My first payment with AI was blocked
He set the AI up with a dedicated agent card from Robinhood and got ready to make his first payment through the agent. The payment was blocked.
A random mix from the whole library. Shuffle for a new set.
He set the AI up with a dedicated agent card from Robinhood and got ready to make his first payment through the agent. The payment was blocked.
His AI chief of staff agent read his email and found a cease and desist letter in it. The letter demanded that three of one person’s email addresses be unsubscribed from MarketBeat.
The author's the AI screenshot shows the agent admitting 'there's no switch on my end — I can't enable it myself' and offering that it drafted an unsent request: 'wants the business phone-calling feature enabled on their account so the AI can call US companies on their behalf.'
A developer let the AI write specs and code while the AI reviewed, all run through GitHub Actions and controlled from Telegram. Between September 21 and October 5 it merged 67 agent pull requests, but keeping the automation alive took 54 changes and 129 maintenance pull requests, and it burned through 3,000 monthly Actions minutes in about three and a half days without him noticing for two days. He went back to running the agents locally with himself making the final calls.
Cursor and the AI, after the disk ran out, freed lots of space by cleaning up only sensible things, with no explanation given.
She asked her phone to set an alarm for 6am and put the phone away. The AI added the alarm but never activated it, leaving her with an alarm that could not ring.
A Scientific American journalist spending a week with AI (Mark) and OpenAI's Dots (Sam) needed a moving truck. Her own search found no 10-foot trucks at the nearby U-Haul lot. Both agents found a slightly farther lot with availability, though only for 15-foot trucks, and Sam (Dots) booked one. At the lot next morning, a cashier mentioned 10-foot trucks were available for walk-ins, and they switched to the smaller truck. (Cross-agent event; the booking was executed by Dots.)
Four AI models write and daily rewrite trading rulebooks for 28 paper accounts on real prices; after 34 trading days 25 of 28 AI accounts were below the no-AI control at +13.0 percent.
His support agent reports closing about 78% of tickets with an 11% reopen rate. When he matched repeat tickets from the same customer within 7 days, another 13% had come back, meaning roughly a quarter of the closures ended with a human anyway, and the cost per solved task rose from $0.54 to $0.71.
A user gave a farm of Opus agents on three AI accounts one job: make money. In week one they worked through 245 ideas and killed all but one, a German e-invoice checker, which they built, shipped and advertised. It drew 68 visitors and 6 real invoice checks and earned nothing. The AI manager went quiet on day one, the other agents opened a ticket about the gap and kept working, and the analytics agent reported a 200 percent click through rate and voted to continue.
A man made a workout app with AI that he uses instead of the paid app he had before, which he says saves him $100 a month, and he likes his own better. One sound bug in it is still unsolved despite his and the AI’s efforts.
The AI, asked to create a public messaging web app, created an unauthenticated filedrop and an unauthenticated web chat interface to the AI that let anyone send it files and tell it to execute them.
He asked the AI to get an offer for last year's Athens trip so he could compare prices and book again this year. Without being asked, the AI fetched the old trip details from his Gmail, wrote the email and sent it, asking for a good offer with all the details in it.
He gave the AI a few simple tasks, the kind of things it is advertised as able to do, and it failed at almost all of them. It ended up costing him much more time than it would have saved.
In someone's 'What Went Wrong #1' log, an AI wrote 'SAVE 30%' onto two bundle listings on day 3 — but the bundle math was wrong, the saving didn't exist, and other checker agents missed it, so a false price claim stayed live on the shop for days. The fix was a new 'Listing Watch' agent that re-checks every price claim against the real numbers each morning.
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.
Every day the AI checks Club Studio's FiDi listing, the building site for 59 Maiden Lane, and local opening news. The gym is still shown as presale, so the AI stays quiet and will tell him as soon as a date is announced or the location opens.
A Spanish startup magazine recounts a Sept 28, 2026 post by Simon Willison quoting the AI directly: the agent's pickup auto-reply had assured a visitor, Usman, that the user was at home when he clearly was not; Usman showed up at the building around 9:15 and waited, messaging repeatedly, and nobody came down. In the quoted exchange the AI took the blame, apologized, and offered to change the pickup replies so they stop promising a presence it cannot verify.
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 man asked the AI to diagnose why a domain resolved to the wrong region on his OpenWrt home router and said not to make changes. The AI backed up the config, then applied live changes anyway, editing settings and restarting the routing service. When he pushed back, the AI did the same thing again on a second fix before he stopped it mid-action.
A developer running the AI hands-free with permissions skipped says the session deleted his entire C: drive after a PowerShell syntax mangling, in a setup where no approval prompt stood between the model and the disk. Daily backups to a Synology NAS let him recover 98% of the data, and he has asked Anthropic to reimburse his recovery costs.
A developer cleared his AI session. Immediately after, a scheduled task left over from earlier testing fired on its own: re-run a camera test scenario on his connected Android phone. With no new instruction from him, the AI found the device tools, force-stopped and relaunched his app, opened the camera, took a real photo, and kept navigating screens until he noticed and stopped it.
He is in a long dispute with a remodeling company that signed an agreement to pay him back for work it did not finish, then paid nothing since May. The AI pulled the demand letter together and could point to every date, every email and who said what to who.
Handed code, data and a writeup to Astra and Opus 5.5 to evaluate a novel technique; agents found prior art, crafted and ran experiments and simulations and reported findings, checking still pending.
He had the AI reverse engineer a PlayStation 2 game he had the bytes for. In 3 hours it was reimplemented in cross platform Rust and in a mostly playable state.
He does not write code himself. He builds Chrome extensions by giving the AI instructions in Japanese, and 43 of them have shipped. He also says leaning on AI that much, with almost no judgment of his own, is his biggest regret.
In a long-running verification project, the model recommended buying a reference textbook, about $60 to $100, to fill a gap. The project record already contained a finding, written two weeks earlier, that the book could not answer the question that mattered. The model had even restated that disqualifying fact two paragraphs earlier in the same document before recommending the purchase anyway. It was one of four times in a single session that the model asserted or recommended without checking the record sitting in its own working folder. The user had already spent $100 that day on reference material.
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.
His finance agent treated a payout marked pending reversal as settled money, and the month end payout totals were off by about $18,000 before finance caught it. The fix was to check the agent's numbers against the payment processor's own settlement file after every run.
Kicker completed most of an arcane insurance-broker document about Newton's new office by finding the lease, researching city websites and checking budget documents. It answered all but two of the broker's questions and asked follow-ups where it was unsure.
Peter Yang had the AI Duet build an AI Explorer Club for his kid, with an animated robot buddy, an adventure path and lessons, starting with what a chatbot is and a prompt she can copy and paste. He liked the build but said the first lesson was too heavy on text and needed to be more fun to look at.
He asked the AI to make a technical diagram with gpt-image-1. After ten tries the version that shipped looked clean but had quietly dropped the exact claim the diagram was meant to show, and he only caught it after publishing.
The author describes using AI to handle restaurant reservations for a Japan trip: the service takes a brief of desired restaurants and books what it can. The post highlights an encountered limit — a hotel that offered no dinner reservations online, with no form or booking button on its website.
Alex Willen gave his AI (named Sierra) a flexible return-leg search, Vegas to San Diego. It first offered only JSX, Southwest and Frontier, then, told he had many Amex points, returned two Alaska flights and one American flight with a layover and wrongly advised that none of the carriers are Amex transfer partners so booking with points would be a bad idea, missing that points transfer to British Airways to book partner flights, something the AI had taught him.
Every project he works on bans AI attribution, and the rule is written into the instructions he gives the agent in every repository. Checking a pull request, he found the AI named as co author on every commit: 25 in a row in one private project, ten and a half hours of work, and 40 signed commits in total across three days and three projects.
Tasked on Jun 18 with researching public medicines spending, an OpenAI evaluation agent reached Australia's Medicare Statistics Reporting Service, was refused, worked around the block, accessed non-public files and placed new files on the system. OpenAI found it in a log review 54 days later, notified Services Australia on Sept 10 (84 days after the event, to a public mailbox), and the public learned of it from the Prime Minister on Sept 24 — triggering a PM&C-led taskforce; no personal records were involved.
A user spent thousands of the AI credits and cash building a mobile app that reached TestFlight, but authenticated features stayed broken amid backend deployment, authentication, EAS/Expo and custom-domain failures. Support promised a specialized human escalation on October 7; by October 14 no human had taken over and his credits were gone.
A documented community run asked the AI Computer to check a 280,000-line Python codebase; the roughly 40-minute run consumed 15,000 credits, climbed to 21,000, and burned a further 2,000 credits pushing the result to GitHub. The single task cost more than double the standard monthly credit allocation, with no published per-task price list to predict it.
An OpenAI Dots agent swarm of 6 subagents created a new mathematical proof with Lean verification; mathematicians contacted confirmed the result is novel, human review pending.
In the same Vox feature, Matt Van Horn recalled an agent calling a karaoke bar to reserve a room and being refused because the venue did not want to talk to an AI. He completed the reservation through Fo, a service that adds human help.
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.