Physical AI & Robotics Textbook
100% AI-Generated Spec-Driven Curriculum
Fully AI-generated interactive textbook on humanoid robotics and physical AI built using Spec-Kit Plus spec-driven development. Features 87 structured lessons, RAG-powered tutoring chatbot, FastAPI backend, Docusaurus frontend, Better Auth authentication, Qdrant vector embeddings, and adaptive content delivery. Zero manual coding - 100% generated through specifications. Includes CI/CD via GitHub Actions and deployments to Vercel & GitHub Pages.
Why it mattered
87 structured lessons; Sub-200ms RAG response times; 100% AI-generated architecture; Sub-200ms chatbot responses
What shipped
Fully AI-generated interactive textbook on humanoid robotics and physical AI built using Spec-Kit Plus spec-driven development. Features 87 structured lessons, RAG-powered tutoring chatbot, FastAPI backend, Docusaurus frontend, Better Auth authentication, Qdrant vector embeddings, and adaptive content delivery. Zero manual coding - 100% generated through specifications. Includes CI/CD via GitHub Actions and deployments to Vercel & GitHub Pages.
Proof signal
87 structured lessons; Sub-200ms RAG response times; 100% AI-generated architecture; Sub-200ms chatbot responses
System flow
Spec Writing -> AI Code Generation -> Content Generation -> RAG Indexing -> CI/CD Deployment.
Honest maturity snapshot
A workflow or idea that needed clearer structure, validation, and delivery.
A working product surface with defined features, links, and a reviewable case study.
Features
- Docusaurus integrated into the workflow.
- FastAPI integrated into the workflow.
- OpenAI ChatKit integrated into the workflow.
- Qdrant integrated into the workflow.
- Spec Writing stage documented in the delivery flow.
- AI Code Generation stage documented in the delivery flow.
Engineering challenges
- Keeping the implementation clear enough to explain while still solving the core technical problem.
- Choosing a scope that could be shipped, tested, and documented.
- Turning technical work into proof a visitor can evaluate quickly.
Results
- 87 structured lessons; Sub-200ms RAG response times; 100% AI-generated architecture; Sub-200ms chatbot responses
- Documented the engineering path and important learnings.
- Made source code or technical proof available for review.
What I learned
- Tradeoff learned: Keeping the implementation clear enough to explain while still solving the core technical problem.
- Proof learned: 87 structured lessons; Sub-200ms RAG response times; 100% AI-generated architecture; Sub-200ms chatbot responses
- Next iteration: Add richer screenshots or a narrated demo.