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.

翻译：编写代码一直是人类社会将抽象思想转化为具体技术最具变革性的方式之一。现代人工智能正在改变这一过程，使专家和非专家都能在不实际编写代码的情况下生成代码，转而使用自然语言指令或"氛围编程"。尽管日益流行，但氛围编程对生产力和协作的影响，以及人类在此过程中的作用，仍不明确。本文引入了一个受控实验框架来研究协作式氛围编程，并利用该框架比较了人类主导、AI主导和混合型小组。通过涉及737名人类参与者的20项实验，我们发现人类能为氛围编程提供独特有效的高层指令，而AI提供的指令常导致性能崩溃。我们进一步证明，当人类通过提供指令来主导、同时将评估工作委托给AI时，混合系统的表现最佳。尽管AI系统能针对特定任务快速优化性能，但我们的研究强调了人类引导在塑造未来混合型社会中的重要性。