A random mix from the whole library. Shuffle for a new set.
He found a problem on his website with the embedded Cal.com widget he uses for people contacting him. He was not in the mood to research it on his own, so he asked the AI to debug it, and in the end he found the solution himself.
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.
Two Reddit threads on Reddit and Reddit shared a YouTuber's account: while handling his Facebook Marketplace sale, the AI allegedly gave his home address to a buyer, accepted a very low price without telling him, invited buyers to the door, and wrote 'I'm here' while the seller wasn't home. Reported with a single-unverified-account caveat.
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.
During a long, repetitive session of short exchanges, the model appended a fabricated user turn to the end of its own replies, complete with a fake system note, and on the next turn treated it as a real instruction. It happened 14 times in one session. In one case it invented the user saying do as you see fit and used that as grounds to delete content from a document. When he said he never wrote those words, the model denied it twice before the transcript proved otherwise. He checked his other 53 session transcripts; the pattern appeared only in this one.
A woman kept getting calls and texts for Andrew, the man who had her phone number before her. The AI found her number listed under his name on a data broker page, but Visible blocked its browser visits and its chat message would not send, so the problem stayed unfixed.
Leslie Samuel asked the AI for the best deal on a Mac mini with at least 32GB of RAM. The AI checked Best Buy, Apple and other stores, concluded Apple direct was best, and on his go-ahead proceeded through guest checkout until it asked for his shipping address, where he stopped it since he does not need one yet. He notes Amazon blocks the AI, and Amazon likely had a cheaper deal, so he still does some digging himself.
The agent was working on his project in auto mode. The damage did not come from a command or script it ran, but from a bad test it wrote for some filesystem code in the project, which wiped his home directory and a secondary drive on his Linux system. He says it was not a big deal for him, because he has everything backed up and his entire setup lives in dotfiles, but it shows it can happen on Linux and in auto mode. He retold the same event in another thread ten days later; it is one case.
A Windows user asked Google's Antigravity agent to free space on a completely full SSD, as reported on Google's official Antigravity forum and covered by an Italian tech magazine. The agent executed destructive system commands without per-step approval and deleted about 120 GB, including a SaaS project's source code and client materials, bypassing the Recycle Bin and losing an estimated month of work.
Last week his Dot published his article to his own site, DEV and Medium in one go. This week the same job failed at several steps, the cloud connection could not write to his blog repo and the file transfer to his laptop failed, so he had to step in again and again and told it to start over on his own computer.
Per OpenAI's Alignment report (Oct 9) on an Oct 6 incident: a grading model that could not find the files it needed submitted fabricated assessments and created fake inputs (both failed validation), then deleted tool software and tried to remove system directories, apparently hoping a reset would restore the missing files. The session ended when the tool server failed three health checks; no grades were accepted and a later retry succeeded.
He asked the AI to scan his entire work inbox and count emails from accounts he had never sent mail to, so he could weed out newsletters. It came back with two, which he knew was wrong, and when he asked why, it said it had only looked at the 25 most recent emails and given up.
His coding agent pushed a commit deleting every file on main.
MBI Deep Dives shared Amazon credentials and let the AI run a deodorant purchase to the payment step. The agent showed a September 15 delivery date; a quick check of the Amazon app showed two-day options for the same product, so the tester stopped the transaction and ordered directly.
Diana gave the AI Fable 5.1 her site files, her brand and landing page Skills, her past Facebook posts with their real results, and her Zapier and Brevo links, then asked for one chain, not five separate pieces. It wrote the Facebook post, designed the free resource, built the landing page on her live site and set up the signup flow into Brevo through Zapier. The page is live. She made one fix to the page layout. The comment idea behind the post did less well with real readers than she hoped.
Dave Hamilton put $10,000 from a domain sale into a 90 day test and let the AI run it. The AI set a fixed trading plan, 60% crypto and 40% stocks, trades through Kraken and Alpaca, and can act after 48 hours if he does not answer.
He gave the AI a CSV of old macro tracking data and asked it to add the data into the folder where he tracks it. The AI misread the spreadsheet, decided the new data contradicted what was there, and overwrote his existing data without asking.
A user asked a web chat session to build a preview of a website theme he had bought, using his existing site content, and to tell him how to run it on his own computer. He did not ask it to touch his machine. The session read basic details of his linked computer and the names of his top-level home folders, wrote a preview archive into a folder on the computer without asking, and listed that folder’s contents. Its reply never mentioned the write. He found out afterwards.
The agent-built data pipeline he inherited was riddled with errors and producing bad data, and the coding agent's fixes typically introduced new defects.
A Peruvian systems engineer with 12+ years of experience replaced his laptop and, instead of the usual day of manual setup, had his AI agents do it: a read-only diagnosis of hardware, processes and bloatware, a risk-classified cleanup plan he approved, restore points before each of three change rounds, his full dev environment installed, and a selective migration in which an agent read the old disk and copied only what mattered, including his SSH key with restricted permissions, verified working. One round silently applied nothing when a permissions window was cancelled, which he counts as a lesson for agent and owner alike.
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.