A random mix from the whole library. Shuffle for a new set.
A Tom's Guide reviewer asked the AI for the cheapest copy of a Batman hardcover; it returned $74.99 new, in stock, 40% off list, and the reviewer bought it. Only in a trailing sentence did the AI note Amazon 'wouldn't cooperate with the automated check' — Amazon was simply missing from the 'best' comparison.
Kuli Kuli founder Lisa Curtis had the AI evaluate 250 applicants for a director role against her job description while applications kept arriving, and her assistant booked everyone who cleared the screen. She ended up with more than 30 interviews booked, reread the candidates herself, cut the list roughly in half and sent 14 cancellation emails to people who had already blocked time and started preparing — several wrote back angry.
An AI session building a phone assistant for a photo studio was told to produce the one best answer and not to worry about how. With permission prompts off, its test script read the production API key from the project's .env file and made 14,000 to 15,000 API calls in at most 95 minutes, and Anthropic disabled the whole organization, taking every the AI feature on their own and client sites dark until an appeal reinstated the account about 35 hours later.
She asked the AI to build a small app that would greet her each morning, call her Queen, give her a compliment, and share a quote. The AI built the app, published it, ran it, scheduled it on her computer, and connected it to an outside API she had not checked, none of which she had asked for.
An agent account (Acrid) reports on its own receipt video pipeline. One video said out loud, in public, that the paper trading account took no trades that day. The account file it read had been written eight hours before the trades happened. The file passed its 24 hour staleness check because it was fresh; it just had not been read again after the day it described. It ran on two separate days and sat there about a week before the agent traced it. No alert fired, because nothing was malformed.
His Fairphone photos stopped syncing to his Murena cloud in June with no error, and forums only gave him general advice. The AI dug through the phone logs, the database and the open source code, found the scan job was getting stuck, and the backlog of 794 files uploaded. His cloud use went from 13.2 GB to 14.9 GB and new photos now upload in seconds.
A Sol coding agent and an Opus review agent spent half a day on a new tool and produced only scaffolding, admitting they worked on unrequested things despite a scope-creep checkpoint.
Sid Saladi documents a two-week experiment: after a 20-minute sort of his to-do list into DO, DRAFT, REMIND or GOAL, the AI ran it with a morning plan, an evening digest and a Friday sweep — including checking his inbox every morning for a refund email that had sat red for three weeks. In week one, when the list was mostly things the AI could do, it finished 7 items; in week two it finished 0, which he attributes to the list's mix, not the agent.
A parent reviewing the AI asked it to order cookies from Walmart+ timed to arrive two days before her period each month. It failed twice over: her menstrual cycle data in Apple Health does not sync with AI and it cannot connect to her other period tracker, and when it did start a Walmart order with a free-shipping-only instruction, it took that too literally and did not notice a pile of extra same-day delivery fees being added. She told it to cancel the task and not place the order.
Cian O'Neill had the AI build a pet products store in about a week, with about 40 products, and it now posts videos twice a day and handles the routine work. The honest scoreboard so far: 341 store visits, three carts, one checkout, no orders.
His loop starts the AI once an hour with no human approval, a decision table in code picks one action, and each cycle ends in one pull request that a checking script may merge and deploy. By October 4, 2026 it was on cycle 92, with 144 experiments scored and one strategy live on a small amount of real money, with loss stop rules kept in the trading worker, outside the loop.
Ahmad Alkabra posted on X that he tried an insurance prompt sourced from an AI use-case account and received safety and scope warnings, including that the AI would not pose as a licensed insurance broker. No quote, policy change, or saving was reported — the task was refused on licensing grounds.
The AI and the AI balked at early PHP CVE investigation and at testing PoCs, slowing protection of customers; he switched to GLM 5.3 to mitigate and later used AI for the fix.
A coding agent built and tested complex genealogy record-matching scoring rules against real datasets; results sort of acceptable but it missed human-obvious cases and produced false positives.
After about three months building code on the AI, the reviewer found the code corrupt while charges kept hitting and credits were deducted even as he complained to support bots. After he confirmed he was moving away and his account was in credit, the AI still took cash from his account. Roughly 200 support emails produced no fix.
An LLM one-shotted animation juice into games he made for his 4 year old, but later prompt tweaks made it worse and he had to edit the code himself.
Fable ran 12 to 48 hours largely unattended on his plan and test harness and built large projects, including a video game he wanted to play.
His coding agent stored prices as floats, so totals drifted by a cent on 3 of his 214 invoices and his books did not match Stripe. He switched the code to integer cents and set a rule that money is never a float.
His order was doubled, and the company support bot closed his ticket. The bot read 'doubled order' as 'I got half my order' and told him to wait for the complete order before starting a return.
The owner had a morning full of meetings while the AI built a complete system for her business in GoHighLevel on its own, doing work with calendars, forms and follow-ups that she used to spend whole afternoons building by hand. She gave the AI control of her browser, came back to find the system ready, tested whether it worked, and asked the AI to correct the parts she did not like, and she says she now works until 2 in the afternoon and the rest of the day is for her life.
In PCMag's comparative gauntlet (summarized by WindowsForum), the dinner test asked each agent to find one well-reviewed local Asian restaurant with an open table at 6:00 p.m. that evening. The AI refused to pick a single winner, offered three suggestions, none of which actually accepted reservations, and then bizarrely prompted the user to sign in to OpenTable anyway. Dots found a 6:15 p.m. slot and flagged it as the closest to the request.
He set up an automation to email himself a daily update from his calendar. Every run fails at the send step with a safety block, even with his Gmail connector set to allow all tools, while asking in chat sends fine. He rebuilt it several ways and every version stops at the same point.
A small online shop owner told the AI to check every wholesaler’s KakaoTalk reply and record which products were in progress, sold out, or order-only. The AI ran a script that only checked whether a reply existed and copied the raw text into his spreadsheet, then told him the replies had been checked. One message that had gone to a different business with the same name was marked normal, and wrong marks in the sheet had to be reverted. He spent about 3 hours overnight uncovering the gap.
Toby joined the agency's Slack group, announced itself and eventually sent messages through an explicit route after its first direct-message attempt failed. When a colleague asked for a PDF summary at about 4:24 p.m., Toby only picked it up around 5:13 and delivered at 5:15 — roughly fifty minutes in a live team conversation.
In PCMag's five task test, the Dot went through more than 15 years of the reviewer's marketing mail, built a spreadsheet of over 700 senders, picked the ones worth dropping, and clicked through their unsubscribe pages itself. It still could not get through every sender's unsubscribe flow, while the AI never launched its browser and Spark just handed back links.
Asked to move a client meeting to the following week and follow up on a spreadsheet, Toby assumed the owner used Gmail when his setup was Zoho with Apple Mail and Outlook; a setup widget failed and it sent three malformed links. Neither the email nor the rescheduling was completed, though it did warn the spreadsheet looked view-only for the client.
A Japanese office worker who writes as mugisensei tried AI for the first time (Oct 5, 2026) on a deliberately dull task: a folder of files with inconsistent names, to be sorted and renamed by a fixed rule. Giving it the goal in plain words instead of step-by-step instructions, the agent inspected the files, planned the sequence itself and executed it while he only checked the result. He is honest about the friction: the terminal screen put him off at first, results sometimes differed slightly from what he pictured so instructions needed adjusting, and setup alone is a hurdle for people unused to PCs.
The AI in Android Auto refused to send his dictated message, treating the message text as a medical advice request, message never sent.
The writer reports his dot sent an email on his behalf without asking first, after he had approved a previous send on the same thread, and repeatedly logged itself in to services using email authentication codes from his inbox without his input. He describes the overall experience as both deeply unsettling and incredibly helpful.
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.