Checkpoints & Branching: Safe Experimentation at Scale

Checkpoints & Branching: Safe Experimentation at Scale

Checkpoints in Cursor are like Git commits for your AI-assisted development—but faster and more fluid. They enable fearless experimentation, allowing you to try bold refactoring approaches knowing you can instantly revert if things go wrong.

Understanding Cursor’s Checkpoint System

Unlike Git, which requires explicit commits, Cursor automatically creates lightweight snapshots of your code at key moments. Think of it as having an intelligent “undo” system that understands the semantic boundaries of your changes.

Tip

Key Insight: Checkpoints are stored locally and separately from Git. They’re designed for rapid experimentation during development, not long-term version control.

How Checkpoints Work

Automatic Checkpoint Creation

Cursor creates checkpoints automatically when:

• Before Agent Mode Changes: Every time Agent starts a task
• After Significant Edits: When Agent completes a multi-file operation
• At Natural Boundaries: Between distinct tasks in a conversation
• On Mode Switches: When changing from Agent to Manual mode

Manual Checkpoint Control

You can also create checkpoints manually:

// In chat, simply ask:
"Create a checkpoint before we start the refactoring"

// Or use the checkpoint button in the UI
// Located in the chat input area when viewing previous messages

Checkpoint Strategies for Complex Work

Strategy 1: The Experimental Branch Pattern

When trying multiple approaches to solve a problem:

1. Create Base Checkpoint

   "Create a checkpoint - we're going to try three different
   approaches to optimize this algorithm"

2. Try Approach 1

   "Implement the optimization using memoization"

3. Checkpoint and Reset

   "Create checkpoint. Now restore to the base and try approach 2"

4. Try Approach 2

   "Implement the optimization using dynamic programming"

5. Compare and Choose Review both implementations, choose the best, restore to it

Strategy 2: Incremental Refactoring

For large-scale refactoring, use checkpoints as milestones:

graph LR A[Start] --> B[Checkpoint: Clean State] B --> C[Refactor Module 1] C --> D[Checkpoint: Module 1 Done] D --> E[Test Module 1] E --> F{Tests Pass?} F -->|Yes| G[Refactor Module 2] F -->|No| H[Restore Checkpoint] H --> I[Fix Issues] I --> E G --> J[Checkpoint: Module 2 Done]

Strategy 3: The Safety Net Pattern

Use checkpoints as insurance for risky operations:

// Before a complex database migration
"Create checkpoint: pre-migration state"

// Before upgrading major dependencies
"Checkpoint before upgrading to React 19"

// Before applying automated fixes
"Checkpoint, then fix all ESLint errors automatically"

Advanced Checkpoint Techniques

1. Checkpoint Chains for Complex Features

When building a feature with multiple interdependent parts:

• DirectoryCheckpoint 1 : Initial setup

  • Created API endpoint structure
  • Added database schema
• DirectoryCheckpoint 2 : Backend complete

  • Implemented business logic
  • Added validation
  • Created tests
• DirectoryCheckpoint 3 : Frontend started

  • Created components
  • Added routing
• DirectoryCheckpoint 4 : Integration complete

  • Connected frontend to API
  • Added error handling
• DirectoryCheckpoint 5 : Polish and optimization

  • Added loading states
  • Implemented caching

2. Parallel Development Tracks

Use checkpoints to explore parallel implementation paths:

Track A: REST API

// Checkpoint: base
"Implement user management as REST API"

// Work progresses...
// Checkpoint: REST implementation complete

Track B: GraphQL

// Restore to: base
"Implement user management as GraphQL API"

// Work progresses...
// Checkpoint: GraphQL implementation complete

Decision

// Compare both implementations
"Show me the differences between the REST
and GraphQL implementations"

// Make decision and proceed with chosen path

3. Checkpoint Annotations

Add meaningful descriptions to your checkpoints:

// Good checkpoint practices
"Checkpoint: Auth system working - all tests passing"
"Checkpoint: Pre-optimization baseline (current: 250ms response)"
"Checkpoint: Feature complete, needs code review"

// Avoid vague checkpoints
"Checkpoint" // Too generic
"Save" // Not descriptive

Working with Checkpoints and Git

Best Practices for Dual Version Control

Use Checkpoints for Exploration

Quick iterations, trying different approaches, temporary experiments

Use Git for Milestones

Completed features, stable states, team collaboration

Checkpoint-to-Git Workflow

1. Start with a clean Git state

   git status # Ensure clean working directory

2. Use checkpoints during development

   • Create multiple checkpoints as you work
   • Try different approaches
   • Refactor fearlessly

3. Consolidate into Git commits

   # After reaching a good state via checkpoints
   git add -A
   git commit -m "feat: implement user authentication"

4. Clean checkpoint history

   • Checkpoints auto-expire after the session
   • No need for manual cleanup

Real-World Checkpoint Scenarios

Scenario 1: Debugging a Complex Issue

A senior developer used checkpoints to isolate a performance bug:

// Checkpoint 1: Baseline (bug present)
"Checkpoint: Performance bug baseline - page loads in 3s"

// Checkpoint 2: Added logging
"Add performance logging to all database queries"
// Discovered N+1 query issue

// Checkpoint 3: First fix attempt
"Implement eager loading for user.posts relationship"
// Reduced to 1.5s, but not enough

// Checkpoint 4: Optimized query
"Rewrite the query to use a single JOIN"
// Success! 200ms load time

// Final: Clean up logging and commit
"Remove debug logging, keep the optimized query"

Scenario 2: API Migration

Migrating from REST to GraphQL while maintaining backward compatibility:

Phase 1: Parallel APIs

// Checkpoint: REST API stable
"Create GraphQL resolvers that call existing REST controllers"

// This allows both APIs to work simultaneously
// Checkpoint: Dual API support

Phase 2: Migration

// Checkpoint: Begin controller migration
"Move business logic from REST controllers to service layer"

// Both APIs now use the same service layer
// Checkpoint: Shared business logic

Phase 3: Deprecation

// Checkpoint: Add deprecation warnings
"Add deprecation headers to REST endpoints"

// Monitor usage and plan sunset
// Checkpoint: REST deprecated

Scenario 3: Framework Upgrade

Upgrading a large application from Next.js 13 to 14:

// Strategic checkpoint placement
checkpoints = [
  "Pre-upgrade: All tests passing",
  "Dependencies updated",
  "App directory migration started",
  "Pages converted to app router",
  "Middleware updated",
  "Build successful",
  "Tests updated and passing",
  "Performance benchmarks complete"
]

// Each checkpoint represents a stable, revertable state

Checkpoint Management Tips

1. Checkpoint Hygiene

Caution

Storage Consideration: While checkpoints are lightweight, they do consume disk space. Cursor automatically cleans old checkpoints, but be mindful during large refactoring sessions.

Good practices:

• Create checkpoints at logical boundaries
• Use descriptive checkpoint messages
• Don’t rely on checkpoints for long-term storage (use Git)

2. Checkpoint Navigation

Efficiently moving between checkpoints:

// View checkpoint history
"Show me all checkpoints from this session"

// Restore specific checkpoint
"Restore to checkpoint: 'Auth system working'"

// Compare checkpoints
"What changed between 'REST API' and 'GraphQL API' checkpoints?"

3. Team Coordination

When working with a team:

• Communicate when using experimental checkpoints
• Commit to Git before extensive checkpoint-based experimentation
• Share successful experiment results via Git branches

Performance Considerations

Checkpoint Performance Impact

Operation	Time	Disk Usage
Create checkpoint	under 100ms	~Size of changed files
Restore checkpoint	under 500ms	No additional
List checkpoints	under 50ms	No additional
Auto-cleanup	Background	Frees space

Optimizing Checkpoint Usage

For large codebases:

1. Selective Checkpointing

   // Instead of checkpointing entire project
   "Create checkpoint for src/auth/* only"

2. Checkpoint Before Heavy Operations

   // Before operations that touch many files
   "Checkpoint, then update all import statements"

3. Regular Git Commits

   • Reduces checkpoint storage needs
   • Provides permanent history
   • Enables team collaboration

Troubleshooting Checkpoint Issues

Common Issues and Solutions

Checkpoint Not Available

Issue: Can’t restore to an old checkpoint Solution: Checkpoints expire. Use Git for permanent history

Restore Conflicts

Issue: Restoration fails due to conflicts Solution: Commit current changes first, then restore

Performance Degradation

Issue: Checkpoints slowing down Cursor Solution: Restart Cursor to trigger cleanup

Integration with Development Workflow

The Checkpoint-First Development Cycle

graph TD A[Plan Feature] --> B[Create Base Checkpoint] B --> C[Implement with Agent] C --> D{Happy with Result?} D -->|No| E[Restore Checkpoint] E --> F[Adjust Approach] F --> C D -->|Yes| G[Create Success Checkpoint] G --> H[Test Thoroughly] H --> I{Tests Pass?} I -->|No| J[Fix Issues] J --> H I -->|Yes| K[Git Commit] K --> L[Next Feature]

Checkpoints in Code Review

Use checkpoints during code review implementation:

1. Checkpoint before addressing feedback
2. Try reviewer’s suggestions
3. If suggestion doesn’t work, restore and try alternative
4. Checkpoint successful improvements
5. Final Git commit with all improvements

Best Practices Summary

1. Use checkpoints liberally during development - They’re cheap and fast

2. Create semantic boundaries - Checkpoint at meaningful points, not randomly

3. Combine with Git intelligently - Checkpoints for exploration, Git for preservation

4. Leverage for learning - Try multiple approaches to find the best solution

5. Clean up regularly - Let Cursor manage checkpoint lifecycle automatically

Next Steps

Now that you’ve mastered checkpoints:

1. Practice the Experimental Branch Pattern on your next feature
2. Try Parallel Development for your next architectural decision
3. Move on to Custom MCP Servers to extend Cursor’s capabilities

Remember: Checkpoints make you fearless. Use them to explore boldly, fail fast, and find optimal solutions without risk. The best developers aren’t afraid to experiment—they just know how to do it safely.