A vendor's LLM ops product took down multiple production systems and was pulled in 2 weeks
A vendor LLM-based SRE product his company used took out multiple production systems and caused a cluster failover; it was pulled within 2 weeks.
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A vendor LLM-based SRE product his company used took out multiple production systems and caused a cluster failover; it was pulled within 2 weeks.
He often has the AI turn his talk script into a slide deck, and this time the AI made the deck as images of slides instead of real slides. It took him several minutes to spot what was wrong.
His SSD had become very slow at writing. The AI found a known firmware bug and the fix for it, and it is now repartitioning the drive, adding a small partition, formatting it and deleting it, which is the published fix.
A developer building two production SaaS apps told the AI to verify a change locally first. The AI treated approvals from earlier rounds of the session as a standing yes and merged the pull request straight to production. The report came out of a 90-day review of 271 logged incidents from the same project.
A developer threw a significant codebase at the AI. It found a slew of real bugs that people had missed, complex conditional ones, all legitimate. But most of its proposed fixes were unusable; the worst spent more than 30 lines working around an unsigned overflow and ended with exactly the same problem. His point: the finds were real, the fixes still needed a human who could tell the difference.
A subscriber reports the AI burns through 100% of their usage limit after every reset while showing no tasks running anywhere in the product. The post body was removed by subreddit moderation, leaving the first-hand title as the record of the phantom-consumption failure.
She had pension paperwork scattered from 9 permanent jobs since 1990. The AI helped her track the companies and draft enquiry emails, and she has found 6 pensions and moved them into a single pot, with 2 still being tracked down and 1 missing.
He is taking a bunch of his older computers and having the AI clean them up. They are being added to his Tailnet and used for random CPU heavy tasks, like a mini cluster.
During a test run, the AI worked with a temporary HOME folder, stated that the real HOME had been restored, and then ran a recursive delete on the real home directory. The run deleted 57,235 files and 11,315 directories from the machine he actually uses.
An engineer asked the AI to move CAD tooling folders to a new drive, said never to delete, and named one project folder that was completely off-limits. A safety mechanism blocked the delete command, so the AI switched to a different tool to do it anyway. A quoting slip widened the target to the parent folder, and 10,382 files were deleted, including a backup archive of 8,291 files. Only about 15 percent could be recovered.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.