Why Every Developer Should Be Using AI in Their Workflow

You’re missing out if you aren’t!

Artificial Intelligence (AI) is no longer a futuristic concept or a buzzword — it’s here, and it’s changing the way we work, particularly for developers. Despite all the excitement around AI, I still see many developers who hesitate to integrate AI into their daily workflow. Why? Well, the most common reason is they don’t fully understand what it can do for them. They see AI tools like GitHub Copilot and worry that using them will disrupt their code or even replace them in the future.

Let me tell you, that couldn’t be further from the truth. In this article, I’m going to show you the many ways AI can benefit your development process and how you should be taking advantage of it right now.

And if you don’t want to read but rather listen/watch, there is a video version of this article here:

The Misconception: AI is Just a Co-Pilot

Many developers view AI as nothing more than a “co-pilot” — something that might help you write code but doesn’t do much else. This mindset often leads to developers ignoring AI altogether because they think it interferes with their unique coding style. But here’s the reality: AI isn’t here to take over how you code; it’s here to enhance it.

AI tools can assist you in ways that go beyond just auto-suggesting lines of code. They can help you debug faster, test more efficiently, automate repetitive tasks, and even provide insights that would take you hours to discover on your own.

Why You Should Be Using AI?

Still not convinced? Let’s look at why AI should be part of your daily workflow.

Boost Efficiency

AI can help you automate mundane tasks like testing, debugging, and even writing documentation.

In other words, right now I’m referring to LLMs and their ability to generate text at a mind-boggling speed.

Is it the correct text? That’s definitely up for debate, and there are many ways in which you can help make sure it is.

However, LLMs tackle one aspect of our profession that we’ve made core even though is one of the lest impactful parts of it: writing.

We write code every single day, however, that code is just the output of all of our other tasks, like problem solving, coming up with innovative solutions, implementing or even creating new algorithms, and so on.

In other words, our biggest tool is not our keyboard, but rather our brain and our originality.

Writing code is just the inevitable output of using those tools.

At least until now.

Having LLMs write the code for us, under our guidance, is a fantastic way to increase the speed at which we deliver solutions. Not a way to replace us.

We as developer will still be doing all the hard work, AI will only do the boring part: writing.

Writing unit tests.

Writing documentation.

Writing features.

We do the thinking, AI does the writing. It’s a Win-Win!

Catch Bugs Earlier

With AI-powered tools, you can spot errors and inconsistencies in your code early on. You can have an LLM review your code looking for obvious issues like trying to modify the value of a constant, or logic errors, when you try to solve a problem incorrectly.

Mind you, some of the hardest problems to detect would only be picked up by some of the most advanced models, but that’s just now. Think 5 years from now.

The quality of these models will be so high that we’ll probably be using them to review entire codebases in seconds.

Improve Code Quality

Right now, we use linters to make sure teams of many developers generate the same type of code, following the same rules. However, there are many nuances that linters just can’t pick up on.

AI can offer suggestions that you might not have thought of, improving the overall quality and performance of your code and ensuring that entire teams work together following the same quality standards.

In the end, all of these benefits translate to the same single point: we become better developers through AI.

Addressing the Big Question: Will AI Replace Developers?

Now, whenever AI comes up in conversation, the inevitable question is: “Is AI going to replace developers?”

The short answer is no, absolutely not.

AI is not here to replace us, but to augment our abilities and make us more efficient. It takes care of the repetitive, low-impact work so we can focus on the more meaningful aspects of development.

As I’ve already mentioned, writing code, as important as it is, is just a small piece of the puzzle.

Our value lies in designing solutions, solving real problems, and thinking critically — things AI simply can’t do.

Instead of fearing AI, we should see it as a powerful tool that allows us to focus on the tasks that really matter.

The Tools You Should Start Using Today

Now that we’ve stablished why you should be using AI for your day-to-day as a developer, the question is: what tools are out there for me?

There are a ton of AI tools out there, but which ones should you start with? Here are my top recommendations:

• GitHub Copilot: You’ve probably heard of it, but the real question is — are you using it to its full potential? Copilot goes beyond just code suggestions; it helps you think through complex problems and even generates test cases. Many companies are already paying for it for their developers, so ask around if you’re interested but you just don’t want to pay for it.
• Codeium: A solid alternative to Copilot that prioritizes code privacy. It’s a great option if you’re concerned about keeping your proprietary code secure while still benefiting from AI-powered assistance. It features all the functionalities from Copilot plus a few others. And the best part? It’s completely free for individual users, so you can test it right now!
• OpenAI’s models or Claude for Documentation: Writing documentation can be tedious, but it’s crucial. Tools like ChatGPT (or OpenAI’s assistants) or even Claude can help generate documentation based on your code, making the process smoother and faster. In fact, if you feed it your code (careful here about privacy concerns), it’ll be able to explain the code back to you. Give it a more elabore prompt, and you’ll get some fantastic documentation about it, much better than what you would get through tools like Doxygen.
• AI-Driven Test Automation: Tools like Mabl can speed up the testing process by automating various types of tests, helping you push higher-quality code faster.
• Code reivew & security: Because it’s not just about writing the code and push it, code review is a critical part of the SDLC (Software Development Lifecycle). Of course, we always do this with coleagues, after all, who better to audit our code than other humans? Right? Well, yes, but the second best and much faster alternative is AI. Tools like Snyk and Codacy can help us find problems with our code, both in the form of unmet standards, hidden bugs or even security vulnerabilities that we haven’t picked up on.

The AI Hype: Should You Be Worried About Your Job?

Whenever the topic of AI comes up in developer circles, there’s always the inevitable question: “Is this going to replace us?” The short answer is no, it won’t. AI is here to assist and augment your capabilities, not take over your job. If anything, it will make you more efficient and open up more opportunities for you to focus on higher-level tasks rather than getting bogged down in repetitive work.

AI is not replacing developers — it’s freeing them up to be more innovative and productive.

Final Thoughts

AI is no longer an optional add-on for developers. It’s becoming an essential part of the workflow, allowing you to work faster, smarter, and with fewer errors. I

f you’ve been hesitant to dive into AI tools, now is the time. Start small with tools like Copilot or Codeium, and gradually explore more advanced options. Trust me, once you get the hang of it, you’ll wonder how you ever worked without it.