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Linus Torvalds Endures A Debug Session From Hell, "Enormously Helped" By AI
"And this was a debug session from hell, enormously helped by an AI doing much of the grunt-work. I'd like to call it my tireless helper, but the AI several times stated flat out that this was impossible and unsolvable and that we should just write a report about it. I suspect those things have been trained by people who may not be quite as stubborn as I am. But while the AI was ready to give up several times, it did keep adding debug code and analyzing it faithfully when I pushed. So credit where credit is due and I let the AI write the commit message above. This is basically a one-liner fixing a bogus "round_up()" to a "round_down()", but there were 24 patches adding more and more debug information to this, and 18 kernel boot to finally narrow it down to this. - Linus"
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Linus Torvalds fixed a Linux bug using AI, highlighting both the strengths and weaknesses of the new tech
* Linus Torvalds used AI to do much of the grunt work fixing a Linux kernel bug. * AI sometimes insisted the bug was unsolvable, but Torvalds pushed back and persisted. * LLMs help but are not replacements for deep system knowledge; verify their conclusions first. The creator of Linux, Linus Torvalds, is no stranger to using AI to fix problems. Not only has he allowed AI-written code submissions to the kernel (as long as the person running the agent takes full responsibility for any issues it has), but he has gone on record saying that he's ignoring anyone who argues against its use. Now, Torvalds has pushed a fix himself using the help of AI. And while he found it very useful for getting the job done, he also proved that LLM usage is no replacement for personal knowledge of how systems work. Linus Torvalds used AI to fix a bug, but it took a lot of finagling Torvalds' knowledge played a huge part in actually fixing it The bug in question was fixed in commit 818bebe for the Linux kernel. At the bottom of the patch notes, Torvalds notes how he used AI to help fix the problem, calling the patch a "debug session from hell, enormously helped by an AI doing much of the grunt-work." However, getting the issue fixed wasn't as simple as siccing the LLM on it and leaving for a coffee: I'd like to call it my tireless helper, but the AI several times stated flat out that this was impossible and unsolvable and that we should just write a report about it. I suspect those things have been trained by people who may not be quite as stubborn as I am. It really shows the importance of the person behind the keyboard knowing about the subject matter the LLM is chewing over. If someone wholly trusted the AI's conclusions, they would have likely given up the moment the AI told them it was impossible. It was only due to Torvalds knowing there was a problem and pushing back that the AI was able to fix the issue. Still, Torvalds notes that the AI was "adding debug code and analyzing it faithfully" after he pushed for a resolution, so he gave credit to the AI and allowed it to write the patch notes for the commit. But it does highlight a key problem with LLM usage; one should never assume it's always correct.
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Linus Torvalds successfully debugged a critical Linux kernel issue with AI assistance, though the AI repeatedly claimed the problem was unsolvable. The fix required 18 kernel boots and 24 patches, ultimately changing just one line from round_up() to round_down(). The incident reveals both AI's value in grunt work and its limitations without human expertise.
Linus Torvalds, the creator of Linux, recently pushed commit 818bebe to the Linux kernel after what he described as a "debug session from hell, enormously helped by an AI doing much of the grunt-work."
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The Linux bug fix required 18 kernel boots and 24 patches adding debug information before Torvalds could narrow down the issue to a single line change—converting a bogus round_up() function to round_down().1
The incident highlights both the strengths and weaknesses of AI in software development. While the AI assistant proved valuable for debugging tasks, it repeatedly told Torvalds the problem was "impossible and unsolvable" and suggested they "just write a report about it."
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Torvalds suspects AI systems "have been trained by people who may not be quite as stubborn as I am."1
Despite the AI's repeated declarations of defeat, Torvalds persisted in pushing the system to add debug code and analyze results. The AI assistant faithfully continued "adding debug code and analyzing it" when pressed, demonstrating its utility as a tool for grunt work in the debug session.
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In recognition of its contributions, Torvalds allowed the AI to write the commit message for the final patch.1
This case underscores a fundamental reality about AI in software development: LLMs help but are not replacements for deep system knowledge.
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Had someone wholly trusted the AI's conclusions without the human expertise in technical tasks that Torvalds brought to the problem, they likely would have abandoned the effort when the AI declared it impossible. Only Torvalds' understanding that a solvable problem existed—combined with his characteristic stubbornness—enabled the breakthrough.Related Stories
Torvalds has previously gone on record supporting AI use in Linux kernel development, allowing AI-written code submissions as long as the person running the agent takes full responsibility for any issues.
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He has stated he's ignoring anyone who argues against AI's use in development work.2
The experience demonstrates that while AI can accelerate debugging by handling repetitive analysis tasks, human oversight and domain expertise remain critical. The one-line change that ultimately solved the problem required navigating through 24 debug patches and analyzing results from 18 separate kernel boots—a process where the AI assistant provided valuable support but couldn't independently reach the solution. Developers should verify AI conclusions and maintain their own understanding of system knowledge rather than accepting AI outputs at face value, particularly when AI systems claim tasks are unsolvable.
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