AI coding work is changing rapidly and the positive impacts are not uniform.
A study published in Science suggests that AI-powered coding is now integrated into everyday software creation on GitHub. The authors tracked Python development over time and used a specially designed detector to flag code that likely came from generative assistants such as ChatGPT or GitHub Copilot.
For young developers, the signal is chaotic. Newer programmers rely more heavily on these tools, but the most noticeable performance gains are seen among experienced programmers. In other words, AI tends to reward people who already know how to control it.
How the study tracked AI code
Instead of relying on surveys, the analysis focused on Python features published on GitHub and tracked how individual developers changed over time. The method focused on a trained model designed to identify patterns associated with AI-generated code.
This allowed researchers to compare adoption across different countries and experience levels, and then link usage to outcomes such as commit activity and the range of libraries used by developers. It watches what appears in real repos, not what people say.
Why experience changes payoff
Here’s the hard part. Generative coding tools don’t behave like a universal boost. Less experienced developers seem to use them more often, but the measurable benefits are concentrated among experienced developers, including higher performance and broader library usage.
A likely explanation is judgment. Experienced developers tend to ask tougher questions, spot errors more quickly, and know when to ignore an answer that seems plausible. In this sense, AI coding work reinforces informed decision-making, not just speed.
What you should do next
If you’re early in your career, treat a copilot like a calculator, not a shortcut. Use it to design sample examples, explore unfamiliar libraries, and run tests, then have each line you keep explained to you. If you do this consistently, you will learn faster than if you just ask. Check out the best AI tools for coding.
If you’re looking for a job, prove that you can evaluate code, not just generate it. Clear READMEs, disciplined commits, and thorough code reviews will become more important as AI-powered coding becomes commonplace. Watch out for interviews where debugging and verification are more important than memorized syntax.
