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Linus Torvalds Embraces Generative AI for Coding After Initial Skepticism

Linus Torvalds has publicly shared his evolving views on generative AI tools for programming during the Open Source Summit Europe. The Linux creator noted that AI assistance makes small personal projects more enjoyable by accelerating the path from idea to working result. He described using an AI model to modernize the outdated C-based user interface of a custom guitar pedal project. Initial AI output proved unusable until Torvalds supplied the existing implementation and clear instructions on required changes. Torvalds emphasized that AI helps newcomers achieve tangible outcomes that feel meaningful compared to professional-grade software. At the same time he urged caution when applying these tools to serious kernel development work. He also highlighted the growing burden on maintainers who must review increasing volumes of low-quality, AI-generated vulnerability reports and superficial patches.

AntiMalwareTranslated from Russian

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Linus Torvalds has revealed that he now finds generative AI tools genuinely useful for programming tasks, marking a notable shift from his earlier skeptical stance toward such technologies.

Speaking at the Open Source Summit Europe, Torvalds explained that AI assistance proves especially valuable in areas where he personally lacks deep expertise. As reported by ZDNet, he illustrated the point with a recent personal project involving a custom guitar pedal.

The original interface, written in C, functioned correctly but appeared outdated. Torvalds turned to an AI model to refresh its appearance and functionality. The first attempt produced results he described as terrible, forcing him to provide the existing code implementation along with precise guidance on what needed to change.

According to Torvalds, this form of AI-assisted or “vibe coding” restores the enjoyment of working on smaller projects. He observed that beginners often struggle to view their experiments as worthwhile when compared with mature professional software, yet AI tools enable faster delivery of concrete, working results.

For critical and high-stakes development, however, Torvalds strongly advocates a cautious approach. He pointed out one significant downside of widespread AI adoption: while the tools can help identify vulnerabilities, they also generate large numbers of questionable reports and superficial fixes that burden kernel maintainers.

LinuxLinus TorvaldsZDNet
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