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đź“ą Watch the Complete Video Tutorial
đź“ş Title: How to Use Figma AI To Make Sites 10X More Beautiful
⏱️ Duration: 595
👤 Channel: AI LABS
🎯 Topic: Use Figma Make
đź’ˇ This comprehensive article is based on the tutorial above. Watch the video for visual demonstrations and detailed explanations.
Figma has long been a cornerstone tool for designers and developers alike—but many professionals are missing out on its powerful new AI capabilities. While Figma isn’t going anywhere and won’t be replaced by AI anytime soon, failing to leverage its AI features—especially Figma Make—puts you at a serious productivity disadvantage.
In this comprehensive guide, we’ll walk you through a battle-tested, step-by-step workflow that transforms vague ideas into fully functional, responsive, and production-ready prototypes using Figma Make and complementary AI tools. You’ll learn how to avoid common pitfalls, structure your prompts effectively, integrate design systems, and even connect your AI-generated frontend to a real backend using modern development stacks.
Every insight, tip, tool recommendation, and real-world example from the original transcript is included below—no detail left behind.
Why Most People Fail with Figma Make (And How to Avoid It)
Many users try Figma Make by dumping everything they can think of into a single, unstructured prompt—colors, pages, features, user flows—all at once. The result? A disorganized, non-functional prototype that lacks proper structure and code organization.
The core issue: Figma Make generates working code, and code requires logical architecture. Without clear planning, the AI agent becomes as confused as you are. The key to success isn’t just using AI—it’s using it intentionally and systematically.
Key Insight: “If you’re confused, your AI agent will be confused, too.”
The Power of Figma Make: AI That Generates Real Code
Figma Make is a groundbreaking AI feature that lets you prompt designs into existence with working React code. Unlike generic image generators, Figma Make leverages Figma’s vast repository of real-world design data, enabling it to produce high-quality, structurally sound UIs.
However, its output quality is directly tied to the quality of your input. A messy prompt yields a messy app. A structured, well-planned prompt yields a clean, responsive, and functional prototype—even with working dark mode.
The Foundational Principle: Planning Before Prompting
Before touching Figma Make, you must plan your entire app outside of Figma. This isn’t optional—it’s the bedrock of the entire workflow.
The creator of this method uses ChatGPT’s web interface for brainstorming. For example, when building an app to help users find workspaces outside their homes (“Workspot”), they outlined:
- Target audience
- Core features
- User flows
- Value proposition
After reviewing and editing this plan, they finalized a clear vision—only then did they proceed to Figma.
Step-by-Step Workflow: From Idea to Figma Make Prompt
This workflow consists of three critical preparation steps, each generating structured output that feeds into a final master prompt. Below is the complete process:
Step 1: Generate a Complete App Overview
Use a specialized prompt (available in the AI Labs Discord resources) to get ChatGPT to outline your entire app. This includes purpose, user roles, key screens, and functionality.
Why it matters: This context is essential for Figma Make to understand what your app is about—not just how it looks, but what it does.
Step 2: Define Page Architecture
This step maps out the structure of every page in your app. Earlier attempts failed because pages lacked consistent architecture, leading to visual and functional inconsistencies.
The prompt ensures each screen has a defined layout, navigation pattern, and component hierarchy—critical for a cohesive user experience.
Step 3: Create a Full Design System
Use ChatGPT to generate detailed design specifications:
- Color palette (primary, secondary, accent, background, text)
- Typography (font families, sizes, weights)
- Spacing system (padding, margins, grid)
- Component styles (buttons, cards, inputs)
Important: Review and finalize this design system before proceeding. Once locked in, Figma Make will apply it consistently across all screens.
Assembling the Master Prompt for Figma Make
After completing the three steps above, you combine all outputs into one comprehensive prompt. The structure includes placeholders for:
- App Overview (from Step 1)
- Page Architecture (from Step 2)
- Design System (from Step 3)
Copy the responses from ChatGPT and paste them into the corresponding sections of the master prompt template.
Executing Figma Make: Best Practices for Optimal Output
When using Figma Make, follow this sequence:
- Paste standard best practices instructions at the start of every session. These enforce clean, maintainable, and responsive code patterns.
- Paste your final master prompt containing all three planning outputs.
- Allow Figma Make time to process, structure the code, and generate the design.
The result? A fully responsive, organized, and usable prototype—not the chaotic mess produced by unstructured prompting.
Real-World Result: The Workspot App Case Study
Using this workflow, the creator generated the “Workspot” app entirely via Figma Make. The output included:
- Clean, well-structured UI
- Functional dark mode toggle
- Responsive layouts across screen sizes
- Organized page hierarchy matching the planned architecture
Critically, the design wasn’t just visually appealing—it was logically structured as a real React app, with components and routing ready for development.
From Prototype to Production: Extending Figma Make with AI Coding Agents
If you’re a solo developer or need to build a real application (not just a prototype), Figma Make’s output is just the beginning. The generated React code can be enhanced and connected to a backend using AI coding agents.
The creator uses Warp Code (a sponsor of the original video) to automate this process. Here’s how:
- Download the React code from Figma Make.
- Input a custom universal full-stack conversion prompt into Warp Code.
- Enable “auto mode” to let Warp Code process components automatically.
- Warp Code builds a functional backend using mock data (e.g., from Figma’s generated content).
- Review changes in Warp’s interface to verify implementation accuracy.
- Push the final code to GitHub.
This approach makes it easy to later integrate real backends like Supabase—simply replace mock data with live API calls.
Using Existing Figma Designs with AI: Introducing Dev Mode MCP Server
What if you don’t want to design from scratch? Figma’s Dev Mode MCP (Model Context Protocol) Server allows AI coding agents to pull design context directly from Figma files—even those found online.
This feature bridges the gap between design and code by giving your AI agent full access to your design’s metadata, structure, and assets.
Setting Up the Figma MCP Server (Local vs. Remote)
While a remote MCP server exists, the creator prefers the local MCP server, which requires:
- Downloading the Figma desktop app (not using the browser version)
- Enabling Dev Mode in Figma
- Activating the MCP server within Dev Mode
Alternative: Open-source MCP servers are available but can be complex to set up (a dedicated tutorial video exists for this).
Step-by-Step: Converting a Figma Design to Code Using Warp Code & MCP
Here’s how to clone an existing Figma design (e.g., an expenses app found online) using AI:
- Switch to Dev Mode in Figma.
- Enable the MCP server.
- Download the configuration file from Figma’s official site (link provided in video description).
- In Warp Code, type
/commandand select “Add an MCP”. - Paste the configuration and save.
- Critical setting: Set “image source” to download (not local server) so icons and images are pulled into the code.
How the AI Agent Processes Your Design
Once connected, the agent:
- Fetches metadata from all design pages.
- Captures screenshots to distinguish real app screens from promotional mockups.
- Generates a
page-links.mmdfile listing all valid screens. - If the design has more than 10 pages, it creates a design guide to manage complexity.
- Builds a to-do list of pages to implement.
- Automatically begins coding each screen in sequence.
The Secret Weapon: Implementation Configuration Files
Raw MCP output can be flawed. The creator discovered that without guidance, layouts break, icons misrender, and scroll behaviors fail.
Solution: A custom configuration file
- “Images and icons should always be used as image assets.”
- “Long screens must be scrollable.”
- “Card carousels should be horizontally scrollable.”
Before vs. After Comparison:
| Without Configuration File | With Configuration File |
|---|---|
| Layouts broken on mobile | Fully responsive design |
| Icons not implemented or wrong color | Icons properly rendered (minor contrast fixes needed) |
| Static, non-scrollable screens | Scrollable long content and horizontal carousels |
| Unusable prototype | Nearly production-ready UI |
Even with the config file, minor tweaks may be needed (e.g., changing icon colors for better contrast). But these are easily fixed with a simple prompt: “Change all icons to white for better contrast.”
Supercharging Your UI: Integrating ShadCN with MCP
To elevate your AI-generated app, integrate ShadCN components using the ShadCN MCP server.
ShadCN offers:
- High-quality, accessible React components
- Multiple variants (e.g., button styles, card layouts)
- Compatibility with popular UI libraries like Aceternity UI (known for animated components)
How to enable: Add the ShadCN MCP server to your coding agent (e.g., Warp Code) the same way you added Figma’s MCP. Once connected, your AI can replace generic elements with real ShadCN components—enhancing both aesthetics and functionality.
Tool Stack Summary: Everything You Need
Here’s a complete list of tools mentioned in the workflow:
| Tool | Purpose | Notes |
|---|---|---|
| Figma Make | AI-powered design-to-code generator | Requires structured prompting |
| ChatGPT | App planning, architecture, design system | Web interface preferred for ease of use |
| Warp Code | AI coding agent for full-stack implementation | Offers Pro plan for $5 with code “labs” |
| Figma Desktop App | Required for local MCP server | Browser version won’t work |
| Supabase | Backend database integration | Replaces mock data in final app |
| ShadCN | Production-ready UI components | Used via ShadCN MCP server |
| Aceternity UI | Animated component library | Works with ShadCN |
Pro Tips for Maximizing Figma Make’s Potential
- Always start with planning—never skip the three-step prep phase.
- Use the best practices prompt in every Figma Make session to enforce clean code.
- Lock your design system early to ensure visual consistency.
- Review AI-generated code before pushing to production—automation isn’t perfect.
- Combine Figma MCP + ShadCN MCP for the most advanced, production-grade results.
Troubleshooting Common Figma Make Issues
Problem: Generated app is disorganized and non-functional
Solution: You skipped structured planning. Go back and complete Steps 1–3 before re-prompting.
Problem: Icons or images don’t appear in the coded app
Solution: In your coding agent (e.g., Warp Code), ensure the image source is set to “download,” not “local server.”
Problem: Layout breaks on mobile or small screens
Solution: Use the implementation configuration file with responsive rules. Also verify your design system includes mobile breakpoints.
Advanced: Converting Figma Make Output to Next.js
Because Figma Make generates well-structured React code, converting it to a Next.js app is straightforward. The consistent component structure and dependency usage make refactoring minimal. Simply:
- Move pages into the
app/orpages/directory. - Replace React Router with Next.js routing.
- Integrate your backend (e.g., Supabase) using Next.js API routes or server components.
Resource Links & Where to Find Templates
The original creator provides several key resources:
- Full Figma Make workflow prompt → AI Labs Discord (Resources section)
- Figma MCP configuration file → Video description
- Implementation rules configuration file → Linked in resources
- Tutorial on open-source MCP setup → Separate video (linked in description)
- ShadCN MCP setup guide → Linked in description
Special Offer: Warp Code Pro for $5
At the time of the video, Warp Code offered its Pro plan for only $5 (normally higher) using promo code labs. This plan unlocks advanced AI coding features essential for full-stack implementation.
Final Thoughts: AI Won’t Replace Designers—But It Will Empower Them
Figma Make isn’t a magic button—it’s a force multiplier for thoughtful designers and developers. By combining human strategy (planning, design systems, architecture) with AI execution (code generation, implementation), you can go from idea to functional app in a fraction of the time.
The future belongs to those who use AI not as a crutch, but as a collaborator—guided by clear intent, structured workflows, and deep understanding of both design and code.
Action Plan: Your Next Steps
- Join the AI Labs Discord to access the Figma Make workflow template.
- Brainstorm your next app idea using ChatGPT—define audience, features, and flows.
- Run the three-step prep process (overview, architecture, design system).
- Assemble and execute your master prompt in Figma Make.
- If building a real app, connect your output to Warp Code with the implementation config file.
- Enhance your UI with ShadCN via MCP for production-ready polish.
By following this comprehensive guide, you’ll not only use Figma Make correctly—you’ll use it to its full potential, turning ideas into reality faster and smarter than ever before.
