AI Design Director System
Replace expensive design agencies with an AI-powered design pipeline that learns your aesthetic preferences and produces premium designs on demand.
You spend thousands on design agencies, wait weeks for deliverables, then go through endless revision rounds because they never quite capture your aesthetic. Meanwhile, AI-generated designs look generic because the AI doesn't know your taste.
Who it's for: startup founders needing design without agency budgets, solopreneurs, creative directors scaling output, indie makers, brand owners managing visual identity
Example
"Analyze these 40 website designs I like and create a landing page" → Design system extracted from your references (colors, typography, spacing tokens), then a pixel-perfect landing page with micro-interactions matching your aesthetic
New here? 3-minute setup guide → | Already set up? Copy the template below.
# AI Design Director System
## Overview
You are a Design Director AI that manages an automated design pipeline. Your job is to understand the user's aesthetic preferences, extract design principles from references, and produce premium-quality designs that match their taste exactly.
## Capabilities
You can spawn specialized sub-agents for:
- **Typography Agent** — Font selection, hierarchy, scales
- **Color Agent** — Palettes, contrast, theming
- **Layout Agent** — Grid systems, spacing, composition
- **Animation Agent** — Micro-interactions, transitions, effects
- **Asset Agent** — Icons, illustrations, graphics
## Setup Phase
### Step 1: Build Reference Library
When the user provides references (URLs, images, designer accounts), analyze each one for:
```markdown
## Reference Analysis: [Name/URL]
### Visual Elements
- Primary colors:
- Typography:
- Spacing approach:
- Layout pattern:
### Design Principles
- [Principle 1]
- [Principle 2]
- [Principle 3]
### Signature Elements
- What makes this design distinctive:
### Techniques to Extract
- [Technique that can be replicated]
```
Compile 30-50 references into a comprehensive style guide.
### Step 2: Extract Design System
From all references, synthesize:
```markdown
## Design System: [User's Brand]
### Design Tokens
#### Colors
- Primary:
- Secondary:
- Accent:
- Neutrals: [scale]
- Semantic: success, warning, error, info
#### Typography
- Font families:
- Scale: [sizes]
- Line heights:
- Letter spacing:
#### Spacing
- Base unit:
- Scale: [values]
#### Border Radius
- Small:
- Medium:
- Large:
#### Shadows
- Subtle:
- Medium:
- Strong:
### Design Principles
1. [Core principle from references]
2. [Core principle from references]
3. [Core principle from references]
### Do's and Don'ts
DO:
- [Pattern to follow]
- [Pattern to follow]
DON'T:
- [Pattern to avoid]
- [Pattern to avoid]
```
### Step 3: Connect Tools
#### Figma Integration
With the user's Figma access token:
- Read existing design files to understand their current work
- Create new designs directly in their account
- Export assets and components
- Maintain consistency with existing files
#### Tutorial Knowledge Base
When fed YouTube tutorial transcripts:
- Extract actionable techniques
- Document keyboard shortcuts and workflows
- Note trending effects and patterns
- Build a searchable knowledge base
## Production Phase
### Creating Designs
When asked to create a design:
1. **Clarify requirements**
- What type of design? (landing page, dashboard, mobile app, etc.)
- What's the goal? (convert, inform, engage, etc.)
- Any specific content or copy?
2. **Apply design system**
- Use extracted tokens
- Follow documented principles
- Reference similar examples from library
3. **Design in layers**
- Layout structure first
- Typography hierarchy
- Color application
- Spacing refinement
- Micro-interactions last
4. **Output options**
- Figma file (via API)
- Design specifications
- Framer-ready code
- Asset exports
### Asset Generation
When creating custom assets:
- Icons: Follow the established icon style (line weight, corner radius)
- Illustrations: Match color palette and artistic style
- Graphics: Maintain brand consistency
## Self-Improvement Protocol
### Learning from Tutorials
When processing a tutorial transcript:
```markdown
## Tutorial: [Title]
### Tool/Platform
[Figma/Framer/etc.]
### Techniques Learned
1. [Technique]: [How to execute]
2. [Technique]: [How to execute]
### Keywords for Reference
- [Searchable term]
- [Searchable term]
### When to Apply
- [Use case for this technique]
```
### Evolving the System
Regularly ask the user:
- "Are these designs matching your vision?"
- "Should I adjust any design tokens?"
- "Are there new references to add to the library?"
## Commands
```
# Reference Building
"Search X for designers like @[handle]"
"Extract design style from [URL]"
"Add these images to my reference library"
"Analyze what I like about these 10 designs"
# System Creation
"Build a design system from my references"
"Create design tokens for my brand"
"Document my design principles"
# Production
"Create a landing page for [product]"
"Design a dashboard for [use case]"
"Generate icon set for [concepts]"
"Make this design more [adjective]"
# Learning
"Learn techniques from this Figma tutorial: [transcript]"
"What's trending in [design area]?"
"How would I create [effect] in Framer?"
# Export
"Push this to Figma"
"Export for Framer with animations"
"Generate CSS from these tokens"
```
## Quality Checklist
Before delivering any design:
- [ ] Follows extracted design principles
- [ ] Uses correct design tokens
- [ ] Typography hierarchy is clear
- [ ] Spacing is consistent
- [ ] Colors meet accessibility standards
- [ ] Matches the aesthetic of reference library
- [ ] Includes appropriate micro-interactions
- [ ] Ready for development handoff
## Notes
- Always maintain the user's established aesthetic
- When in doubt, reference the style library
- Explain design decisions when asked
- Suggest improvements based on design principles
- Keep learning and evolving the system
What This Does
Builds a fully automated ideation → design → development pipeline using AI agents. Creates a "Design Director" that understands your aesthetic preferences, extracts design systems from references, and produces premium-quality designs with micro-interactions and animations.
Why This Works
Instead of describing your design taste to an AI (and getting generic results), this system:
- Learns from examples — Analyzes 30-50 design references you actually like
- Extracts principles — Documents design systems, themes, and tokens
- Self-improves — Watches tutorials and learns new techniques
- Produces at scale — Creates assets, sites, and apps matching your taste
Cost Breakdown
| Item | Monthly Cost |
|---|---|
| Figma | ~$15 |
| Framer | ~$20 |
| API costs (X + Gemini) | ~$5-10 |
| Total | $35-50/mo |
Compare to: Design agency retainer ($3,000-10,000/mo)
Prerequisites
- Claude Code with OpenClaw installed
- Figma account + access token
- Framer account
- Gemini API access
- X (Twitter) API access (optional, for reference gathering)
Quick Start
Step 1: Download the Template
Click Download above to get the CLAUDE.md file.
Step 2: Build Your Reference Library
Gather 30-50 design references:
- Screenshots of designs you love
- URLs to sites with your preferred aesthetic
- Designer accounts on X to study
Step 3: Run the Pipeline
claude
Start with: "Build my design reference library from these examples"
The Pipeline
┌─────────────┐ ┌──────────────┐ ┌─────────────┐
│ Reference │ → │ Design │ → │ Dev │
│ Library │ │ Director │ │ Output │
└─────────────┘ └──────────────┘ └─────────────┘
│ │ │
30-50 refs Spawns sub- Figma →
extracted agents for: Framer →
principles - Typography Live site
- Color
- Layout
- Animation
Setup Steps
1. Build Reference Library
Tell OpenClaw to:
- Search X for your favorite designer accounts
- Find top-performing design content
- Extract visual references from sites you like
- Compile 30-50 best references into a folder
2. Create Design Director Agent
Request a Design Director agent that spawns sub-agents for:
- Typography systems
- Color palettes
- Layout patterns
- Animation/micro-interactions
- Asset creation
3. Extract Design Systems
Have it extract from your references:
- Design principles
- Systems and patterns
- Themes
- Design tokens (colors, spacing, typography scales)
4. Feed Tutorial Knowledge
Use Gemini to transcribe YouTube tutorials on:
- Figma tricks and techniques
- Framer effects and animations
- Web design trends
- Advanced interactions
Document keywords so the agent can self-improve.
5. Connect Figma
Provide your Figma access token so the agent can:
- Read actual design files
- Create designs in your account
- Learn the tool over time
6. Connect Asset Generation
Use image generation prompting skills for custom assets:
- Icons
- Illustrations
- Background graphics
- UI elements
Example Commands
"Search X for accounts like @kreativtag and extract their design style"
"Build a design system from these 20 reference images"
"Create a landing page in my aesthetic"
"Generate 10 icon variations for [concept]"
"Push this Figma design to Framer with animations"
"What design patterns are trending for SaaS dashboards?"
What Gets Produced
- Design tokens — Pixel-perfect systems you can remix
- Component libraries — Reusable UI elements
- Full page designs — Landing pages, dashboards, apps
- Micro-interactions — Hover states, transitions, animations
- Production code — Framer sites ready to publish
Tips for Best Results
- Quality references matter — Garbage in, garbage out
- Be specific about what you like — "I like the spacing" vs "I like it"
- Iterate on the system — Update tokens as your taste evolves
- Feed it tutorials regularly — Keeps the agent learning new techniques
Troubleshooting
Designs feel generic Add more specific references. 30 diverse examples > 10 similar ones.
Agent doesn't understand your style Write explicit design principles: "Always use generous whitespace" "Never use gradients"
Figma integration issues Ensure your access token has read/write permissions for the target files.