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
155 lines
4.8 KiB
Markdown
155 lines
4.8 KiB
Markdown
# Phase 3: Advanced Features and AI Integration
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**Timeline**: Weeks 9-16
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**Objective**: Implement advanced AI capabilities, content processing, and intelligent features
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**Success Criteria**: Functional AI agents, automated content processing, and advanced knowledge features
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## Overview
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Phase 3 focuses on the intelligent features that make the Second Brain truly powerful. This includes AI agents, automated content processing, and advanced knowledge management capabilities.
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## Critical Dependencies
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- **Requires Phase 2**: Functional UI and backend integration
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- **AI/ML Infrastructure**: Access to embedding models and processing
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- **Content Processing**: Robust document handling pipeline
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- **Agent Framework**: Working Dana integration
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## Detailed Implementation Plan
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### Week 9-10: Content Processing Pipeline
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#### Advanced Document Processing
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- [ ] Implement OCR for images/PDFs (Tesseract)
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- [ ] Add audio transcription (Whisper)
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- [ ] Create video processing pipeline
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- [ ] Implement content classification
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- [ ] Add metadata extraction and enrichment
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#### Intelligent Chunking
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- [ ] Semantic text chunking algorithms
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- [ ] Context-aware document splitting
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- [ ] Hierarchical content organization
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- [ ] Cross-reference detection
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- [ ] Content quality assessment
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### Week 11-12: AI Agent Development
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#### Core Agent Capabilities
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- [ ] Research agent for automated information gathering
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- [ ] Summarization agent for content condensation
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- [ ] Connection agent for relationship discovery
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- [ ] Question-answering agent
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- [ ] Content generation agent
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#### Agent Orchestration
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- [ ] Agent communication framework
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- [ ] Workflow orchestration system
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- [ ] Agent scheduling and prioritization
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- [ ] Conflict resolution mechanisms
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- [ ] Agent performance monitoring
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### Week 13-14: Knowledge Enhancement
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#### Automated Linking
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- [ ] Semantic similarity detection
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- [ ] Cross-document relationship mining
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- [ ] Knowledge graph expansion
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- [ ] Citation and reference tracking
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- [ ] Concept mapping and clustering
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#### Content Enrichment
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- [ ] Automated tagging and categorization
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- [ ] Entity extraction and linking
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- [ ] Timeline reconstruction
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- [ ] Topic modeling and clustering
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- [ ] Content gap identification
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### Week 15-16: Advanced Features
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#### Intelligent Search
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- [ ] Natural language query processing
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- [ ] Contextual search with conversation history
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- [ ] Multi-modal search (text, image, audio)
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- [ ] Search result ranking and relevance
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- [ ] Search analytics and insights
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#### Personalization
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- [ ] User behavior analysis
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- [ ] Adaptive interface customization
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- [ ] Personalized recommendations
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- [ ] Learning user preferences
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- [ ] Dynamic content prioritization
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## Deliverables
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### AI Features
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- [ ] Functional AI agents with Dana integration
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- [ ] Automated content processing pipeline
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- [ ] Intelligent search and discovery
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- [ ] Knowledge graph enhancement
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- [ ] Personalization engine
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### Processing Capabilities
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- [ ] Multi-format content ingestion
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- [ ] Advanced document analysis
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- [ ] Automated metadata generation
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- [ ] Content quality assessment
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- [ ] Cross-reference detection
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### Intelligence Features
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- [ ] Semantic search capabilities
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- [ ] Automated knowledge linking
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- [ ] Content summarization
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- [ ] Question answering system
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- [ ] Recommendation engine
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## Success Metrics
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- [ ] Content processing accuracy > 95%
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- [ ] AI agent response time < 10 seconds
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- [ ] Search relevance score > 85%
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- [ ] Knowledge graph growth rate > 50% automated
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- [ ] User satisfaction score > 4.5/5
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## Risk Mitigation
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### Technical Risks
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- **AI Model Performance**: Implement fallback mechanisms
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- **Processing Scalability**: Design for incremental processing
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- **Agent Stability**: Sandboxing and error recovery
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- **Data Quality**: Validation and quality gates
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### Timeline Risks
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- **AI Integration Complexity**: Start with simple agents first
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- **Content Processing Volume**: Implement queuing and batching
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- **User Experience Impact**: Feature flags for gradual rollout
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## Testing Strategy
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### AI Testing
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- [ ] Agent behavior validation
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- [ ] Content processing accuracy tests
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- [ ] Search result quality assessment
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- [ ] Performance benchmarking
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### Integration Testing
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- [ ] End-to-end AI workflows
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- [ ] Multi-agent coordination
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- [ ] Content pipeline reliability
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- [ ] Error handling and recovery
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### User Acceptance Testing
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- [ ] AI feature usability testing
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- [ ] Content processing validation
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- [ ] Performance and reliability assessment
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## Phase Gate Criteria
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Phase 3 is complete when:
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- [ ] All AI agents are functional and tested
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- [ ] Content processing pipeline handles all target formats
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- [ ] Advanced search features work reliably
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- [ ] Knowledge enhancement is automated
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- [ ] Performance meets requirements</content>
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<parameter name="filePath">docs/plans/project-phases/phase-3-advanced-features.md |