How the AI Builder Works Inside

System Overview

Spawned's AI builder uses a multi-model architecture to generate, refine, and deploy full-stack applications from natural language descriptions.

Core Components

1. Prompt Processor

Analyzes user input to understand:

• App type (SaaS, marketplace, etc.)
• Required features
• Design preferences
• Technical requirements

2. Code Generator

Multiple specialized models:

• UI Model: React/Next.js components
• Logic Model: Business logic and APIs
• Data Model: Database schemas
• Style Model: Tailwind CSS styling

3. Build Pipeline

• TypeScript compilation
• Dependency resolution
• Environment setup
• Preview deployment

Generation Flow

User Prompt
    ↓
Prompt Analysis → Feature Extraction
    ↓
Architecture Planning → Component Tree
    ↓
Parallel Code Generation
├── Pages & Routes
├── Components
├── API Endpoints
├── Database Schema
└── Styles
    ↓
Assembly & Compilation
    ↓
Preview Deployment

Tech Stack Generated

Every Spawned app includes:

• Frontend: Next.js 14 with App Router
• Styling: Tailwind CSS
• Database: Supabase (Postgres)
• Auth: Supabase Auth or custom
• Deployment: Vercel-ready

Iteration Model

The AI maintains context across conversations:

• Remembers previous requests
• Understands existing code structure
• Makes targeted changes vs full rewrites
• Learns from user feedback

Code Quality

Generated code follows:

• TypeScript strict mode
• ESLint best practices
• Accessibility standards
• Performance optimization
• Security patterns

Integration Points

Supabase

• Auto-generates schemas
• Creates RLS policies
• Handles migrations

Stripe

• Payment intent setup
• Webhook handling
• Subscription management

Solana

• Wallet connection
• Token interactions
• Transaction signing

Limitations

Current limitations:

• Complex animations require manual tweaking
• Highly custom backends may need expert review
• Very large apps benefit from modular prompts

Prompt Engineering Tips

For best results:

1. Be specific about features
2. Mention design preferences
3. Specify user flows
4. Include edge cases
5. Iterate in small chunks