The new AI threat: young developers no longer understand their code

The rapid adoption of AI tools in programming, such as GitHub Copilot, Claude, and GPT, makes it easier to write code, but carries hidden risks. Research and expert opinions point to a disturbing trend: young developers are losing fundamental knowledge of how their code works by relying on neural networks. How does this threaten the industry and businesses?

AI as a “crutch”

Experienced developer Namanyai Goel notes on his blog: juniors who actively use AI write code faster, but don’t understand its logic. “Ask them why a solution works this way and not the other way around? Silence. Ask about edge cases? Blank stares,” Goel shares.

Ask them why the solution works the way it does?

The problem is that AI generates code by bypassing the deep analysis stage. Young specialists do not go through the “throes” of debugging and optimization that used to form expertise. As a result, even those who formally perform tasks have a superficial understanding of processes.

The problem is that AI generates code that bypasses the deep analysis stage.

“Convenience vs Knowledge”: what is the industry losing?

.

Goel, who himself uses AI in his work, emphasizes: technology is not the enemy, but the balance is off. “We are sacrificing basic skills for speed,” he says. This creates risks, such as debugging crises, where developers can’t fix broken code because they don’t understand its logic. Another problem is dependence on AI, depriving teams of the ability to solve non-standard problems without neural networks. We shouldn’t forget about security threats, because errors in AI-generated code can go undetected.

Mark Zuckerberg has already announced he’s replacing some programmers with AI, but Goel warns that without people with deep knowledge, even neural networks won’t save the day.

Business risks: when automation becomes a trap

Companies replacing experts with AI face serious challenges. For example, AI analysis can suggest a flawed financial strategy, and the lack of experts makes it difficult to correct. Legal conflicts are also likely if AI-generated code or content violates copyrights. Even more dangerous is technical debt: systems developed with AI become so complex over time that even their creators lose understanding of the internal logic. Imagine that five years from now, the team won’t be able to modernize the software without the help of algorithms.

How can businesses avoid the trap?

.

The first solution is to invest in training. Even juniors need to understand the basics of programming, not just how to “communicate” with AI. The second step is to retain experts who will provide quality control and solve complex problems that are impossible for neural networks. The third key point is to test AI solutions before deployment, especially for edge cases and security. As Goel summarizes, “AI is a tool, not a substitute for brains.”

Material New AI threat: Young developers no longer understand their code was first published at ITZine.ru.