A month-long sprint building 19 AI-powered applications in 21 weekdays, demonstrating rapid prototyping skills and AI integration expertise across diverse use cases.
Successfully shipped 19 distinct AI applications with consistent architecture, comprehensive testing, and full documentation, establishing a repeatable workflow for rapid AI prototype development.
Role: Solo Full-stack Developer & AI Engineer
Timeframe: August 2025 (21 weekdays)
Needed to rapidly advance AI development skills while building a portfolio of diverse, production-ready AI applications. Required a systematic approach to learning multiple AI APIs, frameworks, and deployment patterns while maintaining code quality and documentation standards.
Established standardised starter templates (Next.js + TypeScript + Mantine for web, Flask for Python APIs) to eliminate repetitive setup. Each day followed a consistent workflow: scope MVP features, implement core functionality with AI integration, write tests, deploy to production, and document learnings. Created a central hub repository to organize all projects with calendar-based navigation.
Successfully delivered 19 distinct AI applications covering diverse use cases including natural language processing, image generation, data analysis, and chatbot interfaces. Maintained consistent quality standards with testing for all projects and comprehensive documentation. Developed reusable patterns for API integration, error handling, and deployment that accelerated development speed throughout the challenge.
Central hub repository containing project calendar and overview, linking to individual day repositories. Each application uses Next.js 15 App Router with API routes for backend logic, or Flask for Python-specific AI tasks. Database integration via Neon Postgres with Drizzle ORM for data persistence. Third-party AI APIs integrated through secure server-side routes. Automated testing with Jest and React Testing Library for frontend, Pytest for Python services. Deployments automated through Netlify (frontend) and Render (Python APIs).
Integrated OpenAI GPT models for conversational interfaces, text generation, and semantic analysis. Leveraged AI assistance in Cursor for rapid code generation, debugging, and test writing throughout the challenge.
Create comprehensive recap post with consolidated metrics and key learnings. Add interactive demos with embedded screenshots and GIFs. Expand most promising applications with additional features and monetization strategies. Extract common patterns into open-source starter template for AI application development.