Overview
This video demonstrates how to build a complete full-stack AI application using Google’s Anti-gravity IDE and Stitch design tool. The tutorial shows how to create a personal AI search engine powered by PostgreSQL without writing any code, using autonomous AI agents to handle everything from frontend design to backend deployment.
Key Takeaways
- AI agents can now replace traditional development workflows - tools like Anti-gravity can autonomously edit files, run terminal commands, and manage entire application stacks without human coding intervention
- No-code full-stack development is production-ready - you can build complete applications with authentication, payments, databases, and deployment using visual tools and AI agents instead of manual programming
- Database-native search eliminates external dependencies - implementing BM25 ranking directly in PostgreSQL removes the need for ElasticSearch or other external search systems, simplifying architecture
- Visual design tools integrate seamlessly with code generation - connecting UI design agents like Stitch to development environments enables immediate translation from mockups to functional applications
- Implementation plans guide AI development consistency - creating detailed project roadmaps helps AI agents maintain focus and follow through on complex multi-component builds
Topics Covered
- 0:00 - Introduction to Anti-gravity and Stitch: Overview of Google’s free AI development tools and their capabilities for building full-stack applications
- 2:00 - Project Demo - AI Search Engine: Introduction to building a personal AI search engine powered by PostgreSQL with BM25 ranking
- 3:00 - Prerequisites and Setup: Required accounts and tools: Google, Stripe, Tiger Data, Vercel, and authentication setup
- 4:00 - Stitch UI Design Process: Using Stitch AI designer to create frontend components and connecting via MCP to Anti-gravity
- 7:00 - Anti-gravity Implementation Planning: Creating detailed project plans for AI agents and setting up the development environment
- 8:30 - Backend Setup with Tiger Data: Configuring PostgreSQL database with AI agent integration and MCP connectivity
- 11:00 - Payment Integration and Text Search: Setting up Stripe payments and implementing BM25 search extension in PostgreSQL
- 12:30 - Application Build and Testing: AI agent executes the implementation plan and builds the complete functional application
- 14:00 - Final Demo and Features: Showcasing the completed AI search engine with authentication, payments, and advanced search capabilities