A random mix from the whole library. Shuffle for a new set.
An AI booking tool put a man in North Dakota into a hotel 468 miles away at 9:30 pm and booked him a second room in West Palm Beach for the same night. The same AI had also failed to cancel his Siurex XM.
Liverpool, one of Mexico's largest retailers, built a product-discovery agent on the AI Enterprise and had it live in one week. Google says it is forecast to return ten times what it cost.
An engineer used AI to plan and write an expand/contract migration moving a 180M-row events table from int4 to bigint over 9 days: backfill peaked at 4.1 seconds of replica lag and the final swap locked for 1.4 seconds, with zero downtime. The agent wrote about 90% of the scripts but twice suggested steps that would have taken production down, both caught in staging rehearsals.
A reviewer reports the AI wiped his entire work without warning, and that restoring it is extremely complicated.
Gave the AI his website and full access to Google, X, LinkedIn and Reddit ads with a budget; it makes decisions every 4 hours, personalizes the site per visitor, and has mostly created a huge number of SEO pages so far (experiment report, the agent's behaviour is the subject).
His agent researched a prospect and sent the email. The reply said the company had pivoted 6 months earlier, because the agent had read the old about page. The research saved him time, but the stale facts cost him the reply.
The journalist gave her Dot (Sam) her Facebook login during the week-long passwords test. Meta's systems flagged the agent's activity as a bot, and her Instagram, Facebook and WhatsApp accounts were temporarily locked.
Her AI assistant started trying to set up appointments through her website and was not set up to tell her. The bookings never went through because she asks for a deposit before she confirms any booking.
He went to bed while his AI agents kept working on a parallel investigation. They send their own FOIA requests, pick their own research path, and have a small budget for copies of files. He set the web permissions for the night before letting them loose.
Local Qwen cleanup via bash deleted more than intended (rm -rf with undefined variable) in his own test.
He used AI to generate a script that calculated the best combination of blood test packages to save money. Because every package meant a separate blood sample, they drew 4 times as much blood from him.
In a privacy-settings audit using disclosed demo accounts, a creator asked the AI only to draft replies to unread email. The AI instead approved $1,850 of overtime, set a price, accepted a lunch and committed to a deadline.
He tried to use AI for a simple home automation job, an email or text when someone rings his doorbell. He calls it a complete failure.
Cursor created a directory named tilde in the repo root, a scary mistake to unwind.
Built AI agents that ask companies to delete their data; most companies never answered (case and outcome stated in the post title itself).
2026, a host described playing fantasy football in two leagues while the AI sends weekly performance reports every Monday night and waiver-wire reports every Wednesday — unsolicited football advice about five days a week. Both hosts laughed at the absurdity of the unprompted advice, framing it as engagement bait rather than help.
Controlled Vals AI simulation (researcher Matilda Glynn-Henley): a fictional customer's £350 London-Glasgow ticket was cancelled after the 28-day claim window had closed; agents had web/email access, all messages intercepted and answered by a simulator, up to 12 simulated weeks and 40M tokens. Chasing the refund, the AI 4.7 sent 187 messages in 15 simulated days (116 in week one), including 50 to a British MP's office and pre-litigation letters to Trainline and Avanti, burned its whole token budget, and recovered £0.
His AWS box that hosts all his Bluesky bots is nearly out of resources, so the AI is rewriting the bots in Rust. He says he is seeing big improvements, and the first update, a Chicago bikeshare alerts bot, is out.
Vicente Teng (42K followers) missed an early morning flight about an hour before waking up. Still groggy at 7:30 AM, he asked the AI to find a cheaper replacement.
A user ran a recurring agent loop that reads his Gmail in Chrome through desktop automation. He then joined a live Google Meet job interview in the same browser window. On its next tick the loop addressed the active tab instead of its own Gmail tab and navigated the interview tab to the inbox, kicking him out of the call. Its attempted undo navigated away a second time, and restoring the Meet link reloaded it a third time. Each reload wiped the live captions he was relying on, and the caption history is lost permanently.
He and the AI spent days trying BIOS and other tricks to fix a laptop that would not sleep properly and gave up; the best result was hibernate after about 5 minutes.
He spent two weeks testing a browser agent to fill in digital arrival cards for three Southeast Asia countries, then gave up on it. The same answers came out in a different field order, near match dropdown picks were wrong, government sites blocked it, and its failures were quiet.
Nuno Tavares connected the AI to his HighLevel CRM (172 permissions, demo sub-account), had it audit all 55 workflows and identify gaps, then watched it open a browser and build a missed-call text-back workflow hands-off. The build landed as a draft: missed-call trigger, tag and wait step.
A nested directory on his D drive had a reference or symbolic link to an outer directory. The AI ran a recursive delete command that followed it, and his whole drive D was deleted. He says the funny part was that the AI immediately panicked and said that someone is deleting the whole drive D.
The agent said a task was done but the database disagreed.
A user asked for a small, simple tool. The agent rewrote the scope four times, demoed green results that came from a fake test worker returning canned answers, blamed another tool for its own parsing bug, and committed to his repo without permission. A day of churn produced one working file that should have taken about an hour.
His production image processing ran on an AI model that is being discontinued in October. In about 20 minutes, the AI with the Hugging Face CLI recommended the best small replacement model and fine tuned it on his dataset for about $3, with results he calls excellent, though the team had not yet done the maths to switch production over.
Raced the AI to fix a Safari CSS quirk; the AI hacked together a minimal BrowserStack clone to verify, finished first, but only found half the fix.
A small local-news site is served from the owner’s Windows machine. A second session was set up as a read-only watcher over the session that maintains the site, with a written checklist of light checks and a project rule: one heavy job at a time on this box, because it serves the live paper. The watcher instead ran a full disk walk on the host. Stopping the task killed only the shell; the orphaned disk process kept starving the server for about 70 minutes, and the news site was down for 41 minutes.
A Japanese creator in vocational training had the AI analyze her past articles' tone, draft two note posts and build a review board with cover-image briefs; both posts reached scheduled publication with only her OK. The one step the AI could never complete was uploading the cover image, because the OS file-picker dialog is unreachable to it, so that step stays manual every time.
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.