Why Human Guidance Matters in Collaborative Vibe Coding
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866918375026851840 |
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| author | Hu, Haoyu Marjieh, Raja Collins, Katherine M Li, Chenyi Griffiths, Thomas L. Sucholutsky, Ilia Jacoby, Nori |
| author_facet | Hu, Haoyu Marjieh, Raja Collins, Katherine M Li, Chenyi Griffiths, Thomas L. Sucholutsky, Ilia Jacoby, Nori |
| contents | Writing code has been one of the most transformative ways for human societies to translate abstract ideas into tangible technologies. Modern AI is changing this process by enabling experts and non-experts alike to generate code without actually writing it, instead using natural language instructions or "vibe coding". While increasingly popular, the impact of vibe coding on productivity and collaboration, and the role of humans in this process, remains unclear. Here, we introduce a controlled experimental framework for studying collaborative vibe coding and use it to compare human-led, AI-led, and hybrid groups. Across 20 experiments involving 737 human participants, we show that people provide uniquely effective high-level instructions for vibe coding, whereas AI-provided instructions often result in performance collapse. We further demonstrate that hybrid systems perform best when humans lead by providing instructions while evaluation is delegated to AI. Although AI systems can rapidly optimize performance for specific tasks, our work highlights the importance of human guidance in shaping future hybrid societies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_10473 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Why Human Guidance Matters in Collaborative Vibe Coding Hu, Haoyu Marjieh, Raja Collins, Katherine M Li, Chenyi Griffiths, Thomas L. Sucholutsky, Ilia Jacoby, Nori Human-Computer Interaction Artificial Intelligence Social and Information Networks Writing code has been one of the most transformative ways for human societies to translate abstract ideas into tangible technologies. Modern AI is changing this process by enabling experts and non-experts alike to generate code without actually writing it, instead using natural language instructions or "vibe coding". While increasingly popular, the impact of vibe coding on productivity and collaboration, and the role of humans in this process, remains unclear. Here, we introduce a controlled experimental framework for studying collaborative vibe coding and use it to compare human-led, AI-led, and hybrid groups. Across 20 experiments involving 737 human participants, we show that people provide uniquely effective high-level instructions for vibe coding, whereas AI-provided instructions often result in performance collapse. We further demonstrate that hybrid systems perform best when humans lead by providing instructions while evaluation is delegated to AI. Although AI systems can rapidly optimize performance for specific tasks, our work highlights the importance of human guidance in shaping future hybrid societies. |
| title | Why Human Guidance Matters in Collaborative Vibe Coding |
| topic | Human-Computer Interaction Artificial Intelligence Social and Information Networks |
| url | https://arxiv.org/abs/2602.10473 |