Code debugging with ChatGPT: Tutorial

How many hours have you lost looking at a screen full of errors that you don’t understand? A 2025 Stack Overflow study reveals that developers spend 39% of their time on average Debug codebut who use ChatGPT to depuration They reduce that time up to 68%. in 2025, debug with ia It’s not a luxury: it’s the fastest and most effective way to find bugs, understand why your algorithm fails, and write clean code from the first try. This step-by-step tutorial makes you a ninja of the ChatGPT debugging, whether you are a junior or a senior.

Why ChatGPT is the best debugger you’ll ever have

ChatGPT (especially GPT-4O and GPT-5) Understands context, good practices, and more than 50 languages. It detects logical errors that the linters do not see, explains exceptions in human language and suggests solutions with ready-to-copy examples. According to GitHub, developers who use AI to depuration make 47% fewer recurring mistakes.

Prompt Debug Master (Copy it and always use it)

text

Eres un ingeniero senior de software especializado en depuración.
Lenguaje: [Python / JavaScript / Java / etc.]
Código problemático:
[Pega aquí tu código completo]
Error que obtengo:
[Pega el traceback o mensaje exacto]
Qué intento conseguir:
[Explica en 1-2 frases el objetivo]
Pasos que quiero:
1. Explica el error línea por línea
2. Señala el bug principal y por qué ocurre
3. Ofrece 3 soluciones (la más simple primero)
4. Da el código corregido y limpio
5. Sugiere tests para evitar que vuelva a pasar

With this problem, the ChatGPT debugging It goes from 45 minutes to 45 seconds.

The 15 most effective prompts to debug code

1. “This infinite loop in Python is driving me crazy, here is the code and the error.”
2. “My recursive function gives stack overflow, optimize it and explain the problem to me.”
3. “The REST API returns 500, check this FastAPI driver.”
4. “This JavaScript code does not update the DOM, tell me why and correct it.”
5. “My Scikit-Learn da Accuracy 0 model, here is the full pipeline.”
6. “Explain this NullPointerException in Java line by line.”
7. “The code works locally but fails in production, what can it be?”
8. “Do complete code review of this 200-line script and point to all the bugs.”
9. ‘Turns this TensorFlow cryptic error into explanation for humans.’
10. “My regex does not capture what I want, here is the pattern and examples.”
11. “Async/await gives me unpredictable results, check this feature.”
12. “This potential SQL injection is in my code, fix it without breaking anything.”
13. “My Pandas DataFrame has Memory Leak, optimize this loop.”
14. ‘The test fails only in CI/CD, not locally. Why?’
15. “Turn this spaghetti code into clean and testable code.”

Step-by-step tutorial: Real debugging with ChatGPT

Case 1 – Common Error in Python (Beginner)

Problematic code:

Python

def dividir(a, b):
    return a / b

numeros = [10, 5, 0, 2]
for n in numeros:
    print(dividir(100, n))

Error: ZerodivisionError

Prompt Used: ‘Debug this Python code that gives ZerodivisionError. I want it to work even if there are zeros.’

ChatGPT response in 6 seconds:

• Clear explanation of the error
• 3 solutions (TRY/EXCEPT, FILTER, LIST COMPREHENSION)
• Clean final code with elegant error handling
• Suggested unit test

Case 2 – Logic Bug in JavaScript (Intermediate)

Code that does not update counter in React:

Javascript

const [count, setCount] = useState(0);
const incrementar = () => {
    setCount(count + 1);
    setCount(count + 1);
};

ChatGPT debugging Explains the Stale State, offers useeffect and reducer as solutions, and gives correct code with UseCallback.

Case 3 – Advanced Optimization (Senior)

A Deep Learning model trains slow. You paste the code + metrics. ChatGPT Detects gradient clipping absent, mixed precision and inefficient data loader. Solution: Reduce time from 4 h to 38 min.

Advanced tricks for professional debugging

• Use Code Interpreter (Plus): Paste the code and run it inside ChatGPT, see the error live.
• Ask for “Rubber Duck Debugging”: Explain your line by line code and ChatGPT asks you questions until you see the bug yourself.
• Create a “Senior Debugger” custom GPT with your stack (Fastapi + React + Docker).
• Always ask for “explain as a junior” or “like an architect” according to your level.
• When the bug is weird: “This error only happens in production with 1000 simultaneous users, hypotheses and how to investigate it.”

Complementary tools 2025

• cursor.sh: Editor debugging with GPT-5 in real time.
• GitHub CoPilot X: Suggestions + Explanation of errors.
• PyCharm + ChatGPT plugin: IDE built-in debugging.
• SourceGraph Cody: Look for bugs in the entire repository.

Comparison of debugging methods

The ChatGPT debugging It is, in 2025, the ability that separates good developers from excellent ones. Start today with the Master Prompt and you will see how your debugging sessions go from hell to a walk.

Sources consulted

• Stack Overflow Developer Survey 2025
• GitHub – State of the Octoverse 2025 → https://octoverse.github.com
• Xataka – How to debug code with ChatGPT as a Pro → https://www.xataka.com/basics/depurar-code-chatgpt
• Real Python – Debugging with ChatGpt Tutorial → https://realpython.com/debugging-with-chatgpt/
• FreeCodeCamp – How to Use ChatGpt to Debug Your Code
• Pycon Spain 2025 – Workshop “Purification with AI Generation”