Blog Details

Scenario:

You wrote a Python function, but it works slowly on large inputs or is hard to read. You want your AI assistant to refactor the code and suggest optimizations to make it cleaner, faster, and more maintainable.

Step 0: Define Your Goal

Example Python function (inefficient factorial using recursion for demonstration):

def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1)

Goal:

• Add input validation
• Improve readability
• Suggest performance improvements if applicable

Step 1: Craft the AI Prompt

Treat AI as a senior developer or mentor. Include:

1. Your current code
2. Request for refactoring and optimizations
3. Optional: maintain functionality and add explanations

Example Prompt:

Refactor the following Python function for readability, performance, and safety.
Add input validation, comments, and suggest any improvements.

Step 2: AI Output Example

def factorial(n: int) -> int:
    """
    Calculate the factorial of a non-negative integer n.
    """
    if n < 0:
        raise ValueError("Input must be non-negative")  # Input validation
    result = 1
    for i in range(2, n+1):
        result *= i  # Multiply each number up to n
    return result

Explanation from AI:

• Switched from recursion to iteration → avoids stack overflow for large n
• Added type hints and docstring → improves readability
• Input validation ensures safe usage

Step 3: Test & Compare

print(factorial(5))  # 120
print(factorial(0))  # 1
# print(factorial(-1))  # Raises ValueError

• Compare with your original function
• Observe improvements in safety, readability, and maintainability

Step 4: Mini Lab Challenges

1. Refactor your is_prime(n) function for clarity and efficiency.
2. Refactor a small automation script to reduce duplicate code and improve readability.
3. Ask AI to optimize a loop-heavy function for performance.
4. Challenge: refactor a function to include logging and edge case handling.

Step 5: Pro Tips

• Treat AI as a mentor, not just a code generator
• Ask AI to suggest alternatives and explain trade-offs
• Use refactoring to learn Python best practices
• Iteratively refine prompts: focus on readability, efficiency, maintainability

Lab Summary

• AI can act as a code mentor, suggesting cleaner and faster implementations.
• Refactoring prompts + clear instructions = improved code quality.
• Always test AI-suggested improvements to ensure correctness.
• Using AI for optimization helps you learn better coding practices and write production-ready code.