ML Pipeline Orchestrator

Overview

This skill transforms ML development into a SpecWeave increment-based workflow, ensuring every ML project follows the same disciplined approach: spec → plan → tasks → implement → validate. It orchestrates the complete ML lifecycle from data exploration to model deployment, with full traceability and living documentation.

Core Philosophy

SpecWeave + ML = Disciplined Data Science

Traditional ML development often lacks structure:

• ❌ Jupyter notebooks with no version control
• ❌ Experiments without documentation
• ❌ Models deployed with no reproducibility
• ❌ Team knowledge trapped in individual notebooks

SpecWeave brings discipline:

• ✅ Every ML feature is an increment (with spec, plan, tasks)
• ✅ Experiments tracked and documented automatically