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Dhruv Joshi
Dhruv Joshi

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AI Coding Assistants for Beginners: How to Use ChatGPT & Copilot Without ‘Cheating’

#ai #chatgpt #githubcopilot #coding

Hey devs 👋

I’m Dhruv, a tech writer and developer who spends a lot of time helping beginners ship their first real-world projects.

If you’ve just started coding, you’ve probably asked yourself:

“If I use ChatGPT or GitHub Copilot… am I cheating?”

Short answer: you’re not cheating if you’re still learning, thinking, and taking responsibility for your code. You are cheating yourself if you stop doing those things.

In this post, I’ll show you how to use an AI coding assistant for beginners (like ChatGPT or Copilot) in a healthy way — more like a pair programmer than a shortcut machine.

1. Why AI feels like “cheating” (and why it doesn’t have to be)

When we learned to code, the rules sounded like this:

  • “Write every line yourself.”
  • “Don’t copy-paste solutions from the internet.”
  • “Real devs debug without help.” (Spoiler: they don’t.)

Now there’s an AI that can:

  • generate functions, tests, and docs
  • explain complex concepts in plain English
  • complete code as you type in your editor

It feels like someone is doing your homework.

But think of it this way:

  • Using Stack Overflow, documentation, and tutorials was always fine.
  • Pair programming with a senior dev was encouraged.
  • Using autocomplete, IntelliSense, or linters was normal.

AI is the next evolution of those tools. The key difference is how you use it:

  • If you paste a problem → copy a solution → never understand it → ✅ result, ❌ learning.
  • If you use it to explore, debug, and understand → ✅ result, ✅ learning.

That mindset shift is everything.

2. ChatGPT vs Copilot: what they’re actually good at

You’ll usually use these tools together, but for different kinds of tasks.

ChatGPT – your “explain, plan, and debug” partner

Use ChatGPT for:

  • Learning a new concept

“Explain JavaScript promises in simple terms with code examples.”

  • Planning features

“Help me break down a simple todo app in React into small tasks.”

  • Debugging & understanding errors

“Here’s my error and the code. Help me understand what’s going wrong, don’t just fix it.”

  • Refactoring & best practices

“Suggest improvements for readability and maintainability.”

  • Documentation & comments

“Generate a concise docstring for this function.”

GitHub Copilot – your “auto-complete on steroids”

Copilot works best when:

  • You already know roughly what to write.
  • You write a clear function name, comment, or signature, then let it suggest code.
  • You review every line and edit it like code a junior dev sent you.

Think of Copilot as a super-fast junior teammate:

  • It’s great at patterns, boilerplate, and repetitive code.
  • It’s bad at domain knowledge, edge cases, and long-term maintainability unless you guide it.

3. The pair-programming mindset: you are still the senior dev

Even if you’re a beginner, when you use AI, you are the “senior engineer in charge.”

That means:

  • You decide what the feature should do.
  • You verify whether the code makes sense.
  • You test the behavior, not just trust the output.
  • You keep learning the underlying concepts.

Here’s a simple mental model:

AI writes code. You write the spec. You own the result.

Before you ask AI for code, ask yourself:

  1. What am I trying to build?
    Describe it in one sentence.

  2. What do I already know about this?
    List any functions, APIs, or concepts you recognize.

  3. What exactly do I want help with?
    “Explain”, “suggest”, “debug”, “refactor”, not just “write everything for me.”

If you can’t do step 1, you’re not ready for AI yet — you’re ready for a tutorial.

4. Good habits vs bad habits with AI coding assistants

Good habits ✅

  • Ask “why”, not just “what”.

“Explain why this solution works step by step.”

  • Request smaller pieces.

“Write just the validation function for this input.”

  • Translate the answer back in your own words.
    If you can’t explain it, you don’t understand it yet.

  • Use AI to compare approaches.

“Show me two ways to do this and when to use each.”

  • Let AI review your code first. Write something, then ask:

“Review this for bugs, edge cases, and readability.”

Bad habits ❌

  • “Write the whole app for me.”
  • Copy-pasting code you don’t understand.
  • Skipping docs and relying only on AI.
  • Using AI to finish assignments you’re graded on (without permission).
  • Ignoring security, performance, and readability because “AI gave it, so it’s correct.”

Ask yourself honestly:

“If this AI disappeared tomorrow, would I still know how to solve this type of problem?”

If the answer is “no” every time, you’re leaning too hard on it.

5. A simple AI-first workflow for beginners

Let’s say you want to build a small CLI todo app in Python.

Here’s how to use AI without cheating yourself:

Step 1: Clarify requirements (ChatGPT)

Prompt:

“I’m a beginner at Python. I want to build a simple command-line todo app that can add, list, and mark tasks as done.
Help me break this into small steps and suggest what Python concepts I should learn for each step.”

You’ll probably get:

  • parse command-line input
  • store tasks in a list or file
  • print formatted output
  • basic functions, loops, conditionals

Now you have a roadmap.

Step 2: Learn micro-concepts (ChatGPT)

Pick one concept at a time:

“Teach me how to read and write a simple JSON file in Python with examples. Then give me 3 small exercises.”

Do those exercises yourself. Don’t ask AI to solve them unless you’re stuck and need a hint.

Step 3: Code with guidance (Copilot + ChatGPT)

In your editor:

  1. Write a comment: # function to load todos from todos.json
  2. Start writing the function — let Copilot suggest.
  3. Read the suggestion line by line. Ask:
  • Do I understand each line?
  • Is error handling missing?
  • Is the file path hardcoded?

If not sure, you can paste the snippet into ChatGPT:

“Explain this function line by line like I’m new to Python. Then suggest any improvements for beginners.”

Step 4: Debug like a detective (ChatGPT)

When you hit an error:

“Here’s the error and the relevant code.

  1. Explain what this error means.
  2. Ask me questions to help debug it instead of fixing it immediately.
  3. Only then suggest a possible fix.”

Now AI is acting more like a mentor than a vending machine.

6. Example prompts you can steal (and adapt)

Here are some prompt templates you can copy, tweak, and reuse.

For learning a concept

“I’m a beginner in [language/tech].
Explain [concept] in simple terms with 2–3 short code examples.
Then give me 3 practice tasks (without solutions) to try myself.”

For code review

“Review this [language] function as if you’re a senior engineer.

  • Point out bugs or edge cases.
  • Suggest improvements for readability and maintainability.
  • Don’t rewrite everything; comment on what I have.”

For refactoring

“Here’s my code.

  • Show a refactored version that’s easier to read.
  • Then list the main changes you made and why.
  • Keep your explanation beginner-friendly.”

For debugging

“Here’s an error message and the related code.

  • Explain what this error means in plain language.
  • Suggest 2–3 things I should check.
  • Only then propose a fix.”

For using Copilot better

You can even tell Copilot what you’re doing in comments:

# I'm a beginner. Generate a simple, readable function.
# Avoid clever one-liners; prioritize clarity and comments.
Enter fullscreen mode Exit fullscreen mode

You’ll notice the suggestions become more beginner-friendly.

7. How to avoid becoming “AI-dependent”

It’s a real risk: AI can make you feel productive without actually making you better.

Here’s a simple rule I use:

Always have at least one “AI-free” rep.

For example:

  • Solve one practice problem fully on your own before using AI.
  • Try implementing a feature yourself, then compare with AI’s version.
  • After AI explains something, take a break and re-explain it from memory in your notes.

You’ll quickly see what actually stuck vs what just “felt” clear in the moment.

8. When is it actually cheating?

Let’s be blunt:

It’s cheating when:

  • A course, exam, or assignment explicitly forbids AI, and you still use it.
  • You submit AI-generated work as your own without understanding it at all.
  • You misrepresent your abilities in a job or interview by relying on AI behind the scenes.

It’s healthy tool use when:

  • You’re honest about using AI where relevant.
  • You still practice solving problems yourself.
  • You treat AI as a partner, not as a replacement brain.

Most serious teams today would rather work with:

A junior dev who uses AI well and keeps learning
than
A dev who refuses AI out of “purity” but moves slowly and never improves.

9. Final thoughts: You’re allowed to get help

If you’re a beginner, here’s what I want you to remember:

  • You don’t get extra points for suffering in silence.
  • Real-world devs collaborate, search, copy patterns, and use tools.
  • AI is just a very powerful new tool in that toolbox.

Use an AI coding assistant for beginners like ChatGPT or Copilot to:

  • learn concepts faster
  • see more examples
  • avoid getting stuck for days
  • write cleaner, tested code earlier in your journey

…but don’t outsource your thinking.

You’re still the developer. AI is just your (very fast, slightly overconfident) pair programmer.

If you found this helpful, feel free to connect with me on LinkedIn:
👉 Dhruv Joshi

Happy coding — and happy pair-programming with AI. 🚀

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