How I launched Learnrithm AI in 29 days and landed first customer

# The Challenge

Peter Okafor approached me with an ambitious vision: create an AI-powered learning platform that could generate personalized quizzes and courses. The catch? He needed it launched in 30 days to meet an investor deadline.

## Week 1: Foundation & Architecture

**Days 1-3: Technical Planning**
- Chose Next.js 14 with App Router for performance
- Supabase for database and auth
- AI SDK with OpenAI for content generation
- Stripe for payments

**Days 4-7: Core Infrastructure**
- User authentication system
- Database schema design
- AI prompt engineering for quiz generation
- Basic UI components with shadcn/ui

## Week 2: AI Integration & Core Features

**Days 8-14: The AI Engine**
The most critical part was building the AI content generation system:

```typescript
// AI Quiz Generator
const generateQuiz = async (topic: string, difficulty: string) => {
const { text } = await generateText({
model: openai('gpt-4'),
prompt: `Create a ${difficulty} quiz about ${topic}...`,
})
return parseQuizData(text)
}
```

**Key Technical Decisions:**
- Streaming AI responses for better UX
- Caching generated content to reduce API costs
- Progressive enhancement for offline capability

## Week 3: User Experience & Testing

**Days 15-21: Polish & Performance**
- Implemented real-time progress tracking
- Added collaborative learning features
- Performance optimization (achieved 95+ Lighthouse score)
- Beta testing with 50 early users

## Week 4: Launch & Iteration

**Days 22-29: Go-to-Market**
- Deployed to Vercel with custom domain
- Integrated analytics and user feedback
- Payment processing with Stripe
- First paying customer on day 27!

## Results & Impact

**Metrics after 30 days:**
- 500+ registered users
- 85% user retention rate
- $5M seed valuation raised
- Featured on Product Hunt

**Technical Achievements:**
- 99.9% uptime
- Sub-200ms API response times
- Scalable architecture handling 10k+ concurrent users

## Lessons Learned

1. **AI Integration Strategy**: Start with simple prompts, iterate based on user feedback
2. **Performance Matters**: Users expect instant responses, especially with AI features
3. **MVP Focus**: We shipped with 3 core features, added 15+ more post-launch

## The Equity Partnership

Peter chose the $2k + 4% equity option. As current CTO, I continue to:
- Lead technical development
- Scale the platform architecture
- Mentor the growing engineering team

**Want to build your own AI-powered MVP?** The same 30-day process that worked for Learnrithm can work for your idea.