1. Project Title AI Product Workspace Platform 2. Executive Summary The AI Product Workspace Platform is a web-based application designed to centralize product development workflows using AI-powered agents tailored to different roles within a team. The platform enables Business Analysts, Product Owners, Designers, Developers, and QA engineers to collaborate within a single project environment, generating artifacts such as user stories, wireframes, code, and test cases using AI. It integrates with tools like Jira and will evolve into a marketplace for AI agents and extensions. 3. Objectives * Centralize product development workflows * Reduce dependency on multiple disconnected tools * Accelerate delivery using AI-generated outputs * Provide role-specific AI assistance * Enable integration with existing tools (starting with Jira) 4. Scope 4.1 In Scope (Phase 1 - MVP) * User authentication * Project creation and management * Single chat interface per project * Role-based AI agents: * Business Analyst Agent * Designer Agent * Developer Agent * Shared project context (memory) * Structured outputs: * User stories * Wireframes (text-based or simple representation) * Code snippets * Basic credit/usage system 4.2 Out of Scope (Phase 1) * Marketplace * QA/Test agent * Real-time collaboration * Advanced automation * Full Jira synchronization * Enterprise security features 5. Target Users * Business Analysts (BA) * Product Owners (PO) * UI/UX Designers * Developers * QA/Testers (future phase) 6. User Roles & Capabilities 6.1 Business Analyst / Product Owner * Input requirements * Generate user stories * Define acceptance criteria 6.2 Designer * Generate wireframes * Suggest UI/UX improvements 6.3 Developer * Generate code snippets * Suggest architecture * Convert requirements into implementation 7. Core Features 7.1 Authentication * Email/password login * Basic session management 7.2 Project Management * Create project * View project list * Open project workspace 7.3 Chat System * Single chat per project * Message history storage * AI-generated responses 7.4 AI Agent System Agents are role-based but share the same project context. Agents: * BA Agent * Designer Agent * Developer Agent Capabilities: * Generate outputs based on prompts * Access shared project data 7.5 Context Memory System The system stores and organizes outputs: * User Stories * Design Outputs * Code Snippets Agents can reference previous outputs. 7.6 Output Structuring Each generated output is categorized: * Story * Design * Code Users can: * View outputs separately * Reuse them in future prompts 7.7 Credit System * Free tier with limited usage * Usage tracking per user * Restrict access when credits are exhausted 8. User Flow Step 1: User signs up / logs in Step 2: User creates a project Step 3: User enters project workspace Step 4: User interacts with AI agents via chat Step 5: System generates: * User stories * Designs * Code Step 6: Outputs are stored and reused 9. Technical Requirements 9.1 Frontend * Framework: React (Next.js) * Responsive design * Chat interface 9.2 Backend * Node.js (Express) or Python (FastAPI) * REST API 9.3 AI Integration * Integration with OpenAI API or equivalent 9.4 Database * PostgreSQL 9.5 Hosting * Cloud-based (AWS, Vercel, or similar) 10. Non-Functional Requirements * Performance: <2s response time (excluding AI latency) * Scalability: Support multiple concurrent users * Security: Basic authentication and data protection * Availability: 99% uptime target 11. Deliverables (From Development Company) * Fully functional web application (MVP) * Source code (frontend + backend) * Database schema * API documentation * Deployment setup * Basic testing 12. Timeline Estimated Duration: 4–6 weeks (MVP) 13. Future Phases (Post-MVP) * Integration with Jira * Multi-user collaboration * QA/Test agent * Plugin system * Marketplace * Advanced automation 14. Success Criteria * Users can complete: * Idea → User Story → Design → Code * Stable system with minimal errors * Positive feedback from initial users 15. Budget Considerations (To be defined with development company) Include: * Development cost * AI API usage cost * Hosting cost Optional Section (Strongly Recommended) 16. Questions for Development Company Ask them: * What architecture do you recommend? * How will you handle AI cost optimization? * How will scalability be managed? * What is your testing approach? * What happens after delivery (support/maintenance)?