How to Give LLMs Detailed Instructions for Production-Ready Code

Learn how to provide comprehensive instructions to LLMs so they generate sustainable, testable, and production-ready code instead of just the bare minimum.

Here's a truth that most developers learn the hard way: LLMs are like really smart interns. They can do amazing things, but they need detailed instructions to do them right. If you just say "build me a user authentication system," you'll get something that works—but it probably won't be production-ready, testable, or maintainable.

The difference between a good LLM prompt and a great one is the difference between code that works today and code that works for years to come. Let me show you how to give LLMs the detailed instructions they need to generate sustainable, production-ready code.

The LLM Intern Analogy

Think of an LLM like a brilliant intern who's eager to help but doesn't know your company's standards, processes, or best practices. If you tell them "create a login form," they'll build something that technically works, but it might not follow your security standards, testing protocols, or deployment processes.

But if you give them detailed instructions about your requirements, standards, and processes, they'll deliver exactly what you need. The same principle applies to LLMs.

What Happens When You Don't Give Detailed Instructions

Let me show you the difference between a basic prompt and a detailed one:

❌ Basic Prompt (What You'll Get)

"Create a user authentication system for my React app"

Result: Basic login/logout functionality with minimal security, no tests, no error handling, no database optimization, no deployment setup.

✅ Detailed Prompt (What You Should Get)

"Create a production-ready user authentication system for my React app with the following requirements:

## Security Requirements
- Password hashing with bcrypt (12 salt rounds)
- JWT tokens with 24-hour expiration
- Rate limiting (max 5 login attempts per hour)
- Input validation and sanitization
- CSRF protection
- Secure HTTP-only cookies

## Database Requirements
- PostgreSQL with proper indexing on email and user_id
- User table with email, password_hash, created_at, updated_at
- Password reset tokens table with expiration
- Database migrations for version control

## Testing Requirements
- Unit tests for all authentication functions
- Integration tests for login/register flows
- E2E tests for complete user journey
- Test coverage minimum 80%

## Code Quality Requirements
- TypeScript with strict mode
- ESLint and Prettier configuration
- Error handling with proper logging
- Input validation with Zod or Joi
- Environment variable management

## Deployment Requirements
- Docker containerization
- GitHub Actions CI/CD pipeline
- Environment-specific configurations
- Health check endpoints
- Monitoring and logging setup

## Documentation Requirements
- API documentation with OpenAPI/Swagger
- README with setup instructions
- Code comments for complex logic
- Deployment guide

Please provide the complete implementation with all files, tests, and deployment configuration."

Result: Production-ready system with security, testing, deployment, and documentation.

The Detailed Instruction Framework

Here's my proven framework for giving LLMs detailed instructions that result in production-ready code:

📋 Detailed Instruction Template

# [Feature Name] - Detailed Requirements

## 🎯 Objective
[Clear description of what you want to build]

## 🏗️ Architecture Requirements
- Technology stack and versions
- Database design and relationships
- API structure and endpoints
- Frontend/backend separation

## 🔒 Security Requirements
- Authentication and authorization
- Data validation and sanitization
- Rate limiting and protection
- Environment variable management

## 🧪 Testing Requirements
- Unit test coverage percentage
- Integration test scenarios
- E2E test requirements
- Test data and mocking

## 📊 Database Requirements
- Schema design and relationships
- Indexing strategy
- Migration management
- Performance considerations

## 🚀 Deployment Requirements
- Containerization (Docker)
- CI/CD pipeline setup
- Environment configurations
- Monitoring and logging

## 📝 Code Quality Requirements
- Coding standards and linting
- Error handling patterns
- Documentation standards
- Performance benchmarks

## 📚 Documentation Requirements
- API documentation
- Setup and deployment guides
- Code comments and README
- Troubleshooting guides

## 🔄 Maintenance Requirements
- Update and upgrade procedures
- Backup and recovery
- Monitoring and alerting
- Performance optimization

Key Areas Where Detailed Instructions Matter

1. Security Requirements

LLMs won't automatically implement security best practices unless you tell them to. Be specific about:

• Password hashing algorithms and salt rounds
• Token expiration times and refresh strategies
• Rate limiting thresholds and time windows
• Input validation and sanitization requirements
• CORS and CSRF protection
• Environment variable security

🔒 Security Instruction Example

## Security Requirements
- Use bcrypt with 12 salt rounds for password hashing
- JWT tokens with 24-hour expiration and refresh tokens
- Rate limiting: 5 login attempts per hour per IP
- Input validation using Zod with strict schemas
- CORS configuration for specific domains only
- Environment variables for all secrets and API keys
- HTTPS-only cookies with httpOnly and secure flags
- SQL injection prevention with parameterized queries

2. Testing Requirements

LLMs will write functional code, but they need explicit instructions to include comprehensive testing:

• Unit test coverage percentage
• Integration test scenarios
• E2E test requirements
• Test data and mocking strategies
• Performance testing requirements
• Security testing (penetration tests)

🧪 Testing Instruction Example

## Testing Requirements
- Unit tests with minimum 80% code coverage
- Integration tests for all API endpoints
- E2E tests for complete user workflows
- Mock external services and APIs
- Test database with separate schema
- Performance tests for critical endpoints
- Security tests for authentication flows
- Test environment configuration files

3. Database Optimization

LLMs will create basic database schemas, but they need guidance for production optimization:

• Proper indexing strategies
• Database migration management
• Connection pooling configuration
• Query optimization requirements
• Backup and recovery procedures
• Performance monitoring

📊 Database Instruction Example

## Database Requirements
- PostgreSQL with connection pooling (max 20 connections)
- Indexes on email, user_id, and created_at columns
- Database migrations with version control
- Query optimization with EXPLAIN analysis
- Backup strategy with daily automated backups
- Performance monitoring with slow query logging
- Separate test database with identical schema
- Environment-specific connection configurations

4. Deployment and CI/CD

LLMs won't automatically set up deployment pipelines unless you ask for them:

• Docker containerization
• GitHub Actions or other CI/CD tools
• Environment-specific configurations
• Health checks and monitoring
• Rollback procedures
• Infrastructure as code

🚀 Deployment Instruction Example

## Deployment Requirements
- Docker containerization with multi-stage builds
- GitHub Actions CI/CD pipeline with automated testing
- Environment-specific configurations (dev/staging/prod)
- Health check endpoints for monitoring
- Automated deployment with rollback capability
- Infrastructure as code using Terraform or Pulumi
- Monitoring with Prometheus and Grafana
- Log aggregation with ELK stack or similar

Real Example: Building a Complete Feature

Let me show you how this works in practice. Here's a detailed prompt I used to build a complete e-commerce feature:

🛒 E-commerce Shopping Cart - Detailed Prompt

# E-commerce Shopping Cart System - Production Ready

## 🎯 Objective
Build a complete shopping cart system for an e-commerce platform with real-time updates, 
persistent storage, and checkout integration.

## 🏗️ Architecture Requirements
- React frontend with TypeScript
- Node.js/Express backend with TypeScript
- PostgreSQL database with Redis for caching
- WebSocket for real-time cart updates
- RESTful API with OpenAPI documentation

## 🔒 Security Requirements
- User authentication required for cart persistence
- CSRF protection for all cart operations
- Rate limiting: 100 cart operations per minute per user
- Input validation for all product IDs and quantities
- SQL injection prevention with parameterized queries
- XSS protection for product data display

## 🧪 Testing Requirements
- Unit tests for all cart operations (add, remove, update)
- Integration tests for API endpoints
- E2E tests for complete checkout flow
- Performance tests for cart with 1000+ items
- Security tests for cart manipulation attempts
- Test coverage minimum 85%

## 📊 Database Requirements
- Cart table with user_id, product_id, quantity, created_at
- Product table with inventory tracking
- Database indexes on user_id, product_id, and created_at
- Redis cache for frequently accessed cart data
- Database migrations with rollback capability
- Connection pooling with max 50 connections

## 🚀 Deployment Requirements
- Docker containers for frontend, backend, and database
- GitHub Actions pipeline with automated testing
- Environment variables for all configurations
- Health checks for all services
- Monitoring with Prometheus metrics
- Log aggregation with structured logging

## 📝 Code Quality Requirements
- TypeScript strict mode enabled
- ESLint with Airbnb configuration
- Prettier for code formatting
- Error handling with proper logging
- Input validation with Zod schemas
- Performance optimization for large carts

## 📚 Documentation Requirements
- OpenAPI/Swagger documentation for all endpoints
- README with setup and deployment instructions
- Code comments for complex business logic
- API usage examples and error responses
- Troubleshooting guide for common issues

## 🔄 Maintenance Requirements
- Automated database backups
- Cart cleanup for abandoned carts (30 days)
- Performance monitoring and alerting
- Regular security updates and dependency management
- Capacity planning for peak shopping periods

Please provide the complete implementation including all files, tests, deployment 
configuration, and documentation.

Pro Tips for Detailed Instructions

💡 Detailed Instruction Best Practices

Be specific about versions: "Use React 18 with TypeScript 5.0" not just "React"
Include performance requirements: "Handle 1000 concurrent users" or "Response time under 200ms"
Specify error handling: "Implement proper error logging and user-friendly error messages"
Define success criteria: "The system should handle X users with Y performance"
Include edge cases: "Handle network failures, invalid data, and concurrent modifications"
Specify maintenance requirements: "Include automated backups and monitoring"
Define testing scope: "Unit tests for all functions, integration tests for all endpoints"
Include documentation requirements: "API documentation, setup guides, troubleshooting"

When to Use Detailed vs. Simple Instructions

Use Detailed Instructions For:

• Production systems that will be maintained long-term
• Features that handle sensitive data or user information
• Systems that need to scale or handle high traffic
• Code that will be used by other developers
• Features that are critical to your business
• Learning new technologies or best practices

Simple Instructions Are Fine For:

• Quick prototypes and proof-of-concepts
• Personal projects and experiments
• Learning exercises and tutorials
• Temporary or disposable code
• When you're just exploring ideas

Iterative Refinement

Don't expect perfect results from the first prompt. Use an iterative approach:

Start with detailed requirements - Give comprehensive instructions
Review the output - Check if it meets your requirements
Ask for specific improvements - "Add error handling for X" or "Include tests for Y"
Refine and iterate - Keep improving until you're satisfied
Document what works - Save successful prompts for future use

Measuring Success

How do you know if your detailed instructions are working? Look for these signs:

• Code includes comprehensive error handling
• Tests are included and comprehensive
• Security best practices are implemented
• Documentation is complete and clear
• Deployment configuration is included
• Performance considerations are addressed
• Code follows best practices and standards

Getting Started

Ready to start giving LLMs better instructions? Here's how to begin:

🚀 Quick Start Guide

Pick a feature: Choose something you want to build
Use the template: Copy the detailed instruction template above
Customize for your needs: Add your specific requirements
Be specific about quality: Include testing, security, and deployment
Iterate and improve: Refine based on the results
Document success: Save working prompts for reuse

The Bottom Line

LLMs are incredibly powerful tools, but they need detailed instructions to produce production-ready code. Think of them as brilliant interns who need to understand your company's standards, processes, and requirements.

By providing comprehensive instructions, you'll get code that's not just functional but sustainable, secure, testable, and maintainable. The extra time you spend on detailed prompts will save you hours (or days) of refactoring and debugging later.

Start with one feature. Use the template, be specific about your requirements, and see the difference detailed instructions make. You'll be amazed at how much better the results are when you give LLMs the context they need to succeed.

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