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Learning Learning Paths

github-actions[bot] edited this page Jun 23, 2026 · 1 revision

Learning Paths

Use these paths to match the curriculum to the learner's role. The projects are modular, so teams can run a short workshop or a deeper onboarding sequence.

Path A: CAE engineer

Goal: use CaeReflex to inspect local artefacts and prepare evidence for review.

  1. CLI-first Inspection
  2. OpenFOAM Case Review
  3. VTK Result Context
  4. CrossRef Literature Context
  5. REST/OpenAPI Agent Workflow, optional

Path B: Python or platform developer

Goal: understand the software surfaces and how workflows move through CLI, services, adapters, exporters, and REST.

  1. CLI-first Inspection
  2. REST/OpenAPI Agent Workflow
  3. Adapter Extension Design
  4. Assessment Rubric, for review standards

Path C: AI-agent engineer

Goal: expose engineering evidence to an agent safely and avoid unsafe tool claims.

  1. CLI-first Inspection
  2. REST/OpenAPI Agent Workflow
  3. CrossRef Literature Context
  4. Glossary, especially agent context, provenance, extracted fact, and inferred fact

Path D: Instructor or technical lead

Goal: run the curriculum for a team or class.

  1. Instructor Guide
  2. Environment Setup
  3. CLI-first Inspection
  4. Pick two domain projects: Gmsh, OpenFOAM, VTK, or CrossRef
  5. Finish with Assessment Rubric

Path E: Advanced contributor

Goal: extend CaeReflex without breaking its architecture or safety boundary.

  1. Adapter Extension Design
  2. Architecture: Adapters
  3. Architecture: Services Layer
  4. Developer Guide: Adding Adapters
  5. Developer Guide: Testing

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