This guide outlines the optimal workflow for leveraging Claude AI across your development, documentation, and problem-solving tasks.
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Define Context
- Provide relevant code snippets, files, or project structure
- Share error messages or logs when troubleshooting
- Include any constraints (performance, memory, compatibility)
- Mention relevant frameworks, libraries, or environments
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Frame Your Request
- Be specific about the desired outcome
- Break complex tasks into manageable subtasks
- Include acceptance criteria for the solution
- Specify any style, pattern, or best practices to follow
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Problem Analysis
- Ask Claude to analyze the situation first
- Request explanations of complex issues before solutions
- Have Claude identify potential approaches
- Discuss tradeoffs between different solutions
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Implementation
- Start with high-level approaches
- Request incremental code solutions
- Ask for explanations of critical sections
- Test implementations against edge cases
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Refinement
- Request optimization for specific concerns
- Ask for alternative approaches
- Have Claude help with debugging issues
- Request simplification of complex solutions
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Documentation
- Ask for documentation in markdown format
- Request examples demonstrating usage
- Have Claude explain design decisions
- Generate comments for complex algorithms
- Be Specific: The more details you provide, the better Claude can assist
- Iterative Process: Build on previous messages for complex tasks
- Request Explanations: Ask "why" to understand Claude's reasoning
- Provide Feedback: Tell Claude what works or doesn't work
- Review Output: Always verify generated code before implementation
- Save Discussions: Keep solutions for future reference or training
- Code Generation: "Write a function that..."
- Debugging: "Help me fix this error..."
- Refactoring: "Improve this code by..."
- Learning: "Explain how this algorithm works..."
- Documentation: "Create documentation for..."
- Testing: "Generate test cases for..."