Developers blame AI for code errors: a growing trend

As artificial intelligence tools like GitHub Copilot become more common in software development, a new and troubling trend is emerging: developers increasingly shift the blame for buggy or poor-quality code onto the AI. While these tools offer productivity boosts, they also introduce a risky temptation—using AI suggestions as an excuse for subpar work.

AI is helpful, but not a substitute for human judgment

Many developers use GitHub Copilot to generate code snippets and automate repetitive tasks, making their workflow faster and more efficient. However, experienced developers warn that blindly accepting Copilot’s suggestions can introduce subtle bugs and security flaws. On the subreddit r/ExperiencedDevs, one senior developer shared their frustration: “I’m tired of hearing ‘Copilot suggested that’ when I point out errors.”

The core issue is that Copilot is only a tool—it does not absolve developers of responsibility. While some newer programmers may over-rely on AI, believing it to be a shortcut, veterans stress the need for critical thinking and a deep understanding of programming fundamentals. Code must always be reviewed and understood by the developer who commits it, regardless of its origin.

A generational divide in development practices

This debate has also highlighted a growing gap between those who learned to code before AI tools and those who started with them. The former group tends to value methodical, hands-on coding, while the latter sometimes uses AI to bypass deeper learning. Despite these differences, most developers agree on one point: responsibility lies with the human, not the machine.

GitHub Copilot can be a powerful ally, but only when used with intention and care. In the end, AI should enhance human decision-making—not replace it.