How Developers Are Using ChatGPT as a Coding Assistant

For many developers, ChatGPT has quietly become another tool in the toolbox—right alongside the IDE, Stack Overflow, and documentation. It’s not a replacement for real engineering skills, but it is a surprisingly capable coding assistant that can help with debugging, boilerplate, and learning new languages faster.

Here’s how developers are using it in practice.

1. Debugging: Explaining Errors and Hunting Bugs

One of the most common use cases is simple:

“Here’s my error. What does it mean, and how do I fix it?”

Developers paste in:

• A stack trace

• A short code snippet

• A description of what they expected to happen

ChatGPT can then:

• Translate cryptic error messages into plain English

• Suggest likely causes (“You’re mutating state directly in React”, “This is a null pointer in this line…”)

• Propose a minimal fix or refactor

For example, a developer might paste:

“I’m getting TypeError: Cannot read properties of undefined (reading 'map') in this React component…”

ChatGPT can point out that the array might be undefined on first render, suggest adding a defensive check, or initializing state correctly. It doesn’t always nail it first try, but it often gets you close enough to spot the real issue.

The key is to keep snippets small and focused. If you paste an entire codebase, the answer will be vague. If you provide a clear, self-contained example, ChatGPT behaves more like a sharp debugging buddy.

2. Generating Boilerplate and Scaffolding

No one enjoys writing the same setup code over and over:

• REST API handlers

• CRUD endpoints

• Form validation logic

• Redux slices, context providers, DTOs, etc.

Developers increasingly ask ChatGPT to:

• “Generate an Express.js route for CRUD operations on a User resource.”

• “Create a basic Spring Boot controller for /orders with GET/POST endpoints.”

• “Write a TypeScript interface and a simple React form for this JSON schema.”

The result is boilerplate that’s 70–80% correct, which you then shape to fit your architecture, conventions, and security requirements. It saves time on the repetitive bits so you can spend energy on the logic that’s actually unique to your system.

3. Learning New Languages, Frameworks, and APIs

ChatGPT is also acting as an interactive tutor for developers moving into new territory:

• “Show me the equivalent of this Java code in Go.”

• “Explain how async/await works in JavaScript with a simple example.”

• “I know Java, teach me the basics of Rust using comparisons.”

Because it supports conversation, you can:

1. Ask for a high-level explanation

2. Follow up with, “Can you simplify that?”

3. Then ask, “Now give me a slightly more advanced example.”

This makes it much easier to ramp up on new languages and frameworks than reading docs alone. Docs are still essential, but ChatGPT helps bridge the gap between “I kind of get it” and “I’ve seen a working example tailored to my question.”

4. Writing Tests and Refactoring Existing Code

Another growing pattern is using ChatGPT to improve existing code instead of only generating new:

• “Here’s a function—write Jest tests that cover the main edge cases.”

• “Refactor this long method into smaller functions while keeping behavior the same.”

• “Improve the naming and add comments explaining what this function does.”

It’s not perfect, and you still need to review carefully, but it’s particularly good at:

• Suggesting edge cases you might have missed

• Cleaning up overly long functions

• Proposing clearer names and adding docstrings

In other words, it nudges code toward being more readable and testable—even if you don’t accept every suggestion.

5. The Real Role: Partner, Not Replacement

The most effective developers don’t treat ChatGPT as an infallible authority. They treat it like:

• A junior dev who’s fast, tireless, and good at pattern recall

• But who sometimes makes things up, misses context, or ignores constraints

You still need to:

• Understand what the code does

• Check for security, performance, and correctness

• Make architectural decisions and tradeoffs

Used this way, ChatGPT doesn’t replace developers—it amplifies them. It shrinks the time spent on boilerplate, rote debugging, and “I just need an example” moments so you can focus on shipping better software.