Blog Details

Scenario:

You just wrote a Python function for your project, but you’re unsure if it’s efficient, readable, and bug-free. Instead of asking a human mentor, you bring in your AI assistant:

“Review my code and suggest improvements — readability, performance, and best practices.”

Step 1: Craft the AI Prompt

Treat the AI like a mentor or senior developer. Include:

1. Your code
2. What you want feedback on
3. Optional: suggestions for optimization or documentation

Example Prompt:

Here is my Python function:

def factorial(n):
    result = 1
    for i in range(2, n+1):
        result *= i
    return result

Please review it. Suggest improvements for readability, efficiency, and error handling. Include comments or sample improved code.

Step 2: AI Output Example

Feedback:

• Add input validation to handle negative numbers
• Include type hints and docstring
• Optionally use recursion or more Pythonic style

Improved Function Example:

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

Explanation:

• Added type hints and docstring → improves readability
• Added error handling → prevents invalid input
• Loop style kept for efficiency and clarity

Step 3: Test & Compare

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

• Compare your original code with AI-suggested improvements
• Notice the clarity, safety, and Pythonic practices

Step 4: Mini Lab Challenges

1. Submit a reverse_string(s) function to AI and ask for improvements.
2. Provide a longer script (e.g., CSV automation) and request efficiency improvements.
3. Ask AI to comment every line of your code like a teaching assistant.
4. Challenge: let AI suggest one alternative approach and explain trade-offs.

Step 5: Pro Tips

• Ask AI to act as a senior developer or mentor for more advanced feedback
• Request readability improvements, performance suggestions, or security checks
• Use AI to explain trade-offs between different approaches
• Combine AI suggestions with your judgment — don’t blindly copy

Lab Summary

• AI can be your instant code reviewer, giving feedback on readability, efficiency, and best practices
• Treat AI like a mentor: ask for explanations, suggestions, and alternative approaches
• Iteratively improve code: submit → review → modify → test
• Code review assistance speeds up learning and reduces bugs in your projects