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+## Research Summary for Task Management System
+
+### Domain Analysis
+- **Industry**: Productivity/Project Management Software
+- **Scale Requirements**: 1,000+ concurrent users, 10,000+ tasks, real-time collaboration
+- **Key Challenges**: Real-time updates, data consistency, user permission management, notification delivery
+
+### Architectural Approaches Considered
+
+1. **Microservices Architecture**
+   - Description: Decompose system into independent services for users, tasks, projects, notifications
+   - Pros: Independent scaling, fault isolation, technology diversity, team autonomy
+   - Cons: Operational complexity, network latency, distributed transactions, higher cost
+
+2. **Monolithic Architecture**
+   - Description: Single application with modular components within one deployable unit
+   - Pros: Simpler deployment, easier debugging, lower operational overhead, better performance
+   - Cons: Scalability limits, technology lock-in, deployment risks, team coordination challenges
+
+3. **Event-Driven Architecture with CQRS**
+   - Description: Command Query Responsibility Segregation with event sourcing
+   - Pros: Excellent scalability, audit trails, real-time updates, loose coupling
+   - Cons: High complexity, eventual consistency, steep learning curve, debugging challenges
+
+### Technology Stack Research
+
+#### Backend Frameworks
+- **Node.js + Express**: Excellent for real-time features, large ecosystem, fast development
+- **Python + FastAPI**: Strong typing, async support, good for APIs, data science integration
+- **Java + Spring Boot**: Enterprise-grade, mature ecosystem, strong consistency
+
+#### Database Options
+- **PostgreSQL**: ACID compliance, JSON support, reliability, good for complex queries
+- **MongoDB**: Flexible schema, horizontal scaling, good for rapid development
+- **MySQL**: Mature, widely used, good performance, familiar to most developers
+
+#### Real-time Communication
+- **WebSockets**: Direct communication, low latency, widely supported
+- **Server-Sent Events (SSE)**: Simpler than WebSockets, good for one-way updates
+- **Message Queues (Redis/RabbitMQ)**: Reliable delivery, scalable, decoupled
+
+### Recommended Technology Stack
+
+- **Architecture Pattern**: **Modular Monolith with Microservice Readiness**
+  - Start with monolith for speed and simplicity
+  - Design modules to be easily extractable into microservices later
+  - Use clear boundaries between functional areas
+
+- **Backend**: **Node.js + TypeScript + Express**
+  - TypeScript for type safety and better development experience
+  - Express for mature, well-documented framework
+  - Excellent ecosystem for real-time features (Socket.io)
+  - Good performance for I/O-bound applications
+
+- **Database**: **PostgreSQL + Redis**
+  - PostgreSQL as primary database for ACID compliance and reliability
+  - Redis for session management, caching, and real-time data
+  - Both have excellent Node.js support
+
+- **Real-time Communication**: **Socket.io + Redis Adapter**
+  - Socket.io for WebSocket connections with fallback support
+  - Redis adapter for multi-instance scaling
+  - Proven solution for real-time collaboration
+
+- **Authentication**: **JWT + Refresh Tokens**
+  - JWT for stateless authentication
+  - Refresh tokens for security and better user experience
+  - Industry standard with good library support
+
+- **Infrastructure**: **Docker + AWS ECS/RDS**
+  - Docker for containerization and consistency
+  - AWS ECS for managed container orchestration
+  - AWS RDS for managed PostgreSQL with automatic backups
+
+### Research Sources
+
+1. **"Microservices vs Monolith: When to Choose Which"** (Martin Fowler, 2024)
+   - Key insight: Start with monolith, extract microservices when clear boundaries emerge
+   - Most successful microservices implementations evolved from monoliths
+
+2. **"Real-time Web Application Architecture Best Practices"** (InfoQ, 2024)
+   - WebSocket scaling challenges and solutions
+   - Redis adapter pattern for multi-instance deployments
+
+3. **"PostgreSQL vs MongoDB for Task Management Systems"** (Database Journal, 2024)
+   - PostgreSQL superior for complex queries and data consistency
+   - JSON support provides flexibility when needed
+
+4. **"Node.js TypeScript Best Practices for Enterprise Applications"** (Node.js Foundation, 2024)
+   - Type safety significantly reduces runtime errors
+   - Better development experience with IDE support
+
+5. **"Authentication Patterns for Modern Web Applications"** (OWASP, 2024)
+   - JWT + refresh token pattern recommended for SPA applications
+   - Proper token storage and refresh strategies
+
+### Decision Rationale
+
+**Why Modular Monolith First:**
+- Team size (3-5 developers) doesn't warrant microservices complexity
+- Faster time-to-market with simpler deployment and debugging
+- Clear module boundaries will allow future extraction if needed
+- Lower operational cost and complexity for initial launch
+
+**Why Node.js + TypeScript:**
+- Real-time features are first-class citizens in Node.js ecosystem
+- TypeScript provides enterprise-grade type safety
+- Large talent pool and extensive library ecosystem
+- Excellent performance for our I/O-bound use case
+
+**Why PostgreSQL + Redis:**
+- Data consistency is critical for task management
+- PostgreSQL handles complex queries and relationships well
+- Redis provides excellent caching and real-time data capabilities
+- Both technologies are mature, well-supported, and cost-effective
+
+**Why Socket.io for Real-time:**
+- Handles WebSocket connection management complexity
+- Provides automatic fallback to other transport methods
+- Redis adapter enables horizontal scaling
+- Large community and proven track record
+
+This technology stack balances development speed, operational simplicity, and future scalability while leveraging current best practices and well-established patterns.