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World of Software > Software > What makes good vibe coders?
Software

What makes good vibe coders?

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Last updated: 2026/05/04 at 5:49 AM
News Room Published 4 May 2026
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What makes good vibe coders?
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In a study with a hundred students, three researchers from ETH Zurich examined which skills lead to good results in vibe coding. It turned out that knowledge of computer science and good language skills are helpful. Surprisingly, the participants who used AI more frequently in everyday life delivered worse results.

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For the study, Sverrir Thorgeirsson, Theo Weidmann and Zhendong Su gave the hundred students who had already completed an introductory course in computer science three vibe coding tasks: They were supposed to recreate an app for planning meals, add new functions to an app for organizing their own university courses and also recreate an abstract app with no apparent purpose.

In order to better classify the results, the researchers also tested the participants’ general cognitive abilities, their computer science knowledge and their written expression in a short essay.

Computer scientists code better vibe

The result shows that computer science knowledge had the greatest influence on the successful solution of the tasks. This effect remained even when the researchers leveled out the differences in students’ general cognitive abilities. However, the study only shows a correlation and does not provide any information about the causal relationships. However, the scientists suspect that people who better understand how programs work can also give instructions to an AI more efficiently.

Language skills were also advantageous. Students who can express themselves better and in a more structured way also write more successful prompts. Unclear or imprecise wording, on the other hand, is more likely to result in faulty programs.

High prompters are worse

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A surprising finding was that students who use AI particularly often in everyday life performed worse both in writing essays and in vibe coding. The study also does not explain why this is the case. For the authors, it is conceivable that the frequent use of language models weakens their own ability to express themselves. Conversely, students who have difficulty writing could also use AI tools more quickly.


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