# Fortune 500 Case Study Validation: Netflix
# Schema: ../../contracts/case-study-validation.schema.yaml

case_study: netflix
industry: Entertainment/Technology
fortune_rank: 115

jtbd: "When content taxonomy evolves, I need backward-compatible schema migrations across all services, so that existing content remains accessible while new features are supported."

scale_requirements:
  content_items: 100000000
  metadata_fields: 500
  services: 100
  latency_slo: "<30min for schema evolution"

required_commands:
  - command: "ggen ontology init"
    purpose: "Initialize content ontology structure"
    criticality: P2
    current_support: pending
    gaps: []

  - command: "ggen marketplace validate"
    purpose: "Validate schema evolution rules"
    criticality: P1
    current_support: pending
    gaps: []

  - command: "ggen template lint"
    purpose: "Lint templates for backward compatibility"
    criticality: P1
    current_support: pending
    gaps: []

  - command: "ggen template new"
    purpose: "Create new content type templates"
    criticality: P2
    current_support: pending
    gaps: []

validation_status: pending
validated_date: null
validator: claude-code

test_scenarios:
  - scenario: "Backward-compatible schema evolution"
    steps:
      - "ggen ontology init content-taxonomy-v2"
      - "ggen template lint --check-compatibility content-v1.tmpl content-v2.tmpl"
      - "ggen marketplace validate --package_id content-schema"
    expected: "Schema changes validated for backward compatibility"
    actual: pending

  - scenario: "Content type extension"
    steps:
      - "ggen template new --name interactive-content --base content.tmpl"
      - "ggen template lint --strict interactive-content.tmpl"
    expected: "New content type extends base without breaking changes"
    actual: pending

gaps: []

recommendations: []

notes: |
  Netflix case study focuses on schema evolution and backward compatibility.
  Key concerns: zero breaking changes, migration automation, rollback.
  Industry pattern: scale-driven with emphasis on data evolution.
