The coding landscape has fundamentally changed. What once required hours of research, planning, and trial-and-error can now be accomplished efficiently with the right AI-powered workflow. But most developers are missing the secret: structured AI collaboration.
Todo2 isn’t just another task manager – it’s a Cursor extension that transforms your IDE into an AI-powered development environment through Model Context Protocol (MCP) integration.
The Structured AI Advantage
Traditional AI coding follows a chaotic pattern:
- Ask AI for code snippets
- Copy-paste without full understanding
- Debug when things inevitably break
- Repeat until it works
With Todo2’s structured approach in Cursor:
- Plan with clear objectives and scope
- Research with AI-powered web search and documentation
- Implement with full context and structured guidance
- Review and document outcomes for future reference
The result? Higher quality code with deeper understanding and better long-term maintainability.
Todo2: Your AI Development Companion
Todo2 is a Cursor extension that provides AI-powered task management through MCP integration. This means your AI assistant can:
- Create and manage development tasks
- Perform structured research with web search
- Track implementation progress
- Document decisions and outcomes
- Maintain project context across sessions
All without ever leaving your Cursor IDE.
Ready to supercharge your AI-powered development? Install Todo2 for Cursor and experience structured AI collaboration that actually scales with complex projects.
Advanced AI Coding with Todo2’s MCP Integration
1. Structured Research Conversations
Don’t just ask for code – engage in structured research first:
AI: "I'll research modern authentication patterns for you"
> Uses Todo2's research tools to search web for 2025 best practices
> Documents findings with links and analysis
> Creates implementation plan based on research
Result: Informed decisions, not random code generationTodo2’s research phase ensures every implementation is backed by current best practices and documented rationale.
2. Context-Aware Task Management
Provide rich context through Todo2’s structured workflow:
User: "Create a todo for password reset functionality"
AI: "I'll create a structured todo with research requirements"
> Creates todo with detailed acceptance criteria
> Plans research phase for security best practices
> Sets up implementation structure
> Defines review and testing requirementsThe AI maintains full project context through Todo2’s workspace-specific storage.
3. Intelligent Progress Tracking
Instead of losing track of complex features, Todo2 provides structure:
User: "Show me the status of the auth system implementation"
AI: "Let me check your Todo2 progress"
> Reviews current todos and their states
> Shows research completed, implementation progress
> Identifies blockers and next steps
> Suggests optimal task sequencingThe Art of Structured AI Prompting
Research-First Development
❌ "Create a user authentication system"
✅ "Create a todo for user authentication, then research 2025
security best practices including OAuth, JWT handling,
and rate limiting approaches"Todo2 enforces the research phase, preventing uninformed implementations.
Context-Rich Task Creation
❌ "Add validation"
✅ "Create a todo for input validation that handles our current
user model, integrates with our error handling patterns,
and follows our API security standards"Structured Documentation
"Document the implementation approach, key decisions made,
and lessons learned for future reference"Todo2’s result comments capture institutional knowledge that would otherwise be lost.
Tired of losing context between coding sessions? Todo2’s MCP integration maintains project memory in Cursor, ensuring your AI assistant always understands your project’s current state and history.
Productivity Patterns That Scale
The “Structured Research” Method
Traditional approach: Ask AI for code, hope it works. Todo2 approach: Research → Plan → Implement → Review
// Todo2 Workflow Example:
// 1. Research: AI searches for rate limiting patterns
// 2. Plan: Create implementation strategy
// 3. Implement: Code with full context
function rateLimiter(req, res, next) {
// Implementation based on researched best practices
// AI suggestions are contextually relevant
// Decisions are documented for future reference
}
// 4. Review: Document approach and lessons learnedWorkspace-Specific Intelligence
Todo2 stores project state in .todo2-state.json in your workspace, meaning:
- Project memory – AI remembers your specific context
- Version control integration – Todo history travels with code
- Team collaboration – Shared understanding of project status
- Long-term learning – Accumulated project knowledge
Progressive Enhancement with Structure
Build features systematically with Todo2’s workflow:
1. Create todo: "Basic user registration endpoint"
2. Research: Security patterns, validation approaches
3. Implement: MVP with proper error handling
4. Review: Document security considerations
Next iteration:
1. Create todo: "Add email verification to registration"
2. Research: Email service patterns, verification flows
3. Implement: Enhanced registration with verification
4. Review: Document integration patternsMeasuring Your AI-Enhanced Productivity
Track these metrics to quantify Todo2’s impact:
Development Quality Metrics
- Research depth before implementation
- Bug density in initial implementations
- Code review feedback volume and type
- Technical debt accumulation over time
Workflow Efficiency Metrics
- Time from idea to working prototype
- Context switching frequency
- Knowledge retention across sessions
- Team alignment on project status
Most developers using Todo2 report:
- 60% better code quality due to research-first approach
- 40% faster feature development with structured workflows
- 80% better project context retention across sessions
- Significantly improved team communication through documented decisions
Advanced Todo2 Workflow Patterns
Dependency-Driven Development
User: "Create todos for the entire user management system"
AI: "I'll create a structured todo hierarchy"
> Creates foundational todos (database, models)
> Sets up dependent todos (authentication, authorization)
> Plans integration todos (API endpoints, UI)
> Establishes testing and deployment todosResearch-Driven Architecture
User: "Research microservices vs monolith for our project"
AI: "I'll create a research todo and investigate both approaches"
> Searches current best practices and trade-offs
> Documents findings with links and analysis
> Creates follow-up todos based on research conclusionsIterative Improvement Cycles
User: "Add a result comment to the authentication todo"
AI: "I'll document the implementation outcomes"
> Records what was built and how
> Captures lessons learned and gotchas
> Identifies areas for future improvement
> Updates related todos based on learningsCommon AI Development Traps (And How Todo2 Prevents Them)
Over-Engineering with AI
Problem: AI generates complex solutions quickly without considering simplicity. Todo2 Solution: Research phase includes evaluating solution complexity and trade-offs.
Context Loss in Long Sessions
Problem: AI conversations become lengthy and lose focus. Todo2 Solution: Structured comments maintain context across sessions and team members.
Blind Implementation
Problem: Copy-pasting AI code without understanding. Todo2 Solution: Research and review phases ensure understanding and documentation.
Inconsistent Patterns
Problem: AI suggestions vary without project-specific context. Todo2 Solution: Workspace-specific storage maintains consistent patterns and decisions.
Building Your Todo2 AI Workflow
Start with Simple Features
Begin with low-risk tasks to learn the Todo2 workflow:
- Utility functions with research requirements
- API endpoints with security considerations
- UI components with accessibility research
- Database schemas with performance analysis
Develop Structured Prompting Skills
Learn to work with Todo2’s MCP tools:
- “Create a todo for…” instead of “Write code for…”
- “Research current best practices for…” before implementation
- “Add a result comment documenting…” after completion
- “Show me todos that are ready for implementation”
Integrate with Your Team Workflow
Connect Todo2 with your development process:
- Code review integration with documented decisions
- Sprint planning with research-backed estimates
- Knowledge sharing through structured comments
- Onboarding with project context preservation
Ready to transform your development team’s AI workflow? Todo2’s Cursor integration provides structured AI collaboration that scales from individual projects to enterprise development teams.
The Future of AI-Powered Development
We’re moving beyond simple code generation to structured AI collaboration. The developers and teams who learn to work with AI through structured workflows like Todo2 will have a significant advantage as these tools become more sophisticated.
The key insight: AI is most powerful when guided by structure, not when left to generate code randomly. Todo2 provides that structure while keeping everything seamlessly integrated in your Cursor IDE.
How has structured AI collaboration changed your development workflow? What productivity gains have you seen with research-driven development? Share your Todo2 experiences and help the community level up together.