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:
- Break down tasks into small, well-defined jobs rather than complex instructions
- Treat AI interactions like a rapid Slack conversation rather than delayed email exchanges
- Build complex routines iteratively, starting simple and adding functionality gradually
- Test all AI-generated code thoroughly before implementation
- Use debugging tools to verify AI code behavior step-by-step
- Keep AI coding assistance separate from your main IDE for better control
- Selectively use portions of AI-generated code as needed
- Avoid requesting proprietary or institution-specific code from AI
- Provide context and examples to help AI understand your codebase
- Focus AI requests on common programming patterns and library usage
- Request even small code snippets if they save time
- Provide feedback when AI code doesn’t work and request improvements
- Cross-check results between different AI models
- Leverage AI for writing CSS selectors
- Use AI to generate regular expressions
- Have AI test and explain regular expressions
- Delegate complex loop logic to AI
- Ask AI to analyze code problems
- Request AI explanations of code functionality
- Know when to abandon AI assistance and code manually
- Use specific naming conventions to help AI understand intent
- Review AI’s explanatory notes for additional insights
- Return to AI for incremental help on existing code
- Use AI to modernize deprecated code
- 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.
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