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Technical Design Workshop Minutes

Attendees

  • Engineering Manager
  • Backend Engineer
  • Frontend Engineer
  • Data Scientist
  • Product Manager

Key Decisions

Clustering Approach

  • Primary Algorithm: Custom Go implementation
  • K-means variant
  • Geospatial clustering
  • Rationale:
  • Full control over algorithm
  • Predictable performance
  • Avoid dependency on external ML libraries
  • Performance Target: Process 200 entries in < 5 seconds

Technology Stack

  • Backend: Go (Gin/Echo framework)
  • Database: PostgreSQL with PostGIS
  • Frontend: React with TypeScript
  • Clustering: Custom implementation
  • Leverage Go's performance
  • Avoid dependency on rapidly changing ML libraries

Prototype Development Phases

Week 1 Deliverables

  1. CSV Parsing Module in Go
  2. Robust input validation
  3. Efficient memory management

  4. High-performance parsing

  5. Initial Clustering Algorithm

  6. Implement custom clustering logic
  7. Optimize for geospatial calculations
  8. Benchmark-driven development

Week 2 Deliverables

  1. Route Suggestion Logic
  2. Develop Go-based routing algorithm
  3. Implement efficient data structures

  4. Create performance-critical clustering method

  5. Frontend Integration

  6. Develop route visualization
  7. Create interactive route adjustment interface

Action Items

Immediate Tasks

  • Set up development environment
  • Create project repository
  • Define detailed technical specifications

Backend Engineer

  • Implement CSV parsing module in Go
  • Design validation layer
  • Set up performance testing framework

Data Scientist

  • Research clustering algorithm parameters
  • Develop initial clustering prototype
  • Create sample datasets for testing

Frontend Engineer

  • Design route visualization interface
  • Implement basic upload and display components
  • Ensure responsive design

Product Manager

  • Coordinate with online florist partner
  • Prepare user acceptance testing plan
  • Document feature requirements
  • github.com/gin-gonic/gin (Web framework)
  • github.com/lib/pq (PostgreSQL driver)
  • github.com/paulmach/orb (Geospatial operations)
  • gonum.org/v1/gonum (Scientific computing)

Performance Considerations

  • Leverage Go's concurrent processing
  • Use goroutines for parallel clustering
  • Implement efficient memory pooling
  • Zero-copy parsing techniques

Risk Mitigation Strategies

  1. Implement modular architecture
  2. Create comprehensive test suite
  3. Plan for iterative algorithm improvement

Next Steps

  • Schedule weekly progress review
  • Set up continuous integration
  • Prepare initial prototype demonstration

Success Metrics

  • Process 200 entries in < 5 seconds
  • Demonstrate basic route clustering
  • Achieve 75% route optimization accuracy

Estimated Timeline

  • Prototype Development: 2 weeks
  • Initial Testing: 1 week
  • Refinement: Ongoing

Appendix

  • Detailed technical specifications
  • Performance benchmarking methodology
  • Initial clustering algorithm research