25 practical tips for software developers to get the most out of ChatGPT

The evolution of AI tools like ChatGPT has created new opportunities for developers to enhance their programming productivity and workflow efficiency. Here are 25 key tips for leveraging AI in programming:

1. Break down tasks into small, well-defined jobs rather than complex instructions
2. Treat AI interactions like a rapid Slack conversation rather than delayed email exchanges
3. Build complex routines iteratively, starting simple and adding functionality gradually

4. Test all AI-generated code thoroughly before implementation
5. Use debugging tools to verify AI code behavior step-by-step
6. Keep AI coding assistance separate from your main IDE for better control

7. Selectively use portions of AI-generated code as needed
8. Avoid requesting proprietary or institution-specific code from AI
9. Provide context and examples to help AI understand your codebase

10. Focus AI requests on common programming patterns and library usage
11. Request even small code snippets if they save time
12. Provide feedback when AI code doesn’t work and request improvements

13. Cross-check results between different AI models
14. Leverage AI for writing CSS selectors
15. Use AI to generate regular expressions

16. Have AI test and explain regular expressions
17. Delegate complex loop logic to AI
18. Ask AI to analyze code problems

19. Request AI explanations of code functionality
20. Know when to abandon AI assistance and code manually
21. Use specific naming conventions to help AI understand intent

22. Review AI’s explanatory notes for additional insights
23. Return to AI for incremental help on existing code
24. Use AI to modernize deprecated code

25. Leverage AI when working with unfamiliar programming languages

Critical considerations: Legal and intellectual property implications must be evaluated when implementing AI-generated code in commercial projects.

• Companies should establish clear policies regarding AI code usage
• Focus AI assistance on common programming patterns rather than proprietary business logic
• Consider using AI primarily for internal tools and open-source projects to minimize ownership concerns

Looking ahead: While AI proves invaluable for accelerating development workflows, it functions best as a sophisticated programming assistant rather than a complete replacement for human developers, potentially doubling productivity when used strategically with proper validation and testing protocols.