Aug 22 • General discussion
My workflow
From Sketch to Production
## Overview
This workflow represents a fully integrated AI development pipeline that handles everything from initial concepts to deployed applications using orchestrated AI tools and MCPs (Model Context Protocol servers).
## The Stack
### **Core AI Tools**
- **Claude Desktop** - Ideation, design planning, and implementation specification
- **Claude Code CLI** - Autonomous development with design review integration
- **Warp AI** - Terminal automation, quick coding, and macOS integration
### **Design Pipeline**
- **Sketch/Wireframe** → **Claude Desktop** → **Figma Make** → **Production Design**
- **Figma MCP** - Design inspection and code generation guidance
### **Development MCPs**
- **Context7** - Real-time library documentation and current best practices
- **Playwright** - Live UI testing, screenshots, and interaction validation
- **Design Review Agent** - Professional-grade UI/UX evaluation
### **Data Integration**
- **FileMaker MCP** - Campaign and client data
- **PostgreSQL/Supabase MCPs** - Project-specific database selection
- **Vector Supabase MCP** - Shared project memory across all AI tools
## The Workflow
### **1. Ideation to Design**
```
Rough Sketch → Claude Desktop Refinement → Figma Make → Clean Design
```
Claude Desktop bridges concepts and execution, translating ideas into actionable design specifications.
### **2. Design to Code**
```
Figma Design → Claude Desktop Prompt Generation → Claude Code CLI Implementation
```
Highly effective prompt translation eliminates design-code disconnect.
### **3. Development Execution**
- **Context7** ensures current library usage
- **Database MCPs** provide real data integration
- **Playwright** validates UI with live testing
- **Vector memory** maintains context across tools
### **4. Quality Assurance**
- **Design Review Agent** provides systematic UI/UX validation
- **Style guide compliance** ensures consistency
- **Multi-viewport testing** guarantees responsiveness
## Key Advantages
**🚀 Speed**: Rough concept to deployed feature in significantly reduced time
**🎯 Quality**: Professional-grade validation and current best practices
**🔄 Context**: Shared memory across all tools maintains project continuity
**📊 Real Data**: Testing with actual data scenarios, not mocks
**⚡ Automation**: Terminal tasks and quick coding handled by AI
## Impact
This ecosystem transforms development from manual coordination of separate tools into a seamless AI-orchestrated pipeline where each component enhances the others, resulting in faster delivery without sacrificing quality or design standards.
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My workflow
skool.com/claude-9099
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