So, it was 2 a.m. Tuesday night. The release was scheduled for tomorrow morning. And there’s a Firebase crash laughing at me. NullPointerException. This only happens on Android 9. Only when the user moves the screen after logging in, but before data is loaded.
I was going insane. Examining this 500-line passage that was written by someone else, with Log.d(“PLEASE WORK”, “value: $someValue”) inserted all over it. You’re familiar with the feeling, right? When one bug makes you question whether you should have become a farmer instead.
Today? I still experience those moments. But now I have this secret weapon. A code companion that never sleeps, is extremely knowledgeable, and does not judge my awful variable names. ChatGPT. It won’t take our place. Simply put, it speeds up the tedious tasks so we can resume creating exciting things. It is like to gaining superpowers for your coding process.
What ChatGPT Can Do (and What It Can’t) for debugging and error?
AI can help with it. Your code has not been compiled by ChatGPT. Not like a computer, it doesn’t “understand” itself. Pattern matching on steroids is more accurate. It gained knowledge from a tonne of code on Stack Overflow, GitHub, and documents. “Hmm, seen millions like this, but in working ones, this part is different,” it says when it sees your flawed code.
It can help interpret stack traces; those strange Gradle errors? Use “explain this like I’m an Android dev” to paste them in, and it will work like magic. It can suggest likely causes and recommend fixes based on your code snippet. It’s excellent for tasks such as “convert this Java AsyncTask to Kotlin Coroutine” or for “write Parcelable for this data class.”
Where it falls short:
It makes things up
A major issue. ChatGPT is confidently going to create outdated library functions or create modifiers that don’t exist. Always verify its responses.
Privacy
Avoid pasting business code into ChatGPT’s public area. Make the assumption that anything you paste will be utilised for training.
Context matters
Dumping 200 lines without any context results in a garbage response.
How to Feed It the Right Info to ChatGPT?
The difference between a “meh” and a “wow” answer is the prompt.
Be specific
Share the actual error message.
Add relevant code
Don’t just paste broken functions. Include data classes, XML layout, and error messages.
Mention the language, framework, and version
It helps a lot. It can guess, sure, but if you say “Go” or “Python” right away, the answers get sharper. Give it a role: Start with “You are an expert Android Developer who specializes in Kotlin, Coroutines, Jetpack Compose…”
Describe what you expected vs. what actually happened
A bad prompt is: “My code crashes.” A good prompt is: “Android app crashes with NetworkOnMainThreadException when I call this from MainActivity onCreate. Using Retrofit. Here’s the function, interface, and logcat trace. What’s the right way to do a network request off the main thread with Coroutines?”
Example prompt
“Hey, my Kotlin function crashes with a NullPointerException. think it’s because the ‘user’ object can be null. How do I fix this to be safe and return the default string if the user or profile image is null?”
Real-Life Use Cases
1. Tracking down a null reference in Kotlin
Before:
Kotlin
data class User(val name: String, val profileImageUrl: String?)fun getProfileImage(user: User?): String {
return “Showing profile for ${user.name}: ${user.profileImageUrl}”
}
This crashes with a NullPointerException on the user. Name of the user is null.
Prompt
“Hey, my Kotlin function crashes with a NullPointerException. think it’s because the ‘user’ object can be null. How do I fix this to be safe and return the default string if the user or profile image is null?”
After (The Fix):
Kotlin
fun getProfileImage(user: User?): String {val userName = user?.name ?: “Guest”
val imageUrl = user?.profileImageUrl ?: “no_image_available.jpg”
return “Showing profile for $userName: $imageUrl”
}
2. Getting unstuck from a UI loop in Jetpack Compose
Before: Want to show user list but UI keeps refreshing non-stop.
Kotlin
@Composablefun UserList(viewModel: UserViewModel) {
val users = viewModel.getUsers() // Problem is here
LazyColumn {
items(users) { user ->
Text(text = user.name)
}
}
}
Prompt
“Hey ChatGPT, Jetpack Compose composable stuck in infinite recomposition loop. Pretty sure the problem is how I’m getting the user list from the ViewModel. Can you check this code and tell me right way to collect state in Compose?”
After (The Fix):
Kotlin
@Composablefun UserList(viewModel: UserViewModel) {
val users by viewModel.users.collectAsStateWithLifecycle()
LazyColumn {
items(users) { user ->
Text(text = user.name)
}
}
}
3. Diagnosing a failed build in Android Studio
Before (The Error):
Execution failed for task ‘:app:kaptDebugKotlin’.
> class org.jetbrains.kotlin.kapt3.base.KaptContext cannot be cast to class org.jetbrains.kotlin.kapt3.base.KaptContext
Prompt
“Getting weird Gradle sync error after pulling changes. Looks like a class casting issue with Kapt. No idea what this means. Can you explain and suggest fixes?”
After (The Explanation)
ChatGPT Explained: Error means KaptContext can’t be cast to KaptContext. Sounds impossible, but happens when two different classloaders load the same class. Classic dependency conflict. Usually means two different Kotlin Gradle Plugin versions are fighting. Check Kotlin versions in all build.gradle files.
Beyond Fixes: Asking “Why”
Ask it to explain the bug, not just patch it. Blindly copy-pasting without understanding = skills get worse. But use it for learning, asking “explain this fix” or compare to your solution can actually make you better faster. Use ChatGPT to learn better habits or avoid common pitfalls.
When you’re stuck, ask yourself, “What are three other ways to do this?” It helps you escape thought patterns and shows you new patterns you might not find otherwise. This is good for juniors who want to grow by understanding, not just copying solutions. The copy-paste trap: You won’t learn anything if you simply imitate without understanding why it works.
Tips to Get Better Results for Code Debugging and Error Fixing with ChatGPT
Use follow-ups to refine the answer
Yep, and you should. That’s part of how to use ChatGPT for debugging; it works better as a back-and-forth than a one-shot answer machine. The first answer isn’t always the best. If you don’t like the solution, tell it! “That works, but global CoroutineScope feels wrong. Can you use viewModelScope instead?”
Don’t just paste the answer, read it:
What happens if ChatGPT provides an ineffective solution? It does! As the developer, you remain in charge.
Run tests after applying any change
Don’t just copy-paste, test it, and see if it actually runs. Test carefully at all times.
Don’t blindly trust code
ChatGPT helps, but you ship it. It makes things up. Always verify its responses. If it gives a wrong answer for debugging, and it happens, give it more info and ask again.
Final Thoughts: It’s Like Pair Programming, Minus the Judgement
ChatGPT won’t replace your brain. Our jobs won’t be replaced by AI. However, developers who use AI will be far more productive than those who don’t. A magic wand is not what ChatGPT is. Incapable of understanding business needs, creating scalable architecture, or replacing the fulfillment that comes from resolving challenging issues on your own.
Use it as a tool in your debugging workflow, not a crutch. It can be a really effective helper. It eliminates the most tiresome and annoying aspects of the work, such as boilerplate, confusing error messages, and ridiculous syntax problems. It frees up mental energy for important tasks like creating stunning user interfaces, fantastic features, and supporting other developers.
Frequently Asked Questions
Can ChatGPT fix code bugs?
Yeah, pretty often. You just need to tell it what the code should do, what’s actually happening, and paste the snippet. That’s the basic way I use it to spot issues fast.
Do I need to say the language while debugging?
Helps a lot. It can guess, sure—but if you say “Go” or “Python” right away, the answers get sharper.
What kind of stuff can it fix for debugging?
Syntax errors, weird logic, bad loops, imports that don’t exist, stuff like that. It also explains error messages well, making them less cryptic.
Is ChatGPT better than a real debugger?
Not really. But if I don’t feel like stepping through breakpoints or scanning docs for the hundredth time, it saves me time. Think of it like a quick second brain.
What if the bug is in a library I didn’t write?
Still works sometimes. I’ve pasted errors from Next.js or pandas and it’s been helpful. It won’t always nail it, but it gives you a direction to dig into.
Is it safe to paste in my code generate by chatgpt?
Mostly. I don’t drop anything sensitive—no API keys or private stuff. That’s just habit now.
Can I keep asking follow-ups for debugging?
Yep, and you should. That’s part of how to use ChatGPT for debugging—it works better as a back-and-forth than a one-shot answer machine.
What if it gives a wrong answer for debugging?
Happens. Don’t just copy-paste—test it, see if it actually runs. If it doesn’t, give it more info and ask again.
Can it clean up the code while fixing it?
Yeah. You can ask for shorter code, simpler logic, or even “make it more readable.” I do that all the time after debugging something gnarly.
