The Decline of Professional Developers: Why Bad Code Still Rules in an AI World

Bad code isn’t new. It’s been haunting the tech world for decades. What’s troubling now is that it’s thriving in ways we couldn’t have imagined before. Generative AI, a tool with limitless potential, is making it easier and faster to ship bad code than ever. Instead of raising the bar, we’ve given bad habits a turbo boost.

The rise of AI tools highlights something we’ve known for a while: there’s a critical shortage of professional developers—those who take the craft of coding seriously. Instead, we’re flooded with an ever-growing number of coders who lack the skills, discipline, or commitment to write clean, maintainable software. And no, AI isn’t fixing that. It’s just exposing the cracks in the system.

Why Bad Code Is Winning

Let’s face it: most developers don’t care about writing good code. The industry celebrates “shipped it fast” over “shipped it right.” As long as it runs, it’s good enough. But this mindset is short-sighted. Bad code doesn’t just cause bugs; it multiplies. It makes systems harder to maintain, harder to scale, and harder to fix when something goes wrong.

Movements like Clean Code and The Scribe’s Oath exist to counter this culture, but let’s be real: they’re niche. Only a tiny fraction of developers care enough to embrace them. The rest? They’re stuck in the churn of quick fixes and patchwork solutions, either unaware or indifferent to the long-term damage they’re causing.

The problem isn’t just individual developers, though—it’s systemic. Companies prioritize speed and cost over quality. They want results yesterday, and they’re willing to sacrifice professionalism to get them. This is how bad code becomes the default: it’s cheaper, faster, and no one cares enough to fix it.

The Shrinking Pool of Professionals

What’s worse is that the number of professional developers is actually shrinking. Sure, there are more people coding than ever before, but professionalism? That’s another story. Companies increasingly hire fresh graduates straight out of college—people who’ve never written production-ready software—and then expect them to just figure it out.

I saw this firsthand while working with CS students in a NYC program. These weren’t beginners; they were about to graduate. But most of them didn’t know how to build anything. They understood algorithms and data structures, sure, but they had no idea how to write code that could actually run in the real world. I was shocked. How do you get a CS degree without knowing how to build software?

This isn’t just an education problem. Companies don’t prioritize mentorship or training anymore. Instead, they expect developers to learn on the job, which often means learning from other inexperienced developers. It’s a vicious cycle, and the result is what you’d expect: bad code everywhere.

AI is Pouring Gasoline on the Fire

Enter generative AI. It’s a tool with immense potential, but instead of raising the bar, it’s making things worse. In the hands of a skilled developer, AI can be transformative. It can automate grunt work, speed up iteration, and free up time for more creative problem-solving. But in the hands of someone who doesn’t know what they’re doing? It’s a disaster.

AI doesn’t replace the need for good coding practices. If anything, it demands more discipline. A poorly written prompt produces poorly written code, and if the user can’t evaluate or refine it, the bad output goes straight into production. What we’re seeing now is AI being used to crank out bad code faster than ever before, creating even more technical debt and dysfunction.

This isn’t a knock on AI—it’s a knock on how people are using it. AI isn’t a shortcut to competence. It’s a tool, and like any tool, its effectiveness depends on the skill of the user. But that’s the problem: too many developers think AI can replace the need for skill, and the industry is letting them get away with it.

Why We Need to Prioritize Professionalism

The tech industry has a choice to make. We can keep celebrating speed over quality, or we can start valuing the craft of software development. If we don’t, the future of code is going to look a lot like its past: messy, unmaintainable, and full of shortcuts.

Here’s what needs to change:

1. Mentorship and Training: Companies need to invest in their developers, not just hire them and hope for the best. Mentorship should be a priority, and clean code principles should be part of every onboarding process.

2. Reform Education: Universities and bootcamps need to do better. Teaching theory is fine, but students also need to learn how to write production-ready code. There’s no excuse for graduating with a CS degree and not knowing how to build software.

3. Use AI Responsibly: AI should be a tool for augmentation, not a replacement for understanding. Developers need to treat AI as a junior collaborator, not a magic wand.

4. Reward Craftsmanship: The industry needs to stop tolerating bad code. We should be celebrating developers who take the time to write clean, maintainable software—not the ones who ship things fastest.

The Bottom Line

Bad code didn’t start with AI, and it won’t end with it either. But generative AI has made the problem impossible to ignore. It’s exposed the gap between those who take their craft seriously and those who don’t. And if we don’t address this gap, the future of software development is going to be a mess.

The principles of clean code and professionalism aren’t optional—they’re essential. They’re the difference between a system that works and a system that falls apart under its own weight. AI can be a game-changer, but only if we stop using it as an excuse for mediocrity and start using it to amplify the skills we already have.

It’s time to reclaim professionalism in software development. Anything less is just bad code on repeat.

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