Layer Definitions for AI-Native Robotics
Reference guide for the 5 pedagogical layers (L1-L5) of AI involvement. Used for assigning content layers, understanding requirements, and validating learning progression.
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.
Related skills
Educational Assessment Builder
Create varied assessments aligned to your learning objectives.
Online Course Module Builder
Structure and create engaging online course modules.
Lesson Plan & Curriculum Designer
Design structured lesson plans and educational curricula.