The ChatGPT Mistake That Kills Your Problem-Solving Skills

What this guide covers

After reading this, you’ll know how to use ChatGPT to boost your work without weakening your core problem-solving and coding skills. You’ll learn to balance AI brainstorming with hands-on building and validation.

When to use it

• When you catch yourself copying ChatGPT-generated code blindly instead of understanding it.
• Debugging an issue that ChatGPT suggests fixes for—use AI’s hint but verify locally.
• Preparing for a tech task where you want AI ideas but need to write and test the solution yourself.
• Learning a new library or tool, using ChatGPT as a reference, not a shortcut.

The move, step by step

1. Ask ChatGPT to brainstorm solutions or explain concepts
   Example: “What are common causes of timeout errors in AWS Lambda?” Use this for ideas, not ready-to-run code.

2. Write the core logic yourself without copy-pasting ChatGPT’s code
   Apply the concepts discussed and type out your own implementation in your editor or IDE.

3. Compare your code with ChatGPT’s example
   Look for gaps or optimizations you missed, but don’t copy it wholesale. Use the AI example to refine your approach.

4. Run your code and debug any issues manually
   Use logs, breakpoints, or monitoring tools to trace the problem. Don’t rely on ChatGPT to fix the bug for you.

5. If stuck, ask ChatGPT targeted questions about error messages or alternative strategies
   Example: “Why would AWS SDK v3 return ‘AccessDeniedException’ for this IAM role?” Break problems down.

6. Document what you learned and how you solved the problem
   This cements your understanding far more than just reading AI outputs.

Example

Input: You want a function to fetch data from an API with retry logic.

Ask ChatGPT:

“How to implement retry logic in Python requests?”

You write:

import requests
import time

def fetch_with_retry(url, retries=3, delay=2):
    for i in range(retries):
        try:
            response = requests.get(url)
            response.raise_for_status()
            return response.json()
        except requests.RequestException as e:
            print(f"Attempt {i+1} failed: {e}")
            time.sleep(delay)
    raise Exception("All retries failed")

Run and test locally with different URLs. If errors happen, debug. Then glance at ChatGPT’s code snippet. Notice differences, refine your code if necessary—but never just copy it.

Common mistakes

• Mistake: Blindly pasting ChatGPT code → Fix: Write the code yourself first, then reference AI for improvements.
• Mistake: Using AI to solve bugs without hands-on debugging → Fix: Run and debug yourself before asking AI follow-ups.
• Mistake: Treating ChatGPT as a replacement for learning → Fix: Use AI as an assistant to complement your coding practice.
• Mistake: Skipping documentation of solutions → Fix: Write notes or comments about what you learned each time.
• Mistake: Over-relying on AI for every small task → Fix: Reserve ChatGPT for ideation and research, build actual solutions by hand.

Next step

Pick a simple bug or feature in your current project. Use ChatGPT to brainstorm the fix or approach, then build the solution yourself. Test it fully before consulting AI again. Then come back and try the next move from the video.