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10*10 LLM.Patterns / IDE-Focused / "Developer Reference"

#ai #promptengineering #productivity

The 10 Principles

1. Structure beats chat

Think pattern completion, not conversation.

2. Context is Currency

First 500 tokens matter most. Front-load intent, prune ruthlessly.

3. Constraints Create Clarity

Restrictions improve output quality. Boundaries prevent hallucination.

4. Scope Defines Success

Specify exact boundaries: function, class, or file-level changes only.

5. Validation Enables Trust

Include success criteria. Model can self-evaluate against clear goals.

6. Tools Have Personalities

Each AI IDE has distinct strengths. Match task to tool personality.

7. Progressive Disclosure Wins

Break complex tasks into phases. Build incrementally, maintain context.

8. Anti-Patterns Kill Performance

Avoid: vague requests, mixed tasks, conversational tone, scope creep.

9. State Anchoring Maintains Focus

Establish architectural context once, reference throughout session.

10. Measurement Drives Improvement

Track success rates, iterations, context efficiency. Optimize systematically.

The 10 Patterns

These patterns work because they align with how LLMs actually process information.

1. DIRECTIVE Block (Universal) 

# DIRECTIVE: [precise_action]
# SCOPE: [function|class|module]
# CONSTRAINTS: [hard_limits]
# OUTPUT: [format_spec]

[code_here]
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2. Surgical Refactor 

# DIRECTIVE: Extract validation logic to pure function
# SCOPE: METHOD → NEW_METHOD
# CONSTRAINTS: No side effects, preserve types
# OUTPUT: New method + updated caller

def process_user(email, password):
    if not email or "@" not in email:  # Extract this
        return False
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3. Context-Aware Generation 

# DIRECTIVE: Create async batch processor
# CONTEXT: User uploads, 2-5sec each, failure-prone
# CONSTRAINTS: Max 10 concurrent, graceful failures
# OUTPUT: Complete class with error handling

class BatchProcessor:
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4. Bug Fix Precision 

# DIRECTIVE: Fix race condition in counter
# SYMPTOMS: Incorrect count under load
# CONSTRAINTS: Thread-safe, no external deps
# OUTPUT: Fixed method only

def increment(self):
    self.count += 1  # RACE CONDITION
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5. Test Generation 

# DIRECTIVE: Generate pytest suite for payment processing
# CONSTRAINTS: Mock external calls, 95%+ coverage
# CONTEXT: Stripe integration, multiple failure modes
# OUTPUT: Complete test file

def process_payment(amount, token, user_id):
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6. Performance Optimization 

# DIRECTIVE: Optimize for 1000x/second calls
# PROFILE: Hot path, current bottleneck
# CONSTRAINTS: No premature optimization, measure results
# OUTPUT: Optimized code + benchmarks

def expensive_calculation(data):
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7. Progressive Implementation 

# DIRECTIVE: Phase 1 - Define interface
# SCOPE: ABSTRACT_CLASS
# OUTPUT: Contract only

# Follow with:
# DIRECTIVE: Phase 2 - Redis implementation
# SCOPE: CONCRETE_CLASS
# CONSTRAINTS: Inherit from above
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8. State Anchoring 

# STATE: FastAPI + SQLAlchemy + Redis architecture
# PATTERNS: Repository pattern, async/await
# CURRENT: User management system, deletion with cascade

# Use this context block throughout session
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9. Error Prevention 

# DIRECTIVE: Generate with paranoid error checking
# CONSTRAINTS: Validate all inputs, handle all exceptions
# MINDSET: Fail fast, clear error messages
# OUTPUT: Defensive code

def risky_operation(user_input):
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10. Documentation Generation 

# DIRECTIVE: Add comprehensive docstring
# CONSTRAINTS: Google style, include examples
# CONTEXT: Public API, complex parameters
# OUTPUT: Docstring only

def complex_function(param1, param2, **kwargs):
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The 12 AI IDE Tools

Tier 1: The Powerhouses

1. Cursor

The Surgical Strike Master

Cursor is recognized as the current frontrunner among AI coding assistants, with advanced features that power users particularly praise.

Personality: Loves precision, handles complex multi-file operations, excels at inline edits.

Sweet Spot: Refactoring, complex logic, cross-file consistency.

Pattern:

# Use @ for file references
# @models.py @controllers.py @types.py
# DIRECTIVE: Ensure User model matches UserController interface
# CONSTRAINTS: Type safety, no breaking changes
# Cursor excels at cross-file consistency
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Best For:

  • Complex refactoring across multiple files
  • Type-safe transformations
  • Architectural changes
  • Senior developers who want precision

2. Windsurf (Codeium)

The Context King

Windsurf is built for large, complex codebases, with deeper multi-file understanding, better team collaboration, and cross-IDE support.

Personality: Methodical, context-aware, team-oriented, handles large codebases.

Sweet Spot: Enterprise codebases, team collaboration, architectural understanding.

Pattern:

# DIRECTIVE: Implement user authentication flow
# CONTEXT: Microservices architecture, 50+ files
# CONSTRAINTS: Follow existing patterns, maintain team conventions
# OUTPUT: Complete implementation with team review comments
# Windsurf understands complex architectural relationships
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Best For:

  • Large enterprise applications
  • Team-based development
  • Complex domain logic
  • Architectural consistency

3. GitHub Copilot

The Pattern Matcher

Personality: Loves descriptive names, patterns, established conventions. Conservative but reliable.

Sweet Spot: Standard implementations, boilerplate, following established patterns.

Pattern:

# Loves: Descriptive names, type hints, docstrings
def calculate_user_subscription_renewal_date(
    user: User, 
    subscription: Subscription,
    billing_cycle: BillingCycle
) -> datetime:
    """Calculate the next renewal date based on billing cycle and user timezone."""
    # Copilot excels at implementing standard business logic
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Best For:

  • Standard CRUD operations
  • Following established patterns
  • Boilerplate generation
  • Developers learning new frameworks

Tier 2: The Specialists

4. JetBrains AI Assistant

The IDE Native

With the 2025.1 release, all JetBrains AI features are accessible for free in JetBrains IDEs, including unlimited code completion and local model support.

Personality: Deeply integrated, refactoring-focused, enterprise-grade.

Sweet Spot: IntelliJ ecosystem, Java/Kotlin, enterprise workflows.

Pattern:

// DIRECTIVE: Refactor to use dependency injection
// CONTEXT: Spring Boot application, existing @Service classes
// CONSTRAINTS: Maintain backward compatibility
// JetBrains AI understands Spring patterns deeply
class UserService @Autowired constructor(
    private val userRepository: UserRepository
)
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Best For:

  • Java/Kotlin enterprise applications
  • IntelliJ/WebStorm users
  • Refactoring-heavy workflows
  • Enterprise compliance requirements

5. Replit Agent

The Full-Stack Deployer

Replit Agent aims to make full-stack development "accessible to everyone" where new coders can describe an idea and the agent generates and deploys it.

Personality: Beginner-friendly, full-stack focused, deployment-ready.

Sweet Spot: Rapid prototyping, full-stack apps, beginner projects.

Pattern:

# DIRECTIVE: Create a todo app with user authentication
# CONTEXT: New developer, needs deployment
# CONSTRAINTS: Use popular frameworks, include deployment config
# OUTPUT: Complete app with hosting setup
# Replit Agent handles the entire stack
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Best For:

  • Rapid prototyping
  • Learning full-stack development
  • Quick MVPs
  • Deployment-included projects

6. v0 (Vercel)

The UI Wizard

v0 is Vercel's AI-powered UI generator for creating React components and Tailwind CSS styling through natural language prompts, excelling at quickly producing polished interfaces.

Personality: Design-focused, React-native, component-driven.

Sweet Spot: React components, UI/UX, Tailwind CSS, design systems.

Pattern:

// DIRECTIVE: Create a modern user profile card
// CONTEXT: React + Tailwind, dark mode support
// CONSTRAINTS: Accessible, mobile-first, loading states
// OUTPUT: Complete component with variants
// v0 excels at polished UI components
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Best For:

  • React component libraries
  • Design system development
  • UI/UX prototyping
  • Frontend-focused projects

7. Cline (VS Code Extension)

The Collaborative Assistant

Cline is an open source VS code alternative that works in your existing IDE and tries to be more collaborative than Cursor/Windsurf by asking more questions.

Personality: Conversational, question-asking, collaborative, open-source.

Sweet Spot: Exploratory development, learning, collaborative coding.

Pattern:

# DIRECTIVE: Implement caching layer
# CONTEXT: Existing Flask app, performance issues
# COLLABORATION: Ask questions about requirements
# OUTPUT: Implementation with explanations
# Cline will ask clarifying questions about cache strategy
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Best For:

  • Learning new technologies
  • Exploratory development
  • Open-source projects
  • Developers who prefer dialogue

Tier 3: The Emerging Force

8. Claude Code (Terminal)

The Terminal Virtuoso

Claude Code works in your terminal, with consensus being that it generates better code quality.

Personality: Terminal-native, high-quality output, command-line focused.

Sweet Spot: CLI tools, DevOps, system administration, terminal workflows.

Pattern:

# DIRECTIVE: Create deployment script for microservices
# CONTEXT: Docker containers, Kubernetes, CI/CD
# CONSTRAINTS: Error handling, logging, rollback capability
# OUTPUT: Production-ready bash script
# Claude Code excels at robust CLI tools
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Best For:

  • DevOps automation
  • CLI tool development
  • System administration
  • Terminal-first workflows

9. Bolt.new (StackBlitz)

The Instant Full-Stack

Bolt.new by Stackblitz can create full-stack web apps from a single prompt.

Personality: Instant gratification, full-stack, demo-ready.

Sweet Spot: Rapid prototyping, demos, proof of concepts.

Pattern:

// DIRECTIVE: E-commerce site with payment processing
// CONTEXT: Need demo for client meeting tomorrow
// CONSTRAINTS: Modern tech stack, mobile responsive
// OUTPUT: Complete app with sample data
// Bolt.new delivers full applications instantly
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Best For:

  • Client demos
  • Proof of concepts
  • Rapid prototyping
  • Time-constrained projects

10. Neovim Avante

The Vim Purist

Neovim Avante is a Neovim plugin that brings AI assistance to the terminal-based editor.

Personality: Keyboard-driven, lightweight, terminal-focused.

Sweet Spot: Vim users, terminal environments, minimal setups.

Pattern:

" DIRECTIVE: Optimize this function for performance
" CONTEXT: Hot path, called 1000x/second
" CONSTRAINTS: No external dependencies
" OUTPUT: Optimized code only
" Avante works within Neovim's modal editing paradigm
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Best For:

  • Vim/Neovim users
  • Terminal-only environments
  • Lightweight setups
  • Performance-critical code

11. Lovable

The Rapid MVP Builder

Personality: Speed-focused, MVP-oriented, business-logic aware.

Sweet Spot: Startup MVPs, rapid business logic implementation.

Pattern:

# DIRECTIVE: Build subscription billing system
# CONTEXT: SaaS startup, need MVP in 2 weeks
# CONSTRAINTS: Stripe integration, admin dashboard
# OUTPUT: Production-ready billing system
# Lovable focuses on business value over technical perfection
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Best For:

  • Startup MVPs
  • Business logic implementation
  • Time-to-market pressure
  • Non-technical founders

12. Same.dev

The Consistency Enforcer

Personality: Pattern-focused, consistency-driven, standard-enforcing.

Sweet Spot: Code standardization, pattern enforcement, team alignment.

Pattern:

# DIRECTIVE: Ensure all API endpoints follow team standards
# CONTEXT: Microservices, 5 developers, growing codebase
# CONSTRAINTS: OpenAPI spec, error handling patterns
# OUTPUT: Consistent implementation across services
# Same.dev enforces architectural consistency
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Best For:

  • Team standardization
  • Code consistency
  • Architectural patterns
  • Growing development teams

Universal Patterns for All Tools

The DIRECTIVE Block (Works Everywhere) 

# DIRECTIVE: [precise_action]
# SCOPE: [function|class|module|app]
# CONSTRAINTS: [hard_limits]
# OUTPUT: [format_spec]
# CONTEXT: [relevant_background]

[code_here]
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Tool Selection Matrix

Task Type Best Tool Second Choice Why
Complex Refactoring Cursor Windsurf Cross-file awareness
Enterprise Java JetBrains AI Cursor Native integration
React Components v0 Cursor Design-focused
Full-Stack MVP Replit Agent Bolt.new Deployment included
Terminal Tools Claude Code Neovim Avante CLI expertise
Team Consistency Windsurf Same.dev Architecture understanding
Learning/Exploration Cline Copilot Collaborative approach
Rapid Prototyping Bolt.new v0 Instant results

Context Optimization by Tool

Context-Heavy Tools (Windsurf, Cursor) 

# STATE: Full architectural context
# ARCHITECTURE: Microservices + Event Sourcing + CQRS
# PATTERNS: Repository pattern, DDD, Clean Architecture
# CURRENT: User management bounded context
# TASK: Add email verification workflow
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Pattern-Focused Tools (Copilot, JetBrains AI) 

# DIRECTIVE: Follow existing authentication pattern
# EXAMPLE: Similar to PasswordResetService class
# CONSTRAINTS: Use existing EmailService interface
# OUTPUT: New EmailVerificationService class
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Speed-Focused Tools (Bolt.new, Replit Agent) 

# DIRECTIVE: Create user dashboard
# REQUIREMENTS: Login, profile, settings, dark mode
# CONSTRAINTS: Modern UI, mobile responsive
# OUTPUT: Complete working application
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Advanced Strategies

Multi-Tool Workflows

  1. Architecture Phase: Windsurf for system design
  2. Implementation Phase: Cursor for complex logic
  3. UI Phase: v0 for components
  4. Deployment Phase: Replit Agent for hosting

Tool-Specific Anti-Patterns

Tool Anti-Pattern Why It Fails
Cursor Vague cross-file requests Overwrites too much
Windsurf Single-file focus Wastes context strength
Copilot Novel patterns Prefers established solutions
v0 Complex business logic UI-focused, not logic
Replit Agent Enterprise requirements Optimized for simplicity

Performance Monitoring

Track these metrics across tools:

  • First-attempt success rate
  • Context efficiency (useful output / tokens used)
  • Iteration cycles (how many back-and-forth exchanges)
  • Time to working solution

Quick Reference

When to Use Each Tool

  • Need surgical precision? → Cursor
  • Large, complex codebase? → Windsurf
  • Standard implementation? → Copilot
  • Java/Kotlin enterprise? → JetBrains AI
  • Full-stack MVP? → Replit Agent
  • React components? → v0
  • Learning/exploring? → Cline
  • Terminal tools? → Claude Code
  • Instant demo? → Bolt.new
  • Vim workflow? → Neovim Avante
  • Startup MVP? → Lovable
  • Team consistency? → Same.dev

The Golden Rules

  1. Match tool to task complexity
  2. Front-load your intent
  3. Specify exact scope
  4. Include success criteria
  5. Measure everything

This guide represents the current state of AI IDEs as of 2025. The landscape evolves rapidly - adapt these patterns as tools mature.

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