version: "1.0.1" name: layer-definitions description: Provide L1-L5 pedagogy layer reference for the AI-Native Robotics Textbook. Use when assigning layers to content, understanding layer requirements, or validating layer progression. allowed-tools: Read
Layer Definitions
Instructions
When determining pedagogical layers:
- Assess the content's AI involvement level
- Match to the appropriate layer (L1-L5)
- Ensure prerequisites from lower layers are met
- Validate layer progression is logical
Layer Overview
| Layer | Name | AI Involvement | Student Role | |
|---|
| L1 | Manual | None | Full manual work | |
| L2 | Collaboration | Assisted | AI helps after understanding | |
| L3 | Intelligence | Templated | Using AI templates/skills | |
| L4 | Spec-Driven | Guided | AI generates from specs | |
| L5 | Full Autonomy | Autonomous | AI-driven end-to-end | |
Layer Selection Guide
Choose L1 when:
- Teaching foundational concepts
- Student must understand without AI assistance
- Building mental models
Choose L2 when:
- Student understands the concept
- AI can provide extensions or variations
- Collaboration enhances learning
Choose L3 when:
- Teaching reusable patterns
- Introducing AI templates and skills
- Building on L1-L2 understanding
Choose L4 when:
- Working with specifications
- AI generates implementation from design
- Integration of multiple components
Choose L5 when:
- End-to-end autonomous workflows
- Student orchestrates AI agents
- Capstone projects
Reference
See layers.md for detailed layer descriptions.