Cursor AI IDE: The Future of Coding or Just Hype? 30-Day Production Review

Everyone’s talking about Cursor. “AI-first IDE that will replace VS Code.” I was skeptical. Used it exclusively for 30 days on real projects.

Results: 40% productivity boost, but it’s not perfect. Here’s the honest review.

What is Cursor?

Cursor is a fork of VS Code with AI deeply integrated:

GPT-4 powered code completion
AI chat in the IDE
Codebase-aware suggestions
Natural language edits
Auto-bug fixing

Installation

# Download from cursor.sh
# Or use homebrew
brew install --cask cursor

Import VS Code settings:

Cursor > Settings > Import VS Code Settings

All your extensions, keybindings, and settings transfer!

Key Features

1. Tab Completion (Copilot++):

More context-aware than GitHub Copilot:

# Type: def calculate_
# Cursor suggests:
def calculate_monthly_revenue(transactions: List[Transaction]) -> float:
    """Calculate total monthly revenue from transactions."""
    return sum(t.amount for t in transactions if t.type == 'sale')

It understands your codebase context!

2. CMD+K (Natural Language Edits):

Select code, press CMD+K, describe changes:

# Original code
def process_data(data):
    result = []
    for item in data:
        result.append(item.upper())
    return result

# CMD+K: "make this more pythonic and add type hints"
# Cursor rewrites to:

def process_data(data: List[str]) -> List[str]:
    """Process data by converting to uppercase."""
    return [item.upper() for item in data]

3. CMD+L (AI Chat):

Chat with AI about your code:

Me: How can I optimize this database query?

Cursor: I see you're using N+1 queries. Here's an optimized version using select_related:

[Shows optimized code with explanation]

4. Codebase Indexing:

Cursor indexes your entire codebase:

Me: Where is the user authentication logic?

Cursor: User authentication is in:
1. auth/views.py - login/logout views
2. auth/middleware.py - JWT validation
3. auth/models.py - User model

[Shows relevant code snippets]

Real-World Usage

Task 1: Add New API Endpoint

Traditional approach (VS Code + Copilot): 30 minutes

With Cursor:

CMD+L: “Add a new endpoint to get user statistics”
Cursor generates:
- Route definition
- View function
- Serializer
- Tests
- Documentation

Time: 8 minutes (73% faster)

Task 2: Refactor Legacy Code

# Legacy code (200 lines, messy)
def process_order(order_id):
    # ... 200 lines of spaghetti code
    pass

# CMD+K: "refactor this into smaller functions with proper error handling"
# Cursor breaks it into:

def validate_order(order_id: str) -> Order:
    """Validate order exists and is processable."""
    # ...

def calculate_total(order: Order) -> Decimal:
    """Calculate order total with tax and shipping."""
    # ...

def process_payment(order: Order) -> Payment:
    """Process payment for order."""
    # ...

def process_order(order_id: str) -> OrderResult:
    """Process order end-to-end."""
    order = validate_order(order_id)
    total = calculate_total(order)
    payment = process_payment(order)
    return OrderResult(order, payment)

Time saved: 2 hours

Task 3: Write Tests

# Select function, CMD+K: "write comprehensive tests"

import pytest
from decimal import Decimal

def test_calculate_total_basic():
    order = Order(items=[Item(price=Decimal('10.00'))])
    assert calculate_total(order) == Decimal('10.00')

def test_calculate_total_with_tax():
    order = Order(
        items=[Item(price=Decimal('100.00'))],
        tax_rate=Decimal('0.1')
    )
    assert calculate_total(order) == Decimal('110.00')

def test_calculate_total_with_shipping():
    order = Order(
        items=[Item(price=Decimal('50.00'))],
        shipping=Decimal('5.00')
    )
    assert calculate_total(order) == Decimal('55.00')

# ... 10 more test cases

Generated comprehensive tests in 2 minutes!

Productivity Metrics

Tracked for 30 days:

Task	Before (VS Code)	After (Cursor)	Improvement
New feature	4 hours	2.5 hours	37%
Bug fix	45 min	25 min	44%
Refactoring	2 hours	1 hour	50%
Writing tests	1 hour	20 min	67%
Documentation	30 min	10 min	67%

Average productivity increase: 40%

Comparison with GitHub Copilot

Feature	Cursor	GitHub Copilot	Winner
Code completion	Excellent	Excellent	Tie
Context awareness	Excellent	Good	Cursor
Natural language edits	Yes	No	Cursor
AI chat	Yes	Limited	Cursor
Codebase understanding	Yes	No	Cursor
Speed	Fast	Faster	Copilot
Price	$20/mo	$10/mo	Copilot

Limitations

1. Hallucinations:

Sometimes suggests non-existent APIs:

# Cursor suggested:
user.get_premium_features()  # This method doesn't exist!

# Had to verify and fix

2. Over-reliance Risk:

Easy to accept suggestions without understanding:

# Accepted this without reading:
def complex_algorithm(data):
    # ... 50 lines of code
    # Contains a subtle bug!

Always review AI-generated code!

3. Privacy Concerns:

Cursor sends code to OpenAI. Not suitable for:

Proprietary algorithms
Sensitive data
Regulated industries

Use .cursorignore:

# .cursorignore
secrets/
config/production.py
*.key
*.pem

4. Cost:

$20/month per developer. For a team of 10: $200/month

But if it saves 40% time, ROI is huge.

Best Practices

1. Review all suggestions:

# Don't blindly accept
# Read and understand the code
# Test thoroughly

2. Use for boilerplate:

# Great for:
- CRUD operations
- API endpoints
- Test cases
- Documentation

# Be careful with:
- Complex algorithms
- Security-critical code
- Performance-sensitive code

3. Combine with traditional tools:

# Use Cursor for:
- Initial implementation
- Refactoring
- Tests

# Use traditional debugging for:
- Complex bugs
- Performance issues
- System-level problems

Configuration

Optimize Cursor settings:

{
  "cursor.ai.model": "gpt-4",
  "cursor.ai.maxTokens": 4000,
  "cursor.ai.temperature": 0.2,
  "cursor.ai.codebaseIndexing": true,
  "cursor.ai.autoSuggest": true,
  "cursor.ai.privacyMode": false
}

Real Project: REST API

Built a complete REST API in 4 hours (normally 12 hours):

# CMD+L: "Create a REST API for a blog with posts, comments, and users"

# Cursor generated:
# 1. Models (models.py)
class User(models.Model):
    username = models.CharField(max_length=100, unique=True)
    email = models.EmailField(unique=True)
    created_at = models.DateTimeField(auto_now_add=True)

class Post(models.Model):
    title = models.CharField(max_length=200)
    content = models.TextField()
    author = models.ForeignKey(User, on_delete=models.CASCADE)
    created_at = models.DateTimeField(auto_now_add=True)

class Comment(models.Model):
    post = models.ForeignKey(Post, on_delete=models.CASCADE)
    author = models.ForeignKey(User, on_delete=models.CASCADE)
    content = models.TextField()
    created_at = models.DateTimeField(auto_now_add=True)

# 2. Serializers (serializers.py)
# 3. Views (views.py)
# 4. URLs (urls.py)
# 5. Tests (tests.py)
# 6. Documentation (README.md)

All generated, I just reviewed and tweaked!

Team Adoption

Rolled out to 5-person team:

Week 1: Skepticism

“This is just fancy autocomplete”
“I don’t trust AI code”

Week 2: Experimentation

“Okay, this is actually useful for tests”
“Saved me 2 hours on refactoring”

Week 4: Adoption

Everyone using it daily
Team velocity up 35%
Code review time down 20%

Cost-Benefit Analysis

Cost:

$20/month per developer
Team of 5: $100/month

Benefit:

40% productivity increase
Each developer saves ~16 hours/month
At $100/hour: $8,000/month value

ROI: 8000%

No-brainer for most teams.

Results

Before Cursor:

Average feature: 8 hours
Tests: Manual, time-consuming
Refactoring: Avoided due to time
Documentation: Often skipped

After Cursor:

Average feature: 5 hours (37% faster)
Tests: Auto-generated, comprehensive
Refactoring: Easy and quick
Documentation: Generated automatically

Team Impact:

Velocity: +35%
Code quality: +20%
Test coverage: 45% → 78%
Developer satisfaction: +50%

Lessons Learned

AI is a tool, not a replacement - Still need to understand code
Review everything - AI makes mistakes
Great for boilerplate - Saves tons of time
Privacy matters - Use .cursorignore
ROI is real - Worth the cost

Conclusion

Cursor is the real deal. Not hype. Genuinely increases productivity.

Is it perfect? No. Will it replace developers? No. Will it make you more productive? Absolutely.

Key takeaways:

40% productivity increase in real projects
Best for boilerplate and refactoring
Always review AI-generated code
ROI is massive ($100/month → $8000/month value)
Privacy concerns for sensitive code

Try Cursor. Give it 2 weeks. You won’t go back to regular VS Code.

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