Prompt Engineering for Developers: Get Better AI Results

AI coding assistants are used by 76% of developers (Stack Overflow, 2024). Good prompt engineering makes AI 3-5x more useful.

The CONTEXT-TASK-FORMAT Framework

CONTEXT: Tech stack, constraints, existing code
TASK: Specific and unambiguous request
FORMAT: Code language, style, structure

Code Generation Examples

// Bad prompt:
"Make a user registration form"

// Good prompt:
"Create a Laravel Livewire component for user registration with:
- Fields: name, email, password, password_confirmation
- Real-time validation using #[Validate] attributes
- Rate limiting (max 5 attempts per minute)
- After success, dispatch a UserRegistered event
- Use PHP 8.3 features (readonly properties, enums)
- Follow Laravel conventions"

Debugging Prompts

"I'm getting this error in Laravel 11:
SQLSTATE[23000]: Duplicate entry 'john@example.com'

This happens when a user submits the registration form twice quickly.
The form uses Livewire and submits via wire:submit.

Current code: [paste relevant code]

How can I prevent this race condition?"

Refactoring Prompts

"Refactor this controller following these principles:
1. Extract business logic into a Service class
2. Use Form Request for validation
3. Use Resource for API response
4. Add proper error handling
5. Keep controller thin (max 10 lines)

Current code: [paste code]"

Tips for Better Results

• Be specific — "PHP 8.3 with strict types" not just "PHP"
• Show examples — input/output examples for complex logic
• State constraints — "no external packages," "must work with SQLite"
• Iterate — refine output in follow-up prompts
• Verify — always review AI-generated code before committing

AI is a powerful pair-programming partner, but the developer is still the decision-maker.