AI Collaboration Guide for UI Development
Standardized AI prompts, patterns, and quality validation for consistent UI component development across all projects.
AI Collaboration Guide for UI Development
Overview
This guide provides standardized AI prompts, patterns, and quality validation techniques to help create consistent UI components across projects. It aims to enhance collaboration between developers and AI assistants while maintaining architectural standards and code quality.
Why AI Collaboration Patterns Matter
We've found that AI tools can significantly accelerate UI development, but consistency requires thoughtful prompting. These patterns have evolved through extensive experimentation to solve common challenges:
- Consistency: Ensuring all AI-generated components follow the same standards
- Quality: Maintaining high-quality code regardless of who (or what) wrote it
- Learning curve: Reducing the time needed to effectively collaborate with AI
- Maintainability: Creating components that integrate seamlessly with existing code
Purpose & Scope
This guide will help you:
- Craft effective, consistent AI prompts for predictable results
- Ensure AI-generated components align with our architectural standards
- Validate and improve AI-generated code quality
- Create components that seamlessly integrate with existing codebase
- Develop a workflow that combines human expertise with AI capabilities
Core AI Collaboration Principles
Our approach to AI collaboration is built on four key principles that help maintain quality and consistency:
1. Predictable Structure
We help AI understand our three-layer architecture by being explicit about component categories and their characteristics:
By consistently using these structural concepts in our prompts, AI can better understand which type of component we're creating and what standards should apply.
2. Consistent Prompting
Standardized prompts provide a common language between developers and AI systems, leading to more predictable results and reducing miscommunication.
(Consider 🤔) Using the template prompts provided in this guide
These templates were developed through iterative testing to produce high-quality, compliant components consistently.
3. Quality Validation
All AI-generated components benefit from validation against our quality standards, covering areas like accessibility, performance, and testing.
(Do ✅) Review AI-generated code against our quality checklist
This helps catch common issues before integration and ensures all code meets our standards, regardless of its origin.
4. Architectural Compliance
Our prompts explicitly guide AI to follow established architecture patterns, ensuring generated code fits seamlessly into our codebase.
Standard AI Prompts for UI Components
Foundation Component Creation
Basic Foundation Component
Interactive Foundation Component
Pattern Component Creation
Composed Pattern Component
Data Display Pattern
Business Component Creation
Domain-Aware Business Component
Entity Management Component
AI Quality Validation Prompts
Pre-Implementation Validation
Post-Implementation Review
Code Migration Validation
AI-Assisted Development Workflows
New Component Development Flow
Step 1: Requirements Analysis
Step 2: Implementation
Step 3: Quality Assurance
Maintenance and Enhancement Flow
Bug Fix Assistance
Feature Enhancement
AI Prompt Templates by Use Case
Component Creation Templates
Quick Foundation Component
Complex Pattern Component
Business Domain Component
Testing Templates
Comprehensive Test Generation
Accessibility Test Focus
Refactoring Templates
Architecture Compliance Update
Performance Optimization
Quality Assurance Integration
Pre-Merge Checklist for AI-Generated Code
Use this prompt to validate any AI-generated component:
Continuous Quality Monitoring
Integration with Development Workflow
Workflow Integration Points
Our AI collaboration patterns integrate seamlessly with the existing development workflow:
Planning Phase Integration
Development Phase Integration
Quality Assurance Integration
For complete development workflow details, see Component Development Workflow.
Troubleshooting Common AI Issues
Issue: AI Not Using Design Tokens
Problem: AI generates hardcoded values instead of theme tokens Solution: Use this corrective prompt:
Issue: AI Missing Accessibility Features
Problem: AI generates components without proper accessibility Solution: Use this enhancement prompt:
Issue: AI Creating Wrong Component Category
Problem: AI places components in wrong folders or mixes concerns Solution: Use this correction prompt:
Related Documents
- UI Architecture Standards - Mandatory development standards
- UI Architecture Overview - Complete architecture guide
- Foundation Components Guide - Component development patterns
- Component Development Workflow - Step-by-step development process
- Core Architecture - System architecture
- Project Structure - File organization
This guide ensures consistent, high-quality AI collaboration for UI component development across all projects.
UI Architecture Standards
Mandatory standards for UI folder organization, component development patterns, and quality requirements across all frontend projects.
Foundation Components Guide
Comprehensive guide to creating, implementing, and maintaining foundation components with design token integration and AI collaboration patterns.