# Create Parallel React POCs ## Request: $ARGUMENTS Usage: `/prp-poc-create-parallel [number_of_demos] "[problem_statement]"` Example: `/prp-poc-create-parallel 5 "create a dashboard for tracking team productivity with real-time metrics"` ## Parallel POC Creation Mission Create multiple React POC variations simultaneously to **maximize concept validation** through diverse implementation approaches. This command generates PRPs for parallel execution using specialized UI/UX and User Journey agents. **Critical Understanding**: Each POC targets different aspects of the same problem: - Different UI/UX approaches (minimal, polished, experimental) - Different user journey focuses (power user, casual user, admin) - Different technical approaches (component-heavy, page-based, single-file) - Different fidelity levels (wireframe, demo, MVP) ## Parallel Creation Strategy ### Agent Specialization Pattern For **N demos** requested, create **N pairs** of specialized agents: - **N UI-UX Agents**: Each focusing on different design approaches - **N User Journey Agents**: Each targeting different user personas/flows **Agent Assignment Matrix:** ```yaml Demo 1: @ui-ux-agent (Minimal/Clean) + @user-journey-agent (Power User) Demo 2: @ui-ux-agent (Polished/Professional) + @user-journey-agent (Casual User) Demo 3: @ui-ux-agent (Experimental/Modern) + @user-journey-agent (Admin User) Demo 4: @ui-ux-agent (Dashboard-Heavy) + @user-journey-agent (Mobile-First) Demo 5: @ui-ux-agent (Component-Library) + @user-journey-agent (Accessibility-First) ``` ### POC Variation Strategy Each POC should explore different aspects: **Design Variations:** - **Minimal**: Clean, simple, content-focused - **Polished**: Professional, brand-aligned, stakeholder-ready - **Experimental**: Modern patterns, micro-interactions, innovative UI - **Dashboard-Heavy**: Data visualization focused, charts/graphs - **Component-Library**: Showcases reusable design system components **User Journey Variations:** - **Power User**: Feature-rich, keyboard shortcuts, advanced workflows - **Casual User**: Simplified navigation, guided experiences, fewer options - **Admin User**: Management interfaces, bulk actions, system controls - **Mobile-First**: Touch-optimized, responsive, gesture-based - **Accessibility-First**: Screen reader optimized, keyboard navigation, high contrast ## Implementation Process ### Step 1: Problem Analysis & POC Strategy Analyze the problem statement and create a **parallel execution plan**: 1. **Parse Request Arguments** - Extract number of demos requested (default: 5) - Analyze problem statement for key concepts and requirements - Identify core user personas and interaction patterns 2. **Design POC Matrix** - Create unique combination of UI approach + User journey for each demo - Ensure each POC validates different aspects of the problem - Plan directory structure: `poc-{problem-slug}-{variant-number}` ### Step 2: Parallel Agent Research **Execute all research agents in PARALLEL using Task tool:** ```yaml # Spawn N pairs of agents simultaneously Task 1 - @ui-ux-agent for Demo 1: "Analyze the problem: '{problem_statement}' and design a MINIMAL/CLEAN UI approach. Focus on: Clean typography, generous whitespace, content-first design. Research component patterns and create UI specifications for a React POC. Target: Stakeholder presentations requiring clear concept demonstration. Return: UI component architecture, styling approach, and design specifications." Task 2 - @user-journey-agent for Demo 1: "Analyze the problem: '{problem_statement}' and design a POWER USER journey. Focus on: Advanced features, keyboard shortcuts, efficient workflows. Research user patterns and create journey specifications for React POC. Target: Users who need maximum functionality and control. Return: User flow architecture, interaction patterns, and journey specifications." Task 3 - @ui-ux-agent for Demo 2: "Analyze the problem: '{problem_statement}' and design a POLISHED/PROFESSIONAL UI approach. Focus on: Brand alignment, professional aesthetics, stakeholder-ready presentation. Research premium component patterns and create UI specifications for React POC. Target: Executive demos and client presentations. Return: UI component architecture, styling approach, and design specifications." Task 4 - @user-journey-agent for Demo 2: "Analyze the problem: '{problem_statement}' and design a CASUAL USER journey. Focus on: Simplified navigation, guided experiences, progressive disclosure. Research beginner-friendly patterns and create journey specifications for React POC. Target: Users new to the system who need guidance and simplicity. Return: User flow architecture, interaction patterns, and journey specifications." # Continue pattern for remaining demos... ``` ### Step 3: PRP Generation from Research After all research agents complete, **synthesize results into POC PRPs**: 1. **Use prp_poc_react.md template** for each POC 2. **Incorporate agent research** into context sections 3. **Customize each PRP** based on UI/UX + User Journey specifications 4. **Create unique identifiers** for parallel development ### Step 4: POC Specification Matrix Generate **N PRPs** with these variations: **POC 1: Minimal Power User** ```yaml poc_name: "poc-{problem-slug}-minimal-power" ui_approach: "Clean, typography-focused, content-first design" user_journey: "Advanced features, keyboard shortcuts, efficient workflows" fidelity: "Demo" unique_aspects: "Focuses on functionality over aesthetics, rapid interaction patterns" ``` **POC 2: Polished Casual User** ```yaml poc_name: "poc-{problem-slug}-polished-casual" ui_approach: "Professional aesthetics, brand-aligned, premium components" user_journey: "Guided experience, progressive disclosure, help tooltips" fidelity: "MVP" unique_aspects: "Executive-ready presentation with beginner-friendly flows" ``` **POC 3: Experimental Admin** ```yaml poc_name: "poc-{problem-slug}-experimental-admin" ui_approach: "Modern patterns, micro-interactions, innovative UI elements" user_journey: "Management interfaces, bulk actions, system administration" fidelity: "Demo" unique_aspects: "Cutting-edge design patterns with administrative power features" ``` **POC 4: Dashboard Mobile-First** ```yaml poc_name: "poc-{problem-slug}-dashboard-mobile" ui_approach: "Data visualization heavy, charts and metrics focused" user_journey: "Touch-optimized interactions, responsive design, gesture-based" fidelity: "Demo" unique_aspects: "Analytics dashboard optimized for mobile devices" ``` **POC 5: Component-Library Accessible** ```yaml poc_name: "poc-{problem-slug}-components-a11y" ui_approach: "Design system showcase, reusable component patterns" user_journey: "Screen reader optimized, keyboard navigation, inclusive design" fidelity: "MVP" unique_aspects: "Accessibility-first design with component library demonstration" ``` ## PRP Output Structure For each POC, generate a complete PRP file: **File:** `PRPs/working-memory/{feature-name}/poc-{problem-slug}-{variant}.md` **Content Structure:** 1. **Goal Section**: Specific to UI approach + User journey combination 2. **POC Scope**: Tailored to the variation's unique focus 3. **Context**: Incorporates both UI-UX and User Journey agent research 4. **Implementation Blueprint**: Customized task sequence for the variant 5. **Validation Loop**: POC-appropriate validation for the specific approach ## Parallel Execution Preparation ### Project Structure Setup ``` react-poc-project/ ├── public/ ├── src/ │ ├── poc-{problem-slug}-minimal-power/ │ ├── poc-{problem-slug}-polished-casual/ │ ├── poc-{problem-slug}-experimental-admin/ │ ├── poc-{problem-slug}-dashboard-mobile/ │ ├── poc-{problem-slug}-components-a11y/ │ └── App.tsx # Main navigation between POCs ├── package.json └── README.md ``` ### Main App Navigation Each POC should be accessible from a main navigation page: ```tsx // App.tsx structure function App() { return ( } /> } /> } /> } /> } /> } /> ) } ``` ## Success Criteria ### Research Quality - [ ] **All agent pairs completed**: N UI-UX + N User Journey agents finished successfully - [ ] **Diverse approaches identified**: Each POC targets different aspects of problem - [ ] **Research synthesis complete**: Agent findings incorporated into PRP context - [ ] **Unique value propositions**: Each POC validates different assumptions ### PRP Quality - [ ] **N complete PRPs generated**: One for each POC variation - [ ] **Context completeness**: Each PRP enables one-pass implementation - [ ] **Validation approaches**: POC-appropriate testing for each variant - [ ] **Implementation clarity**: Clear task sequences for parallel development ### Parallel Readiness - [ ] **Unique naming**: All POCs have distinct identifiers and directories - [ ] **Isolated development**: POCs can be developed simultaneously without conflicts - [ ] **Shared infrastructure**: Common mock data and routing setup defined - [ ] **Execution ready**: All PRPs ready for parallel execution command ## Anti-Patterns ### Research Anti-Patterns - ❌ **Don't create identical approaches**: Ensure each POC explores different aspects - ❌ **Don't skip agent specialization**: Each agent should have distinct focus - ❌ **Don't generalize findings**: Customize context for each POC's unique approach - ❌ **Don't rush parallel research**: Let all agents complete before synthesis ### PRP Generation Anti-Patterns - ❌ **Don't copy-paste PRPs**: Each should be tailored to its unique approach - ❌ **Don't ignore agent research**: Incorporate all findings into appropriate PRPs - ❌ **Don't create conflicting requirements**: Ensure POCs can coexist in same project - ❌ **Don't skip validation customization**: Each POC needs appropriate testing approach ### DO Focus On - ✅ **Maximum concept coverage**: Each POC validates different aspects of the problem - ✅ **Specialized agent research**: Leverage UI-UX and User Journey expertise fully - ✅ **Parallel development readiness**: Structure for simultaneous implementation - ✅ **Stakeholder value**: Each POC provides unique insights for decision making --- **Remember**: The goal is **comprehensive concept validation** through **diverse parallel approaches**. Each POC should explore the problem from a different angle, maximizing the insights available to stakeholders for informed decision-making.