How the AI is Thinking

Structured Prompt: "Act as a senior Python developer with expertise in algorithm optimization. Write code to sort a list of integers in Python with the following requirements:

1. It should handle large datasets efficiently
2. Include error handling for invalid inputs
3. Add comments explaining your approach
4. Format your code according to PEP 8 standards"

AI's Restructured Thought Process: The role prompt activates my knowledge of professional software development practices. The numbered list creates a checklist of requirements that I must address systematically. I should prioritize optimization, handle edge cases, document my code, and follow style conventions - all hallmarks of senior-level code.

Result: A more sophisticated, production-ready implementation:

def optimized_sort(data):
    """
    Efficiently sort a list of integers with proper error handling.
    
    Args:
        data: List of integers to be sorted
        
    Returns:
        Sorted list of integers
        
    Raises:
        TypeError: If input contains non-integer values
        ValueError: If input is None
    """
    # Validate input
    if data is None:
        raise ValueError("Input cannot be None")
        
    # Check for non-integer values
    if not all(isinstance(item, int) for item in data):
        raise TypeError("All elements must be integers")
    
    # Use built-in sort for optimal performance
    # (Python's Timsort is highly efficient for large datasets)
    return sorted(data)

Practical Tips for Mastering Structured Prompting

Here are some actionable techniques to help you get the most out of Level 2 structured prompting:

• Start building a personal library of effective patterns

  • Save prompts that work well for specific tasks
  • Note which structures consistently produce better results

• Experiment with role-based prompts

  • "Act as a [professional role]" can dramatically improve domain-specific outputs
  • Try different roles for the same task to see how the responses change

• Use numbered lists for multi-part instructions

  • Breaking complex requests into numbered steps improves completion rate
  • The AI will often respond with similarly structured points

• Specify your desired output format explicitly

  • "Format your response as a table with columns for X, Y, and Z"
  • "Present this as a markdown list with nested sub-points"
  • "Write this in the style of a formal business memo"

• Establish constraints

  • Set word or character limits ("Keep this under 200 words")
  • Specify tone requirements ("Use a professional but friendly tone")
  • Define complexity level ("Explain this at a high school level")

• Learn pattern combinations

  • Role prompts + format specifications often work better together
  • Constraints + structure requests can dramatically improve relevance

Remember that structured prompting is about discovering and applying patterns that consistently yield better results. The more you experiment, the more effective your prompt toolkit will become.