THE BOOK
AI for Embedded Engineers and Makers
The complete authored chapters, practical labs and supporting references.
- 1. AI at the Embedded Workbench
- 2. How LLMs Work: The Useful Mental Model
- 3. Give AI an Engineering Brief
- 4. Set Up Your AI Workbench
- 5. Git Without the Mystery
- 6. Put Your Project on GitHub
- 7. Experiment, Review, and Recover
- 8. Markdown as an Engineering Notebook
- 9. Build a Useful Project Knowledge Base
- 10. Write AGENTS.md for an Embedded Project
- 11. Turn a Repeated Procedure into a Skill
- Read Datasheets and Plan Interfaces with AI
- Build Firmware in Small, Verifiable Steps
- Debug with Evidence
- Test, Review, and Measure
- 16. Build Your Reusable Engineering Toolkit
- 17. Capstone: Ship a Documented Sensor Monitor
- 18. Maintain the Workflow and Choose What Comes Next
Appendices, glossary and front matter
- Reading map
- Before you begin
- Rights and attribution
- AI for Embedded Engineers and Makers
- A. Terminal and operating-system notes
- B. Git task and recovery reference
- C. Markdown and YAML reference
- D. Reusable task-brief patterns
- E. Project records that survive the conversation
- F. Project instructions and focused skills
- G. Versions and checkpoint map
- Glossary
- H. Troubleshooting by evidence boundary
- I. Sources, rights, and corrections