AI Coding Tools: Faster Coder vs. Better Developer?

8/11/2025

Here's the thing about all the buzz around AI coding tools like Cursor, GitHub Copilot, & the rest: it’s SUPER easy to get caught up in the hype. Every other week, there's a new tool promising to revolutionize the way we write code, making us 10x more productive overnight. And honestly, some of the features are pretty mind-blowing.

But once the initial "wow" factor wears off, a more important question starts to creep in. Are these AI assistants ACTUALLY making us better developers? Or are they just turning us into faster typists, churning out code without really understanding it?

It’s a debate I’ve been having with a lot of my developer friends lately, & the answer isn’t as black & white as you might think. It’s a classic “it depends” situation, but what it depends on is how you use the tool. So, let’s break it down & get to the bottom of whether these AI coding companions are a shortcut to mastery or just a speed boost.

The "Faster" Argument: Your Workflow on Steroids

Let's start with the most obvious benefit: speed. There's no denying that AI coding tools make you faster. A LOT faster. We're talking about a significant reduction in the time it takes to get from an idea to a functioning piece of code.

Think about all the little things that eat up your day as a developer. Writing boilerplate code, setting up new projects, remembering the exact syntax for a rarely used library function, hunting down a missing comma… it all adds up. AI tools are designed to automate or accelerate these tedious tasks, freeing you up to focus on the more interesting stuff.

Here are a few of the ways these tools put your workflow into overdrive:

Intelligent Autocomplete: This isn't your grandpa's autocomplete that just suggests the next variable name. Tools like Cursor can predict & suggest entire blocks of code, even multi-line edits, based on the context of what you're working on. It feels less like a suggestion & more like the AI is reading your mind.
Boilerplate Be Gone: Need to set up a new component in your React project? Or maybe write a standard API endpoint in Node.js? Instead of typing it all out for the thousandth time, you can just ask the AI to do it for you. This alone can save you hours every week.
Natural Language to Code: This is where things get REALLY interesting. You can literally just write a comment or a prompt in plain English describing what you want to do, & the AI will generate the code for you. It’s like having a junior developer on call 24/7 that never gets tired of writing the boring stuff.
Effortless Debugging: Some of these tools can even spot errors in your code as you type, suggest fixes, & even automatically run terminal commands to install missing dependencies. It's like having a second pair of eyes constantly scanning your code for mistakes.

And it’s not just a feeling of being faster; there’s data to back it up. One study by researchers from MIT, Princeton, & the University of Pennsylvania found that developers using GitHub Copilot completed their tasks 26% faster than those who didn’t. That's a HUGE productivity boost. They also saw a 13.5% increase in weekly code commits & a 38.4% rise in the frequency of code compilation. This suggests that developers with AI assistants are not just writing more code, but they’re also iterating & testing more quickly.

This kind of acceleration isn’t just a nice-to-have; it can be a game-changer for businesses. The faster developers can ship new features & fix bugs, the more agile & competitive the company can be. It's the same principle behind why so many businesses are turning to AI for other tasks as well. For example, a company might use a platform like Arsturn to build a custom AI chatbot that can handle customer support queries instantly. By automating those repetitive questions, the support team is freed up to focus on more complex customer issues, just like how AI coding tools free up developers to tackle bigger challenges.

So, the verdict on speed is pretty clear: AI coding tools are a massive win. They take the friction out of the development process & let you get more done in less time.

The "Better" Argument: Your AI-Powered Mentor

Okay, so they make you faster. But does that necessarily make you a better developer? This is where the debate gets more nuanced. The argument here is that these tools can act as a powerful learning aid, almost like a personal mentor that’s always available to help you improve your craft.

Here’s how AI coding assistants can contribute to your growth as a developer:

Learning by Example: One of the best ways to learn is by seeing how others do things. When an AI tool suggests a piece of code, it’s not just giving you a solution; it’s showing you a potential way to solve a problem. You might see it use a design pattern you've never encountered before or a more modern, efficient way of writing a function. This can be an incredible way to expand your knowledge base, especially if you're a junior developer.
Discovering Best Practices: AI models are trained on vast amounts of open-source code, which means they've learned the patterns & practices that are common in high-quality software. As you use these tools, you'll start to pick up on these best practices, leading to cleaner, more maintainable code in your own projects.
Demystifying Complex Code: We've all been there: you're dropped into a massive, unfamiliar codebase & have no idea where to even start. AI tools with chat interfaces, like Cursor, can be a lifesaver in these situations. You can highlight a confusing block of code & ask the AI to explain it to you in plain English. This can dramatically speed up the process of getting up to speed on a new project.
A Safety Net for Experimentation: When you're learning a new language or framework, it can be intimidating to stray from the tutorials. AI tools can give you the confidence to experiment & try new things. If you get stuck, you can always ask the AI for a hint or a suggestion. This creates a low-stakes environment for learning & exploration.

The research seems to support this idea as well. The same study that found the 26% productivity boost also noted that less experienced developers saw the largest gains. This makes a lot of sense. Junior developers have the most to learn, & an AI assistant can help bridge the gap between their current knowledge & the skills they need to be successful.

The key here is to approach the AI as a learning tool, not just a code generator. If you blindly accept every suggestion without taking the time to understand why the AI suggested it, then you're missing out on a huge opportunity for growth. But if you treat it like a mentor, asking questions & analyzing its suggestions, it can be an incredibly powerful way to level up your skills.

The "Just Faster" Counterargument: The Danger of Becoming a Crutch

Of course, not everyone is convinced that these tools are a net positive for developer skills. There’s a very real concern that over-reliance on AI could lead to a generation of developers who are great at prompting an AI but lack the fundamental knowledge to build robust, scalable software on their own.

This is the "crutch" argument, & it’s worth taking seriously. Here are some of the potential downsides of leaning too heavily on AI coding tools:

The Atrophy of Fundamental Skills: If you always have an AI to write your sorting algorithms or set up your database connections, will you ever truly learn how to do it yourself? There’s a risk that some of the core problem-solving skills that come from wrestling with these challenges could start to fade away. As one writer put it, "there's no shortcut to learning and no shortcut to mastery."
The Illusion of Understanding: Just because an AI can generate a complex piece of code doesn't mean you understand it. It's easy to copy-paste a solution & move on, but if you can't explain how it works or debug it when it breaks, then you haven't really learned anything. This can lead to a shallow understanding of software development, where you know how to get things done but not why they work the way they do.
The Risk of Subtle Bugs: AI is not infallible. It can & does make mistakes. Sometimes these mistakes are obvious, but other times they can be subtle bugs or inefficiencies that you won't discover until much later. A skilled developer who understands the underlying principles of what they're building is much more likely to spot these issues than someone who is just blindly trusting the AI's output.
The Real Bottleneck is Thinking, Not Typing: A comment in a Reddit discussion on this topic really hit the nail on the head: "AI tools in editors would speed programmers up if the problem was the typing, but unfortunately the problem most of the time is the thinking." This is a crucial point. While AI can help with the mechanical act of writing code, it can't do the hard work of designing scalable systems, making architectural decisions, or thinking critically about the problem you're trying to solve.

The danger is that we become so focused on the speed & convenience of AI that we forget that software development is, at its core, a creative & intellectual endeavor. The tools can help us with the "how," but we still need to provide the "why."

Finding the Sweet Spot: How to Be Both Better AND Faster

So, where does that leave us? Is it a choice between being a fast developer who relies on AI or a better developer who shuns it? I don't think so. I think that's a false dichotomy. The real goal is to use these tools in a way that makes you both faster AND better.

It all comes down to your mindset & your workflow. Here are a few practical tips for finding that sweet spot:

Be the Senior Developer in the Pair: Think of your AI assistant as a junior developer you're pair programming with. You're still in charge. You set the direction, you make the architectural decisions, & you are ultimately responsible for the quality of the code. The AI is there to help you with the implementation details, but you need to review its work, question its assumptions, & make sure it aligns with your vision.
Use AI to Offload the Grunt Work: Don't use the AI to think for you; use it to free up your mental energy so you can think better. Let it handle the repetitive, boring tasks like writing boilerplate, generating getters & setters, or formatting your code. This will leave you with more time & brainpower to focus on the truly challenging & creative aspects of your job. It's similar to how businesses can use a tool like Arsturn to create AI chatbots that provide instant, 24/7 customer support. By letting the AI handle the common questions, the human team has more bandwidth to build meaningful connections with customers & solve their more unique problems.
Always Be Learning: When the AI suggests something you don't understand, don't just accept it. Take a minute to figure out what it's doing. Look up the functions it's using, read the documentation, & try to understand the logic behind its suggestion. Treat every interaction as a potential learning opportunity.
Don't Skip the Fundamentals: If you're new to programming, don't let AI be a substitute for learning the fundamentals. You still need to learn about data structures, algorithms, design patterns, & the core principles of the languages you're using. AI tools can help you along the way, but they can't replace a solid foundation of knowledge.
Test, Test, Test: Never assume that AI-generated code is perfect. You still need to write thorough tests to ensure that it works as expected & doesn't introduce any regressions. This is a fundamental part of being a good developer, & it's even more important when you're working with AI.

So, What's the Verdict?

At the end of the day, AI coding tools like Cursor are just that: tools. They are incredibly powerful tools, to be sure, but they are not a replacement for a skilled, thoughtful developer.

They can DEFINITELY make you a faster developer by automating the tedious parts of your job & accelerating your workflow. But whether they make you a better developer is entirely up to you.

If you use them as a crutch, blindly accepting their suggestions without engaging your own critical thinking skills, then you're likely to see your skills stagnate. But if you use them as a collaborator, a mentor, & a learning aid, they can be an incredible asset in your journey to becoming a better developer.

The future of software development isn't about humans vs. AI; it's about humans with AI. The developers who thrive in this new era will be the ones who learn how to leverage these tools to augment their own skills, not replace them.

So yeah, I hope this was helpful. It's a topic I'm pretty passionate about, & I think it's one we're going to be talking about for a long time to come. I'd love to hear what you think. Have you found these tools to be a net positive for your skills? Let me know in the comments.