AI Code Generation Prompt Formula

Goal + Context + Tech Stack + Inputs/Outputs + Constraints + Standards + Security + Tests. 1. Start by clearly defining exactly what you want the AI to build. 2. Specify your programming language, framework, database, and libraries. 3. Give the AI enough project context to understand where the code fits. 4. Define the expected inputs and outputs with real examples. 5. Add constraints like security, scalability, and error handling. 6. Tell the AI which coding standards and architecture principles to follow. 7. Ask for clean architecture, modular design, and clear comments. 8. Request unit tests, integration tests, and important edge-case tests. 9. Specify the exact output format you want before code generation begins. 10. For new code, describe the feature, stack, authentication, validation, and tests. 11. For debugging, share the code and ask AI to identify the root cause first. 12. Ask AI to explain the bug before rewriting or fixing the code. 13. For refactoring, define whether you want better performance, readability, or scalability. 14. When adding features, tell AI to preserve existing functionality and tests. 15. Never skip input validation and output sanitization in production code. 16. Explicitly ask for protection against relevant risks like SQL injection, XSS, and CSRF. 17. Ask for secure authentication, proper error handling, and safe data handling. 18. Build complex applications feature by feature instead of requesting everything at once. 19. Ask AI to analyze requirements, identify risks, and create an implementation plan before coding.