There’s a lot of buzz around AI coding tools and how they help developers write code faster and more accurately. But some experts are asking whether relying on AI might come at a cost. Recent research from Anthropic looked into how using AI impacts learning new programming skills, especially for less experienced developers. The findings suggest that while AI can make coding quicker, it might also hinder developers’ understanding of what they’re creating.

Testing AI’s Impact on Learning New Skills

The researchers conducted a controlled experiment with 52 junior developers. They split these participants into two groups: one was encouraged to use AI assistance, while the other was asked to code without it. Both groups worked on a task involving the Trio library, a relatively new asynchronous Python tool that they weren’t familiar with. The goal was to see how well they learned and understood the library after completing the task.

The participants had a set amount of time to familiarize themselves with the tools and then to build two features using the Trio library. Afterward, they took a quiz to test their understanding of debugging, reading, and writing code, as well as grasping core concepts of the library. The AI-assisted group had access to an embedded AI helper that could suggest code snippets and fix issues, while the other group relied solely on their knowledge and skills.

Findings Raise Concerns About Skill Development

The results showed a clear difference in performance. Those who used AI scored significantly lower on the quiz—about 17 percentage points behind the group that coded by hand. In practical terms, this was nearly two letter grades lower, despite having just worked on similar concepts moments before. The biggest gaps were in debugging and understanding why code failed or was incorrect.

This is concerning because it suggests that developers who heavily rely on AI might not develop strong skills in analyzing and validating code. If they don’t fully understand what their AI-generated code is doing, they may struggle to identify errors or optimize their work later. The researchers warned that overuse of AI during learning could lead to a future workforce less capable of debugging and designing reliable software.

The Longer-Term Implications for Developers

The experiment lasted about 70 minutes and was designed as a self-guided tutorial, with participants receiving instructions, starter code, and explanations for the new library. They worked on real coding tasks and could ask the AI for help at any time. The researchers monitored how much time was spent coding versus asking the AI for assistance, providing insight into how developers interact with these tools in real-world scenarios.

While AI can save time and help produce correct code quickly, the study highlights that it might also discourage active learning. Developers may become more dependent on AI helpers rather than thoroughly understanding the code they write. This reliance could weaken essential skills like debugging, troubleshooting, and understanding software architecture.

As AI tools become more common, developers and teams will need to find ways to balance speed with skill development. Using AI as a learning aid rather than a shortcut might be key to ensuring programmers maintain strong foundational skills while benefiting from automation. Ultimately, AI should complement human expertise, not replace the critical thinking that underpins good software development.

Inspired by

• https://www.infoworld.com/article/4125231/ai-use-may-speed-code-generation-but-developers-skills-suffer.html

Sources

• shutterstock.com
• arxiv.org
• nwai.co
• anthropic.com
• anthropic.com