions properly
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- [ ] UI is responsive and follows design system
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- [ ] No critical performance issues (<2s load times)
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### User Value Delivered
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- [ ] **Primary**: Browse and read documents in organized domains
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- [ ] **Secondary**: Get overview of knowledge landscape
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- [ ] **Validation**: Users can accomplish basic PKM tasks
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### Key Features Included
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- [ ] Global Navigation Sidebar
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- [ ] Dashboard with Domain Grid
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- [ ] Knowledge Browser (3-pane layout)
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- [ ] File tree navigation
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- [ ] Document rendering (PDF, Markdown)
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- [ ] Basic content viewer
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### Features Explicitly Deferred
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- [ ] Video player integration
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- [ ] Agent customization
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- [ ] Cross-domain queries
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- [ ] Advanced analysis patterns
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- [ ] Media transcription
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### Go/No-Go Decision
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- **GO**: Launch beta with power users, proceed to Phase 3
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- **NO-GO**: Focus on UI/UX improvements, delay advanced features
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## MVP Level 3: Intelligent Content Processing (End of Phase 3)
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**Timeline**: Week 12
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**Goal**: Add automated content analysis and processing
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### Success Criteria
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- [ ] Media files are automatically detected and processed
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- [ ] Transcripts are generated and synchronized
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- [ ] Fabric analysis patterns extract insights
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- [ ] Domain agents process content intelligently
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- [ ] Analysis results display in UI
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- [ ] Background processing doesn't impact user experience
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- [ ] Content processing accuracy >80%
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### User Value Delivered
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- [ ] **Primary**: Automatic content analysis and insight extraction
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- [ ] **Secondary**: Media content becomes searchable and analyzable
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- [ ] **Validation**: System demonstrates AI value proposition
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### Key Features Added
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- [ ] Media Scraper Agent
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- [ ] Video transcript generation
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- [ ] Synchronized video transcripts
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- [ ] Fabric analysis patterns (Extract Ideas, Summarize, etc.)
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- [ ] Domain agent integration
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- [ ] Background processing queue
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### Go/No-Go Decision
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- **GO**: System shows clear AI value, proceed to developer tools
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- **NO-GO**: Focus on content processing quality, consider simplified AI approach
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## MVP Level 4: Developer Experience (End of Phase 4)
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**Timeline**: Week 16
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**Goal**: Enable agent customization and development
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### Success Criteria
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- [ ] Agent Studio loads and functions
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- [ ] Dana code editor works with syntax highlighting
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- [ ] Users can modify and test agent code
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- [ ] REPL executes Dana commands correctly
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- [ ] Agent configuration saves and loads
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- [ ] Basic graph visualization displays
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- [ ] Agent testing workflow is functional
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### User Value Delivered
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- [ ] **Primary**: Power users can customize agent behavior
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- [ ] **Secondary**: System becomes extensible and adaptable
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- [ ] **Validation**: Advanced users can tailor system to their needs
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### Key Features Added
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- [ ] Agent Studio IDE
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- [ ] Dana code editor
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- [ ] Interactive REPL
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- [ ] Context & Graph Manager
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- [ ] Agent configuration interface
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- [ ] Basic testing capabilities
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### Go/No-Go Decision
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- **GO**: Developer community can extend system, proceed to orchestration
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- **NO-GO**: Simplify customization interface, focus on presets
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## MVP Level 5: Full System Orchestration (End of Phase 5)
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**Timeline**: Week 20
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**Goal**: Complete multi-agent cross-domain system
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### Success Criteria
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- [ ] Global Orchestrator Chat functions
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- [ ] Domain scope selection works
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- [ ] Multi-agent queries return coherent responses
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- [ ] Response synthesis is accurate
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- [ ] Cross-domain agent communication works
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- [ ] System handles concurrent queries
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- [ ] Performance remains acceptable under load
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### User Value Delivered
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- [ ] **Primary**: Complex cross-domain knowledge queries
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- [ ] **Secondary**: Unified interface to entire knowledge base
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- [ ] **Validation**: System fulfills original vision
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### Key Features Added
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- [ ] Global Orchestrator Chat
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- [ ] Agent orchestration logic
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- [ ] Response synthesis
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- [ ] Cross-domain communication
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- [ ] Query routing and optimization
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## Alternative MVP Scenarios
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### Conservative MVP (Phase 2 Only)
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**When to choose**: Technical challenges in Phase 1, limited resources
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- Deliver functional knowledge browser
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- Focus on core PKM value
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- Defer AI features to future versions
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- **Success**: Users can manage knowledge effectively
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### AI-Focused MVP (Phases 1-3)
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**When to choose**: Strong AI capabilities, user demand for intelligence
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- Deliver content processing and analysis
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- Skip full developer tooling initially
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- **Success**: System demonstrates clear AI differentiation
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### Developer MVP (Phases 1-4)
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**When to choose**: Developer community focus, extensibility priority
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- Deliver agent customization capabilities
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- Defer full orchestration complexity
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- **Success**: System becomes programmable and extensible
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## Success Metrics by MVP Level
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| Metric | MVP 1 | MVP 2 | MVP 3 | MVP 4 | MVP 5 |
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| User Acquisition | N/A | 10 beta users | 50 active users | 100+ users | 500+ users |
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| Daily Active Usage | N/A | 30 min/day | 60 min/day | 90 min/day | 120 min/day |
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| Feature Completeness | 60% | 75% | 85% | 95% | 100% |
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| Performance (p95) | N/A | <2s | <3s | <4s | <5s |
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| Error Rate | <5% | <2% | <1% | <0.5% | <0.1% |
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| User Satisfaction | N/A | >7/10 | >8/10 | >8.5/10 | >9/10 |
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## Decision Framework for MVP Adjustments
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### When to Expand Scope
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- [ ] User feedback strongly positive
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- [ ] Technical foundation exceeds expectations
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- [ ] Additional resources become available
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- [ ] Market opportunity expands
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### When to Contract Scope
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- [ ] Technical blockers discovered
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- [ ] User feedback indicates different priorities
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- [ ] Resource constraints emerge
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- [ ] Market validation suggests pivot needed
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### Pivot Indicators
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- [ ] Users don't engage with core functionality
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- [ ] Technical assumptions prove invalid
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- [ ] Market has changed significantly
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- [ ] Better opportunities identified
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## Post-MVP Planning
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After achieving any MVP level:
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1. **Immediate**: Gather user feedback and usage analytics
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2. **Short-term**: Address critical bugs and usability issues
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3. **Medium-term**: Plan next feature set based on user needs
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4. **Long-term**: Consider architectural improvements and scaling
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## Communication Plan
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For each MVP achievement:
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- [ ] Internal team celebration and retrospective
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- [ ] User announcement with clear value proposition
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- [ ] Feature roadmap communication
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- [ ] Feedback collection mechanism
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- [ ] Success metrics reporting</content>
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<parameter name="filePath">docs/plans/milestones/mvp-definitions.md |