I Let AI Write My Code. Here Is What I Still Had to Fix

AI can write a React component, generate an API integration, fix a JavaScript error, and even create an entire feature in minutes.

But here is something I have been thinking about lately:

If AI writes most of your code, what exactly should your role as a developer become?

I have been using AI coding tools, and while they can save a ridiculous amount of time, I have also noticed that generating code is often easier than making that code reliable.

And I am curious whether other developers are experiencing the same thing.

AI Can Write the Code. But Can It Understand the Project?

Imagine asking AI to add a feature to an existing application.

It generates the component, creates a few helper functions, and everything looks clean.

But then you notice that it uses a different coding pattern from the rest of your project. It introduces unnecessary dependencies or duplicates functionality that already exists somewhere else.

Technically, the feature works.

But would you actually approve that code in a production pull request?

This raises an interesting question: should AI be responsible for understanding the entire codebase before making changes, or is that still entirely the developer's responsibility?

GitHub has published useful guidance on reviewing AI-generated code, including checking its correctness, security, and maintainability.

The Happy Path Is Not the Real Application

Here is a simple example:

const userName = user.name.toUpperCase();

AI might generate this perfectly reasonable line of code.

But what happens when the API returns an incomplete user object?

What happens when the request fails, the data is missing, or the application receives something unexpected?

The code might work perfectly in the example AI tested, but real applications rarely behave that predictably.

This is where developer experience still matters.

However, I also wonder whether these problems are genuinely caused by AI or whether developers have always written code without considering enough edge cases.

Is Reviewing AI Code Becoming a Full-Time Job?

One argument I keep hearing is that AI makes developers faster.

Another argument is that developers now spend more time reviewing, debugging, and correcting generated code.

Both seem reasonable.

If AI generates 500 lines of code in a few minutes, but understanding those 500 lines takes an hour, did we actually save much time?

Or is the problem simply that we are asking AI to generate too much code at once?

I think smaller tasks, proper context, and automated tests can make a huge difference. But I am interested in how other developers approach this.

Microsoft also recommends reviewing AI-generated changes and validating them through testing. Its AI coding best practices explain how developers can work more effectively with coding agents.

The Bigger Question: What Happens to Junior Developers?

This is probably the part I find most interesting.

Earlier, junior developers learned by writing functions, debugging errors, understanding documentation, and gradually becoming comfortable with code.

Now, a beginner can ask AI to generate almost anything.

That sounds great for productivity, but could it also make it easier to skip the learning process?

If someone can generate a working application without understanding how it works, what happens when that application breaks?

At the same time, AI might actually help beginners learn faster if they use it to understand concepts instead of blindly copying solutions.

So perhaps the real difference is not whether someone uses AI.

It is whether they understand the code AI produces.

Where I Stand

I do not think AI is replacing the need for developers to understand programming.

If anything, I think understanding code is becoming more important because developers now have more code to review, more implementation choices to evaluate, and more responsibility for deciding whether generated solutions are actually good.

AI is a powerful coding assistant.

But I would still trust a developer who understands a simple solution over someone who generates a complicated application without understanding what happens inside it.

For businesses building applications through Custom Web Development Services, this distinction matters too. Faster code generation is useful, but maintainability, security, and reliability still require engineering judgment.

Now I Want to Hear From Other Developers

I am genuinely curious about how other people are using AI in their development workflow.

Do you actually review every line of AI-generated code, or do you trust it when the tests pass?

Have you ever spent more time fixing AI-generated code than writing it yourself?

Do you think AI coding tools are making junior developers better programmers or making them more dependent?

If AI can generate an entire application, what skill will separate a good developer from an average one in the next few years?

Personally, I think the last question is going to become increasingly important.

What has your actual experience been with AI-generated code? Not what AI promises, but what happens when you use it on real projects?