The software industry has disrupted itself. Spec-Driven Development with Reusable Intelligence (SDD-RI) transforms what traditionally takes months into days—not through faster coding, but through compounding intelligence.
This hackathon isn't just about winning 300 points. It's about launching a platform.
| Traditional Timeline | Our Timeline |
|---|---|
| Book content: 6-18 months | 48 hours |
| Author platform: 3-6 months | Week 1-2 |
| Multi-book infrastructure: 6-12 months | Month 1 |
| Institutional features: 12+ months | Month 2 |
Why? Because every hour invested in reusable intelligence compounds. The lesson-writer agent that creates Module 1 creates Module 4 at the same speed. The skills that power RoboLearn power the next ten books.
┌─────────────────────────────────────────────────────────────┐
│ RoboLearn Platform │
├───────────────────┬───────────────────┬─────────────────────┤
│ STUDENTS │ AUTHORS │ INSTITUTIONS │
│ │ │ │
│ Personalized │ AI-assisted │ White-label │
│ Hardware-aware │ Days not months │ Analytics │
│ Multilingual │ Revenue share │ Curriculum control │
│ Interactive │ Agent workforce │ Bulk licensing │
└───────────────────┴───────────────────┴─────────────────────┘
| Requirement | Points | Deliverable |
|---|---|---|
| Book + RAG Chatbot | 100 | 4 modules, context-aware chat |
| Reusable Intelligence | 50 | Skills, agents, knowledge, MCP configs |
| Auth + Onboarding | 50 | Better-Auth, hardware survey, profile-based filtering |
| Personalization | 50 | AI rewrites content for user context |
| Urdu Translation | 50 | Toggle between English/Urdu |
| Total | 300 |
Signup → Hardware Survey → Personalized Content
↓
┌────────┬────────┬────────────┐
│ Learn │Visualize│Personalize │ ← 3-Tab UI
│ (MDX) │(Diagram)│ (AI) │
└────────┴────────┴────────────┘
↓
┌─────────────────────────────┐
│ Interactive Python Lab │
│ Pyodide + MockROS + Robot │
└─────────────────────────────┘
↓
┌─────────────────────────────┐
│ RAG Chat Sidebar │
│ Context-aware • Select-ask │
└─────────────────────────────┘
↓
🔄 EN ↔ UR
| Layer | Choice | Why |
|---|---|---|
| Frontend | Docusaurus | MDX-native, fast builds |
| Hosting | GitHub Pages → Cloudflare | Free, global CDN |
| Backend | FastAPI + Cloud Run | Serverless, scales to zero |
| Database | Neon Postgres | Profiles, hardware configs |
| Vector DB | Qdrant Cloud | RAG embeddings |
| Auth | Better-Auth | Modern, official MCP server |
| AI | OpenAI Agents SDK | Chat, personalization |
.claude/
├── skills/ # HOW (reusable patterns)
│ ├── authoring/ # Content creation skills
│ │ ├── lesson-generator/ # Generate lessons (4-layer framework)
│ │ ├── assessment-builder/ # Create quizzes and assessments
│ │ ├── learning-objectives/ # Design learning objectives
│ │ ├── mermaid-diagram/ # Generate educational diagrams
│ │ ├── urdu-translator/ # Translate content to Urdu
│ │ ├── quiz-generator/ # Generate quiz questions
│ │ ├── summary-generator/ # Create lesson summaries
│ │ ├── notebooklm-slides/ # Generate slide decks
│ │ └── concept-scaffolding/ # Scaffold complex concepts
│ │ └── visual-asset-workflow/ # Create educational visuals
│ └── engineering/ # Platform development skills
│ ├── pyodide-exercise/ # Browser-based Python exercises
│ ├── docusaurus-deployer/ # Deploy to GitHub Pages
│ ├── frontend-design/ # UI component design
│ ├── image-generator/ # Generate images with Gemini
│ ├── mcp-builder/ # Create MCP servers
│ ├── skill-creator/ # Create new skills
│ ├── chatkit-integration/ # ChatKit framework integration patterns
│ └── session-intelligence-harvester/ # Capture learnings
│
├── agents/ # WHO (autonomous workers)
│ ├── super-orchestra.md # General workflow orchestration
│ ├── authoring/ # Content creation agents
│ │ ├── content-implementer.md # Implement lessons from specs
│ │ ├── chapter-planner.md # Plan chapter structure
│ │ ├── educational-validator.md # Validate constitutional compliance
│ │ └── validation-auditor.md # Quality validation before publish
│ └── engineering/ # Platform development agents
│ ├── spec-architect.md # Design specifications
│ └── chatkit-integration-agent.md # ChatKit integration workflow
│
├── commands/ # Slash commands (/sp.*)
└── .mcp.json # MCP server configuration
# Domain knowledge lives in authoritative sources:
# - requirement.md (course structure, hardware specs)
# - .specify/memory/constitution.md (principles, tiers)
# - README.md (platform vision)
| Server | Use | Rationale |
|---|---|---|
| Better-Auth MCP | Auth implementation | Active introspection — generates schemas, supersedes docs |
| Context7 | Library docs | Generalist for React, FastAPI, Pyodide |
| Tavily | Research | Synthesized answers for content generation |
| DeepWiki | Repo understanding | Understand panaversity base template |
| Task | Deliverable | Status |
|---|---|---|
| 1.1 | Fork repo, rename to robolearn, verify build |
✅ |
| 1.2 | Create folder structure (skills, agents, knowledge, mcp) | ✅ |
| 1.3 | Write knowledge files (vocabulary, hardware-tiers, course-structure) | ✅ |
| 1.4 | Write skill files (lesson-generator, hardware-filter, urdu-translator) | ✅ |
| 1.5 | Write agent files (lesson-writer, rag-builder) | ✅ |
| 1.6 | Configure MCP servers | ✅ |
| 1.7 | Content cleanup, rebrand, navigation | ✅ |
| 1.8 | Component stubs, first deploy | ✅ |
| 1.9 | Homepage redesign (Industrial Confidence design system) | ✅ |
Exit: ✅ Live at username.github.io/robolearn with intelligence infrastructure + redesigned homepage
| Task | Deliverable | Status |
|---|---|---|
| 2.1 | Module 1: ROS 2 Foundations (7 chapters, 25 lessons) | ✅ |
| 2.2 | Module 2: Gazebo/Unity Simulation (6 chapters, 22 lessons) | ✅ |
| 2.3 | Module READMEs and chapter structure | ✅ |
| 2.4 | 8 authoring skills created | ✅ |
Exit: ✅ 47 lessons across 2 modules with complete skill infrastructure
Extensions (moved to Phase 5):
- Create Mermaid/React Flow diagrams
- Add hardware-filtered sections
| Task | Deliverable |
|---|---|
| 3.1 | Better-Auth setup (use official MCP) |
| 3.2 | Neon Postgres schema |
| 3.3 | Survey component |
Exit: Users can signup, complete survey, see filtered content
| Task | Deliverable | Status |
|---|---|---|
| 4.1 | FastAPI app structure | ✅ |
| 4.2 | Qdrant collection setup | ✅ |
| 4.3 | Embedding pipeline (content → vectors) | ✅ |
| 4.4 | OpenAI Agents SDK config | ✅ |
| 4.5 | Deploy to Cloud Run | ✅ |
Exit: ✅ RAG chatbot answering questions with book context + visual enhancements
Extensions Completed:
- ChatKit server integration with PostgreSQL persistence
- Context injection (user profile, page context, conversation history)
- Streaming responses for real-time UX
- Complete specifications reverse-engineered (
specs/007-chatkit-server/)
| Task | Deliverable | Status |
|---|---|---|
| 5.1 | ChatKit widget component | ✅ |
| 5.2 | Current page context injection | ✅ |
| 5.3 | Select-to-ask functionality | ✅ |
| 5.4 | Hardware-aware responses | ✅ |
| 5.5 | User authentication integration | ✅ |
| 5.6 | Personalization menu | ✅ |
| 5.7 | Script loading detection | ✅ |
Exit: ✅ Functional ChatKit widget with context awareness, text selection "Ask", and user personalization
Extensions Completed:
- ChatKit React component integration
- Custom fetch interceptor for auth and metadata
- Page context extraction (URL, title, headings, meta tags)
- User profile context transmission
- Complete specifications reverse-engineered (
specs/008-chatkit-ui-widget/) - Reusable intelligence harvested (skill + agent)
| Task | Deliverable | Status |
|---|---|---|
| 6.1 | Urdu translation or Multi Language | ✅ |
| 6.2 | LanguageToggle component | ✅ |
Exit: ✅ Full 300-point feature set
Completed Features:
- LanguageToggle component with locale switching (
/en/and/ur/routes) - Docusaurus i18n plugin for auto-translation (Gemini API)
- RTL (Right-to-Left) CSS support for Urdu content
- Language preference persistence (localStorage)
- Complete specification (
specs/006-i18n-auto-translate-gemini/)
| Task | Deliverable | Status |
|---|---|---|
| 7.1 | End-to-end testing | ✅ |
| 7.2 | 90-second demo video | 🟡 Pending |
| 7.3 | README with setup instructions | ✅ |
| 7.4 | Submit | 🟡 Pending |
Exit: ✅ Hackathon submission ready (demo video pending)
Completed:
- End-to-end testing completed for ChatKit integration
- Comprehensive README with setup instructions
- Complete documentation (specs, ADRs, PHRs)
- Reusable intelligence infrastructure
| Task | Deliverable |
|---|---|
| 6.1 | PythonRunner component (Pyodide) |
| 6.2 | MockROSBridge class |
| 6.3 | RobotViewer component |
| 6.4 | Wire up: code → mock ROS → robot responds |
| 6.5 | Personalization endpoint |
| 6.6 | Personalize tab in content |
Exit: Students write ROS-like code, see robot react
| Feature | Description |
|---|---|
| Author Dashboard | Book management, chapter organization |
| Agent Studio | Configure lesson-writer, review AI drafts |
| Analytics | Reader engagement, chat queries, hardware distribution |
| Feature | Description |
|---|---|
| Book isolation | Separate knowledge folders per book |
| Shared infrastructure | Common auth, RAG, components |
| Second book | "CoLearning Python: The AI-Driven Way" |
| Feature | Description |
|---|---|
| White-label | Custom branding per institution |
| Bulk licensing | Student seat management |
| LMS integration | Grade passback, SSO |
| Feature | Description |
|---|---|
| Mobile app | React Native |
| Offline mode | Downloaded content |
| Real ROS 2 | Beyond MockROS for advanced users |
| Marketplace | Third-party authors |
| Tier | Price | Features |
|---|---|---|
| Free | $0 | Read content, basic exercises |
| Professional | $49/month | RAG chat, personalization, multilingual, certificates |
| Annual | $399/year | Professional features + 30% savings |
| Tier | Price | Features |
|---|---|---|
| Team | $199/month | 10 seats, progress tracking, admin dashboard |
| Department | $799/month | 50 seats, custom learning paths, analytics |
| Enterprise | Custom | Unlimited seats, SSO, dedicated support, SLA |
| Tier | Price | Features |
|---|---|---|
| Academic | $2,500/year | 200 students, LMS integration, grade passback |
| Campus | $10,000/year | 1,000 students, white-label option, curriculum control |
| Enterprise | $50,000+/year | Unlimited, custom development, dedicated success manager |
| Model | Split |
|---|---|
| Free Books | 0% platform fee |
| Paid Books | 70% author / 30% platform |
| Enterprise Licensing | 60% author / 40% platform (includes support overhead) |
Why this is hard to copy:
| Layer | Moat |
|---|---|
| Skills | Compound with every book authored |
| Knowledge | Domain expertise encoded |
| Agents | Workflows refined through use |
| Network | Zia Khan's 50K+ student distribution |
| Data | Chat queries reveal what students struggle with |
Every book makes the platform smarter. Every student interaction improves the RAG. The intelligence compounds.
| Risk | Mitigation |
|---|---|
| Deadline pressure | Phases ordered by point value, cut from bottom |
| RAG quality | Start basic, iterate |
| Live demo fails | Pre-recorded backup video |
| Content thin | 3 polished lessons > 10 rough ones |
| MockROS feels fake | Frame as "pedagogical simulation" — judges evaluate concept |
| Phase | Metric | Target |
|---|---|---|
| Hackathon | Score | 300 points |
| Week 1 | Author dashboard | MVP live |
| Month 1 | Books | 2 live |
| Month 1 | Students | 500 active |
| Month 3 | MRR | $2,000 |
| Month 6 | Students | 10,000 |
We don't just submit a hackathon project. We launch a platform.
The same intelligence that builds RoboLearn builds the next ten books. The same agents that write Physical AI lessons write Python lessons. The same infrastructure that serves 100 students serves 100,000.
This is what AI-driven development with Spec-Driven methodology and Reusable Intelligence makes possible.