Are Devs Becoming Lazy? The Rise of AI and the Decline of Care
With the rise of AI-powered tools like GitHub Copilot, software development is entering a strange new era. Coding used to be about craftsmanship, precision, and knowing your tools inside and out. Now? It’s starting to feel more like watching a machine do the heavy lifting while we just click “accept.” While these tools promise to boost productivity, they’re also giving developers an easy way to sidestep the messy details, the security checks, the… real work. So, here’s the big question: Are we witnessing a new age of "lazy" developers? Let’s break down why this might be happening.
The Problem with AI-Generated Code
GitHub Copilot, the so-called "AI pair programmer," generates code suggestions in real time, filling in functions, syntax, and even whole scripts based on simple prompts. But here’s the catch: Copilot-generated code can be flat-out risky. Studies have shown that about 40% of Copilot’s code suggestions are vulnerable to security issues like SQL injection and buffer overflows. When developers lean on these suggestions without scrutiny, they’re introducing bugs that could blow up in their faces (or worse, in their users' faces). This reliance can lead to a lazy habit of assuming AI-generated code is "good enough," skipping the critical thinking and problem-solving that make great developers, well, great.
Shortcuts Over Understanding
In the old days, developers had to really know their stuff. Coding wasn’t just a checklist—it was a craft, and every line was written with care. Today, with AI doing the "hard" parts, there’s less incentive to learn the deeper layers of security, optimization, or best practices. Copilot’s suggestions often mirror insecure coding patterns scraped from public code repositories, meaning developers who blindly accept these suggestions are recycling bad habits. Coding now can feel like following the machine’s lead, rather than creating something from scratch. It’s easy. But is it right?
Security as an Afterthought
Take security, for example. You’d think that developers would be extra cautious here. But with tools like Copilot, security can quickly become an afterthought. As mentioned in the study by Chen et al. on GitHub Copilot's security implications, many of Copilot’s code suggestions are vulnerable to CWE Top-25 security issues. It’s not just small mistakes, either. These are big-ticket vulnerabilities—like SQL injection or command injection—that can be exploited to devastating effect. Yet, as long as the code "works," there’s a real temptation to move on, trusting that the AI wouldn’t steer us wrong. Spoiler: It absolutely will.
Dependency on AI at the Cost of Skill
Here’s a hard truth: leaning too much on AI tools can make developers rusty. As more of the "thinking" is handed off to Copilot, we lose chances to sharpen our skills. This dependency could have serious consequences down the line. Imagine a world where developers can no longer troubleshoot complex bugs or spot security flaws because they’re so used to AI doing the heavy lifting. It’s not just a short-term convenience; it’s a long-term risk to the integrity of our software and the skill set of our workforce.
Encouraging Better Practices
So, how do we avoid falling into this trap? Developers and companies alike need to approach AI tools with caution, using them as assistants, not autopilots. Here are a few ways to make sure we stay sharp, even in an AI-driven world:
Always Review AI-Suggested Code – Think of AI suggestions as rough drafts. They’re a starting point, not the final say. Review them carefully, make improvements, and don’t be afraid to reject what doesn’t meet your standards.
Stay Sharp on Core Skills – No matter how powerful AI gets, fundamentals like security practices, debugging, and system design will always matter. Don’t let your skill set atrophy just because an AI can finish your sentences.
Invest in Security Training – As AI tools introduce new risks, developers need to get smarter about spotting them. Regular training in security fundamentals is essential if we’re going to keep AI-generated vulnerabilities from creeping into our code.
Combine AI with Static Analysis and Security Tools – Using tools like CodeQL alongside Copilot can flag security risks early on. If Copilot is your "co-pilot," then think of CodeQL as your backseat driver, keeping you from veering off the road into unsafe territory.
The Bottom Line
Look, the convenience of AI is real, and it’s not going away. But if we rely too heavily on tools like Copilot, we risk losing the very skills that make us valuable as developers. AI isn’t an excuse to get lazy. It’s a tool, and like any tool, it’s only as good as the hands that wield it. So yes, let’s embrace the future of software development, but let’s do it with our eyes open—and our sleeves rolled up. After all, the best developers aren’t the ones who take the easiest path; they’re the ones who do things the right way, every time.
The next time you’re coding, ask yourself: Are you driving, or are you just along for the ride?