7 Ways AI Can Help You Write Code [2024]

7 Ways AI Can Help You Write Code [2024]

Codeium, Copilot, Code Whisperer... The number of new AI coding assistants entering the market might leave you wondering where to begin.

The good news?

Despite the variety, these AI tools share a common goal: to improve your coding productivity.

In this article, we'll talk about the specific features that make AI coding assistants so valuable. We will also determine whether they are necessary or simply a nice thing to have.

Is Using AI for Coding Worth Doing 🤔?

Using an AI coding assistant can be a smart move, especially if you're an experienced developer. These modern tools can take care of the repetitive stuff, like setting up boilerplate code and freeing up your time for the more complex parts of your project.

In short: AI coding assistants are great for helping you focus on the bigger picture.

But if you're just starting out in coding, be careful not to rely on them too much.

It's still important to learn the basics yourself (plus, you should always review the code for accuracy, and experience helps here).

However, in my opinion, it's definitely worth using an AI assistant for those tedious parts of coding that don't need much input from you. You can let the AI handle the routine work while you concentrate on the creative and challenging parts.

Benefits of using AI coding assistants
Benefits of using AI coding assistants

7 Ways AI Can Help with Coding

Let's talk about seven key ways AI can revolutionize how you write code, making your everyday work smoother.

#1. Autocompletion and Code Suggestions

Autocompletion and code suggestions are usually the primary features of most AI coding assistants.

As you type, the AI predicts and suggests the next part of your code, learning from patterns and common practices in programming. This can be particularly helpful when you're dealing with basic code structures.

Codeium's autocomplete feature in action
Codeium's autocomplete feature in action

However, it's worth noting that the nature and accuracy of these suggestions can vary across different tools and languages.

Some tools might better understand specific programming languages or frameworks, while others may excel in offering more relevant suggestions based on the current project.

While most of the tools you try should give you decent results, it's always a good idea to test a few to see which works best for you.

#2. Error Detection and Correction ❌

AI coding assistants can be a game-changer when it comes to fixing bugs in your code.

If you find out something isn’t working, these tools can be your go-to for assistance. Instead of spending hours trying to debug, you can simply ask the AI for help.

It will analyze your code, pinpoint where the issue might be, and suggest solutions or alternative approaches.

Detailed bug explanations by Kodezi
Detailed bug explanations by Kodezi

This saves time and enhances your understanding of the problem, making you a more efficient and effective coder in the long run.

#3. Code Optimization

AI coding assistants can be CRUCIAL in optimizing your code, acting almost like a more experienced developer providing feedback.

If you're unsure about a piece of code you've written, these tools can help you refine it for better readability and performance. Just like asking a colleague for advice, you can request the AI to review your code and suggest improvements.

Potential code improvements (using Sourcegraph Cody)
Potential code improvements (using Sourcegraph Cody)
Of course, AI cannot match the feedback from experienced developers, but don't worry - it's usually constructive.

Whether it's streamlining complex functions, reducing redundancy, or enhancing the overall structure, the AI can guide you towards a more efficient and cleaner codebase.

This feature is especially beneficial for ensuring that your code not only works well but also respects to best coding practices and standards.

#4. Automated Testing 🐞

AI coding assistants can be a lifesaver in automated testing.

Think of them as a head start in creating unit tests for your code. They generate these tests, which can be a great launchpad, saving you the initial hassle of setting up.

Sure, you'll need to edit the output to fit your project's specifics, but they often cover a lot of ground, including basic test cases.

This means you spend less time on the routine start-up of testing and more on refining and strengthening your code's reliability.

#5. Better Code Organization ✅

AI coding assistants go beyond just writing code, and they can also keep your codebase well-organized.

These tools offer features that can scan through your code, helping you locate specific snippets or understand how certain parts are interconnected.

For example, you can ask your AI assistant, "How do we handle user authentication in this project?" and get a direct pointer to the relevant sections of your code.

This is particularly helpful in large projects where keeping track of every piece can be challenging. By using AI to navigate and organize your code, you save time and also maintain a cleaner and more efficient codebase.

This makes it easier for you and your team to work on and understand the project's logic.

#6. AI-Powered Terminal

AI's influence also extends to the terminal, transforming it into a more intuitive and error-resistant tool.

With AI-powered terminals, you get features like autocomplete for your commands, which can be a huge time-saver. The AI anticipates what you're trying to do and suggests commands accordingly.

This not only speeds up your workflow but also helps you learn new command syntaxes and options.

Also: If you run into errors in your terminal, the AI can step in to help you troubleshoot. It analyzes the error messages and offers suggestions or solutions to fix them.

Auto-debugging your terminal error (using Cursor IDE)
Auto-debugging your terminal error (using Cursor IDE)

This means less time googling error codes and more time being productive, making your terminal work smarter and more efficiently.

#7. Natural Language to Code (Bonus)

As a bonus, it's worth mentioning an interesting feature offered by tools like GitHub Copilot X: the ability to convert natural language into code using voice commands.

GitHub Next | Copilot Voice
GitHub Next Project: Write code without the keyboard. Difficulty typing? Use your voice to code without spelling things out by talking with GitHub Copilot.

This feature represents an important step forward in making coding more accessible and efficient. You can simply describe what you want your app to do, and the AI will translate it into functional code.

This can be especially helpful when brainstorming or if you prefer to verbalize your thoughts.

In my opinion, it's a way of making code more interactive and aligned with natural human communication (making the process more intuitive.)

Related: Take a look at my article on Code Whisperer and Copilot.


In case you still have some questions 👇

Can AI Tools Adapt to Different Coding Styles and Practices?

Yes, AI tools can adapt to different coding styles and practices. They are designed to learn from various codebases and can tailor their assistance to match your unique coding approach.

What Are the Benefits of Using AI in Coding?

  • Speeds up the coding process
  • Helps with debugging and error correction
  • Automates repetitive tasks
  • Enhances code quality and organization
  • Offers innovative features like voice-to-code

What Are the Limitations of Using AI in Coding?

A big mistake is to rely too much on AI for coding. While AI tools are excellent assistants, they aren't replacements for human expertise and the reliability of sources written by experienced programmers.


And that's it. Now, you know all the different ways how AI can help you code faster.

P.S. Are you curious about improving your everyday work with modern tools? (also using AI 🧐) Sign up for my newsletter to get my thoughts & tips on this.

Thanks for taking the time to read this - let me know if you have any other questions!

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