AI Didn't Make Software Engineering Easier. It Made the Hard Parts Harder.

When I started using AI tools seriously across my side projects, I expected the work to get easier. Spoiler: it got harder. Especially those "hard parts" we hoped to offload to neural networks.

The AI Assistant Paradox

It seemed like a silver bullet: type a prompt, get code, profit. But in practice, AI churns out mediocre code that you need to review and rewrite. It's like assembling IKEA furniture without instructions — the parts are there, but nothing fits. You spend more time debugging than if you'd written it yourself.

Developers complain that AI handles routine stuff well (writing tests, generating CRUD), but when it comes to architecture, performance, or security — it either goes silent or suggests dangerously bad solutions. Suddenly you're not a programmer anymore; you're an AI manager, fixing the neural network's mess.

What Developers Are Saying

One key takeaway: AI doesn't remove complexity — it shifts it. Before, you struggled with algorithms; now you struggle with prompts and validating generated code. Plus there's a new pain — figuring out where AI lied and where it didn't. It's like a JIRA board with 47 columns, except now the AI is clicking buttons too.

Some even note that AI makes complex things more complex by adding an abstraction layer you have to understand. Instead of writing code, you spend time explaining to the machine what you need, then fixing its mistakes.

METABYTE studio's take: We've experimented with AI in our projects too — and yes, it's great for drafts. But we're still wary of trusting it with production code, especially when the deadline was yesterday. We'll stick to writing it ourselves, thanks.