7.1 KiB
7.1 KiB
Checkpoint 4: Team Structure Report
Team Structure for Iterative Media Processing Development
1. Phase-Based Team Evolution
Phase 1 (Weeks 1-2): Minimal Team
Just 2 people:
├── Backend Python Developer (You or Lead)
│ └── Build v1 basic transcription
└── DevOps/Infrastructure Support (Part-time)
└── PostgreSQL, uv setup, testing
Phase 2 (Week 3): Add Enhancement
+1 person:
└── AI Integration Developer
└── DeepSeek enhancement integration
Phase 3 (Weeks 4-5): Add Multi-pass
+1 person:
└── ML Engineer/Researcher
└── Multi-pass strategies, confidence scoring
Phase 4 (Week 6+): Add Diarization
+1 person:
└── Audio/Speech Specialist
└── Speaker diarization, voice embeddings
2. Core Roles Detailed
Backend Python Developer (Lead)
- When: From Day 1
- Focus: Architecture, protocols, iteration management
- Responsibilities:
- Design protocol-based architecture
- Build v1 basic pipeline
- Manage version transitions
- Ensure backward compatibility
- Code review all iterations
- Implement batch processing system
- Skills: Deep Python, PostgreSQL, clean architecture, Whisper/ML experience
AI Integration Developer
- When: Phase 2 (Week 3)
- Focus: AI enhancement layer
- Responsibilities:
- Integrate DeepSeek/other AI services
- Design enhancement prompts
- Handle structured outputs
- Manage AI costs/quotas
- Implement retry logic
- Skills: API integration, prompt engineering, JSON schemas
ML Engineer/Researcher
- When: Phase 3 (Week 4)
- Focus: Accuracy improvements
- Responsibilities:
- Design multi-pass strategies
- Implement confidence scoring
- Research optimal parameters
- Benchmark accuracy improvements
- Optimize model performance
- Skills: Whisper models, statistics, Python, ML optimization
Audio/Speech Specialist
- When: Phase 4 (Week 6)
- Focus: Speaker separation
- Responsibilities:
- Implement diarization algorithms
- Voice embedding systems
- Speaker clustering
- Audio preprocessing for diarization
- Skills: pyannote, speech processing, audio analysis
3. Support Roles (As Needed)
DevOps/Infrastructure (Part-time from Day 1)
- PostgreSQL optimization
- CI/CD pipeline setup
- Monitoring and logging
- Backup strategies
- Performance monitoring
QA/Test Engineer (Part-time from Phase 2)
- Test data preparation
- Accuracy benchmarking
- Regression testing
- Performance testing
- Real file test management
Technical Writer (Part-time from Phase 3)
- API documentation
- Rule files maintenance
- User guides
- Architecture documentation
- Change logs
4. Communication Structure for Iterations
Phase 1: Direct communication (2 people)
Phase 2: Daily standup starts (3 people)
Phase 3: Weekly architecture review (4 people)
Phase 4: Formal sprint planning (5+ people)
Decision Making by Phase
| Phase | Decision Owner | Review Required | Communication |
|---|---|---|---|
| 1 | Backend Lead | You | Direct |
| 2 | Backend Lead | You + AI Dev | Daily sync |
| 3 | Backend Lead | Team consensus | Weekly review |
| 4 | You | Architecture team | Sprint planning |
5. Work Distribution Strategy
Phase 1 Sprint (Weeks 1-2)
Backend Lead:
- Database schema design
- Basic Whisper integration
- Batch processing system
- JSON/TXT export
- CLI implementation
DevOps:
- PostgreSQL setup
- Test environment
- CI/CD basics
Phase 2 Sprint (Week 3)
Backend Lead:
- Version management system
- Pipeline orchestrator
- Backward compatibility
AI Developer:
- DeepSeek integration
- Enhancement templates
- Error handling
- Prompt optimization
Phase 3 Sprint (Weeks 4-5)
Backend Lead:
- Refactoring for multi-pass
- Version compatibility
- Performance optimization
AI Developer:
- Enhance prompt optimization
- Cost management
ML Engineer:
- Multi-pass implementation
- Confidence algorithms
- Segment merging
- Parameter tuning
Phase 4 Sprint (Week 6+)
All roles contributing:
- Backend: Integration
- AI: Speaker prompts
- ML: Voice embeddings
- Audio: Diarization
6. Skill Requirements by Phase
Phase 1 (Must Have)
- Python 3.11+
- PostgreSQL + SQLAlchemy
- Basic Whisper knowledge
- pytest + real file testing
- Async Python
Phase 2 (Add)
- API integration
- Prompt engineering
- Async error handling
- JSON schema validation
Phase 3 (Add)
- ML/statistics
- Model optimization
- Performance profiling
- Confidence scoring
Phase 4 (Add)
- Speech processing
- Audio analysis
- Clustering algorithms
- Voice biometrics
7. Team Scaling Triggers
When to Add Next Person
- Phase 1 → 2: When v1 is stable and tested
- Phase 2 → 3: When enhancement is working reliably
- Phase 3 → 4: When multi-pass shows value
- Scale beyond: When batch processing needs optimization
Scaling Indicators
- Processing backlog > 100 files
- Response time > SLA
- Feature requests accumulating
- Technical debt growing
8. Risk Mitigation
Single Points of Failure
- Backend Lead in Phase 1-2: Document everything, pair programming
- AI API keys: Multiple service support, fallback options
- PostgreSQL: Regular backups, replication setup
- Domain knowledge: Cross-training between phases
Knowledge Transfer
- Pair programming during transitions
- Comprehensive documentation
- Code reviews for learning
- Recorded architecture decisions
- Weekly knowledge sharing sessions
9. Remote vs Co-located Considerations
Remote Team Benefits
- Access to global talent
- Async work enables 24/7 progress
- Lower costs
- Written communication creates documentation
Remote Team Challenges
- Communication delays
- Time zone coordination
- Pair programming harder
- Onboarding complexity
Recommended Approach
- Core team co-located or same timezone
- Support roles can be remote
- Clear async communication protocols
- Regular video architecture reviews
10. Performance Metrics by Role
Backend Developer
- Code coverage > 80%
- PR review time < 24h
- Bug rate < 5%
- Documentation completeness
AI Integration Developer
- API error rate < 1%
- Enhancement accuracy > 99%
- Cost per transcript < $0.01
- Prompt iteration speed
ML Engineer
- Model accuracy improvements
- Processing time reduction
- Confidence score reliability
- Research output quality
Audio Specialist
- Speaker identification accuracy > 90%
- Diarization error rate < 10%
- Processing speed targets
- Voice quality metrics
Summary
The team structure emphasizes:
- Gradual growth aligned with iterative development
- Clear role boundaries with defined responsibilities
- Phase-based scaling to avoid premature complexity
- Knowledge transfer built into the process
- Metrics-driven performance evaluation
This approach ensures the team grows with the product, maintaining efficiency while adding capabilities.
Generated: 2024
Status: COMPLETE
Next: Technical Migration Report