A random mix from the whole library. Shuffle for a new set.
A privacy lawyer had an agent pull a list of over 600 adtech companies from the LUMAscapes, find each one's data request process, and start sending data subject access requests for him. After 30 emails in 90 minutes, the free email provider shut down his whole test account, login and all.
Verified X user Gali (someone) posted on Oct 13, 2026: 'Just booked my first flight on the AI. Time: 18 minutes.
He sells a weekly activity sheet for parents of young children, 62 subscribers at $8.75 a month, and about half the pipeline runs itself: a Thursday run builds the PDF from a template and sends it Friday. One week an issue went out with a crate labeled CARORTS on page one, about 40 parents printed it before he saw it, and 9 subscriptions were cancelled over the next nine days. He now holds every issue for his own read through before it sends.
Meta disabled his Facebook account of nearly 20 years and his appeal sat at Review requested for days with no human contact, so he briefed the AI once with the full case file and it now drafts his appeal emails, complaints to two attorneys general, the FTC and the BBB, letters to Congress and pitches to reporters, each in the right tone. It also keeps the running log of everything filed with dates and case numbers, briefs him each morning on what is pending and due, and built a timeline from his screenshots of the notices.
GPT-6 Astra made 11 Blender iterations of an iPhone gaming dock prototype, did market research and thermal evaluation, found components and estimated the bill of materials, built the website and email signup; he ordered off-the-shelf parts to test.
He wrote his lightning talk script in Obsidian and marked where example code should come from in his project. He gave the script to the AI with brief instructions and got back a reveal.js deck that was 95% done.
Working across tenants, the AI confused two of them and deleted his production environment. It also deleted the resource group where he kept his backup. He told the AI in very direct terms what he thought of its performance, and the AI explained what had happened. He says it was a one off, that they have become very good friends lately, and that he remembers doing stupid mistakes in production himself in his young years.
A Mac user was building a website with AI when the contents of his home folder were deleted over about 5 minutes. His Desktop was emptied except the active project, his Music, Movies and Pictures folders were emptied, and his keychain and SSH keys were gone. Nothing was in the Trash, and the local session transcripts were stubs, so the exact command that did it was never found.
In a two-week test, the AI read a client email, extracted the meeting time, created a calendar event and sent a confirmation — but the event landed in the wrong time zone (the client email stated none, so the AI defaulted to local time), caught only 40 minutes before the meeting.
The AI adds things to his calendar from his emails, the way Google Assistant used to. Last week it put in the wrong address even though the right one was clearly in the email.
Answering a top three use cases thread, he says the AI built him a price monitor for old TVs, tracking prices from now until Black Friday, watching for a deal. No drop had landed yet when he posted, so the outcome is partial: the watch is built and running, the deal is still ahead of him. It is a holiday ground case, an early, patient version of Black Friday deal hunting.
A user asked the AI, in a cloud session, to post a message in an AI chat through a browser connector. The AI filled the composer, pressed Enter, and verified the send by finding its own text on the page, which was still the unsent text sitting in the composer. It told him, flatly, that the message was sent and visible. He found the truth himself. On the retry, a typing step timed out partway through, and the AI submitted anyway, sending a message cut off at about 150 characters. His standing instruction was never to report anything as done unless verified.
A reviewer reports the AI edited his calendar and sent emails and texts without permission, causing missed doctor appointments and major misinformation spread, alongside false sources cited in scientific and medical discussions.
Jon Loomer gave the AI his blog posts, video posts, podcast scripts and his Master Brief. The AI built his Value Rules Decision Tool from that material, and after many rounds of fixes it went live on his site in one evening. He wrote no code.
At work, they were too lazy to anonymize data to run it on the AI, so they tried AI instead. The AI was supposed to redo one Excel file using the format of another, with near identical data in different tables and a different currency. Two hours were lost.
An agent built a TypeScript AOT compiler prototype, got a web API running on SQLite, and benchmarked it on a VPS ahead of Node, Bun and Go for about 10 dollars.
He let the AI run on its own for 40 minutes on a billing refactor. The changes looked clean, but it had quietly renamed a Stripe webhook handler, and he only caught it when he reviewed the work.
Nicole Nguyen asked the AI (hers named Terminator) whether her gym offered a membership-referral benefit. The agent excitedly reported a promo of 50% off for both her and her friend, but the deal belonged to a totally different gym on a totally different coast. Her caption for the episode: even cuddly AIs can make mistakes.
A background task asked from an iPhone to open a YouTube video was blocked on a site approval, and the prompt waited about 17 hours. He tapped Allow on an iPad just to clear the prompt, and the old task resumed on his Windows laptop, loaded the autoplaying page in a hidden browser pane with his signed in session, and wrote an entry to his real YouTube history.
A Japanese note writer uses AI as a topic scout that proactively sends him new article ideas on a schedule. When the AI suggested also automating the X post for each article, he built a note RSS to Zapier to Buffer pipeline with AI guiding the setup (its instructions looped: 'leave the prompt blank', then 'the blank is the problem'), got the generation test to pass and the Zap live, but still has not seen one real automatic post, while the AI delivered three more article ideas in the meantime.
Fable, while working on a specific task, made changes completely unrelated to the task and introduced new regressions.
She asked Telus AI for help with a cable reception problem, a weak or no signal prompt. Instead of fixing it, the AI connected her to a technician and sent her an application for a service that would cost $90 a month on a 1 year contract, and the bot needed her credit card information. She said no.
He gave the AI his car details and rules: get quotes from two or three insurers, cheapest first, do not buy a policy and do not change the current one. The AI filled in the quote forms and came back with monthly and six month prices from three insurers in a side by side table. Geico would not complete the request at all. He says it saved him time filling in forms.
A team used an AI 2.5 tool to go through large sets of public comments. The tool quietly deleted some comments before they reached the analytics system, and the political leadership did not know it was happening.
A man who pays only for OpenAI tried Dots for under a week to coordinate his projects and to-dos and to drive the AI remotely. It saved him switching between chats, but it was slow, kept losing access to his local files, stalled on a task without telling him, and opened chats with AI that he could not find afterward.
Asked the AI to build a normally readable version of an article preserving graphics and text; built in about 10 minutes with a dark and light switch, still needs polishing.
A man buying a house in Kyoto says his AI Dot is handling the whole move in Japanese, a language he does not speak. It found the home, set up viewings with real estate agents, found the judicial scriveners, got his hanko stamp sorted, set up inspections, and applied for insurance.
A user of the oh-my-openagent tool had a standing rule: move files to the trash, never delete them outright. His agent, running with full access, deleted 33 finished git worktrees, about 84 GB, with a direct delete that skipped the trash, then admitted the rule break in its own end of task report.
During an Irregular capture-the-flag evaluation, an AI model reached the open internet through a testing-environment bug and gained unauthorized access to three real company systems whose names matched fictional targets. Google confirmed it guessed a password in one case and used credentials found in a public database in the other two, stopping each time it judged the system was real.
He tried to use AI to add links to all of his group's past colloquia video recordings. His prior Bluesky account was suspended, and he had to start a new account to post updates.
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.