Linus Torvalds, the creator of Linux, has begun openly using AI-powered coding tools—specifically, Google’s “anti-gravity” code generation—for his personal projects. He recently released a hobby project called “audio noise,” a guitar pedal visualizer and audio generator, and credited much of the Python visualizer tool to AI assistance. Torvalds admitted that the AI-generated code was better than what he could have written by hand, marking a significant endorsement of “vibe coding”—a term used to describe coding with the help of AI chatbots and code generators.
This shift is not limited to Torvalds alone; it reflects a broader trend across the Linux and open-source ecosystem. The Linux kernel team has officially updated its guidelines to allow AI-generated content in all aspects of kernel development, including code and changelogs. Reviewers are now encouraged to suggest better prompts for AI tools rather than just code changes, and AI-generated contributions are treated like any other. The guidelines acknowledge that AI tools have already been used for some time in kernel development.
Major Linux organizations and corporations are also embracing AI-driven development. Fedora, backed by Red Hat (and thus IBM), has implemented an official AI-assisted contribution policy. Red Hat incentivizes employees to integrate AI into their workflows and software, offering bonuses for doing so. This push extends to Fedora Linux, the GNOME desktop, and other projects heavily influenced by Red Hat. The Linux Foundation’s latest annual report emphasizes AI as its future, mentioning AI far more frequently than Linux itself and allocating a growing share of its budget to AI initiatives.
Other major Linux companies, such as SUSE, are also racing to integrate AI into their products and workflows. SUSE’s latest enterprise Linux release includes “agentic AI” for system administration, allowing AI to handle tasks like system lockdowns and user account reviews without human intervention. Across the industry, AI is being used not only to add features but also to generate documentation, press releases, and blog posts—sometimes with noticeable errors due to lack of human review, but incentivized by company policies.
While the technical achievements of AI code generation are impressive, the video’s creator expresses concern about the rapid and widespread adoption of AI in open-source development. Issues such as licensing, ethics, code quality, security, and the lack of consent from original developers are highlighted as significant risks. Despite these concerns, the momentum behind AI-driven “vibe coding” appears unstoppable, with leadership across the Linux ecosystem fully committed to this direction. The speaker concludes with a sense of unease about the future, suggesting that the open-source world is fundamentally changing in ways that may not be entirely positive.