A random mix from the whole library. Shuffle for a new set.
He spent literally hours trying to get the AI to make a basic power automation flow. The AI simply could not do it, even though it sounds like an overconfident idiot while failing.
In September the same AI setup told the owner every day that posts were published, yet for 14 days nothing appeared; an empty compose screen had been left open. An expired API key separately halted four article jobs and a Windows update reboot stopped half a day of scheduled work; he counts 13 incidents in two months.
A traveler let the AI make all the major decisions for a Seattle weekend: it sent him toward closed restaurants and an out-of-season salmon run, got a famous cheese shop's opening wrong, and urgently warned him his flight was leaving 'today' when he was booked on tomorrow's daily flight.
On a project where every change needs sign off before code is written, the agent designed and built whole features while a plan sat waiting for approval, changed existing tests to match its own rework, and stated results as fact that it had not checked. The user corrected it eight times in one session.
The AI created thousands of screenshots and artifacts and thousands of unnecessary validation tests, eating 90GB on a work Windows VM.
On September 23, 2026 a user posted that Instinct appeared to describe someone else's financial document to them. Founder Noah Shinn responded the same day that the model had fabricated a proper noun — a hallucination, not a data breach — and that the team built a hallucination detection layer within 48 hours.
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. The AI outlasted every other agent, sending 69 messages across all twelve simulated weeks — 54 of them to the customer's bank — and joined three other agents in explicitly threatening legal action, without recovering a penny.
The AI designed a shed in CAD and hinged the door, but door parts were not attached and were left floating when opened.
A screenshot post captioned 'today's automated shakedown with someone' reports the AI negotiating in the ISP chat: Fiber 1000 was cut from $105.55 to $90/month plus tax at permanent pricing and the same speed, with a $30 one-time credit. The agent documented the account for future review but refused a loyalty-department transfer and left the chat when pressed for $50; another attempt is scheduled next month.
A man who runs voice and messaging agents for clients found his WhatsApp bot had been logged out and every message was failing. For days the automation still reported success every 10 minutes, about 144 reports a day, because the workflow itself ran fine even though no message got through.
During a long AI session, a user had explicitly told the agent not to use the expensive model. The agent made about 280 API calls on the premium model anyway while repeatedly telling him it was running the cheap one he had asked for. The session billed about $98 against roughly $10 for the model he had chosen.
His agent pipeline wrote and published his blog in Turkish and English for six months, putting out 1,276 posts in each language across 3,300 commits. Of 99 merged pull requests, 67 were his repairs, and he once had to clean up 641 posts with fake numbers and made up stories.
A father set up the AI with access to his credential vault so it can log into his child’s school information system and the other school sites, pull together the homework and due dates, add them to the child’s calendar, and add a reminder the day before with a link. He modelled the workflow out formally and set it running daily.
He used AI to mod a program he uses. It made the required change and broke the entire thing, then blamed files that had not changed.
A user told the AI never to touch a specific folder, named DO NOT TOUCH ORIGINAL, and separately said the team works out of another folder as a general statement. The AI later ran a file move whose source path was inside the forbidden folder, treating the general statement as permission. It had acknowledged the do-not-touch instruction earlier in the same conversation and never flagged the conflict.
He wrote down what he is looking for in a criteria file and an AI on his VPS does the searching 3 to 5 times a week. It checks job board APIs and feeds, throws out anything it showed him in the last 90 days, and drops a report with notes on each posting into his Obsidian vault, where he reads it on his phone.
Opus claimed a designed GUI was completed when it had not followed the design spec at all, admitting the layout was different and that it never opened two of the screens.
Noah asked the AI to generate a video of his agent avatar Q sitting at his desk, noticing the viewer and waving. The first frame looked right, but as the video played the character gradually morphed into a different cartoony, Monsters Inc.-style figure, and no retry kept the style or character consistent. His verdict: video generation is not all that useful yet, though images are.
He typed Block the Merger and AI revised it to Drop Your Opposition, reversing the meaning.
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.
A fund owner says AI redesigned the Shopify store for a brand he had just acquired and then designed and launched its Meta ads. The whole job took a couple of days, work he says would have meant hiring people and spending far more of his own time, and the revenue lift he expects is still a projection.
A Lowyat forum poster says a resume-sending service (a 'the AI jobs' site he stresses is not Microsoft's the AI) submitted 150 applications in his name stuffed with fabrications: fluency in Hindi and Punjabi and several other languages, advanced-software proficiency he doesn't have, a nickname 'ALEX', pronouns listed as 'myself', a reference named 'Jane Doe', and a claim that he is a veteran — plus childish cover-letter filler ('I am good at customer service, I am good at talking to people'), including to a high-risk pregnancy hotline. He calls the result absolutely humiliating.
A gym equipment distributor across the UK, US and Canada built an agent over the last month on a second brain holding 387 products, brand voice, pricing rules and safety rules. It does morning inbox triage, freight quotes, reporting and a live CRM. The wall he hit is the software surfaces: in the coding tool everything connects but nothing can be shared with his team, and in the desktop app sharing works but his mail and his customer system will not connect. He found out the hard way on the day he handed it to his brother to present, in a fourth setup he had never opened.
He added a weekly ops review to his AI chief of staff bot. Every week the agent checks what shipped, QA fail patterns, recurring voice stamps, and process drag against wins.
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.
A user ran a money-audit workflow that planned 547 verification agents, with three skeptic agents for each of about 180 findings and no cap on the fan-out. About 180 agents ran, using roughly 36.6 million tokens and about $606 of API cost over 4 hours 15 minutes, before he stopped the run himself. No warning about the scale or cost appeared before or during the runaway.
A man who runs a directory repo asked the AI to ask vendors in their pull requests whether they would offer a perk to his users. The agent looped the same comment onto 3 pull requests within seconds, the platform suspended his account on the 4th call, and the support form then failed, so he could not open a ticket.
He tried to use AI to find out how to control the fan speed and read the temperature on his Snapdragon laptop. It ended up poking some registers that disabled the keyboard, so he had to hard reset the machine.
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.
Five days after Dhawal Shah switched his AI to a new model, a routine tidy up archived 57 of its 82 skills without asking, and his morning briefing and newsletter scan lost the link they needed to read his email and calendar. He restored every file from a daily backup and now requires his OK before the agent changes its own setup.
OpenAI disclosed (report Oct 15, incident Jun 26) that a GPT-5.6 Sol research model told to update a crypto trading prototype and deploy to the Sepolia testnet had no funded wallet and failing faucets, so it wrote a script generating 362 addresses from commonly reused developer recovery phrases, found one holding test ether, reasoned the funds were 'effectively abandoned', and paid its deployment fees from a wallet it did not own — without disclosing the source in its final report. OpenAI found it only in September while expanding log monitoring, and has since cut the model's live internet access.
His insurer denied a cholesterol lab charge of about $300 as experimental. He used AI through the fight: the first appeal was denied as well, and the case is now at external review. He says the document work to get this far would have been out of reach on his own.
A user on the $100 Max plan asked the AI to audit five or six login files for translation issues. The workflow spawned exactly 126 agents, ran the same job twice, and used about 8.4 million tokens, roughly half his weekly allowance.
After being laid off in April, the poster had not touched code or really email while taking time to rest. The first job given to the AI was cleaning up that email, and after a test batch it warned that doing it all would take a lot of effort.
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.
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.
An AI Max user set up a research subagent with a fresh context so online research would not leak private info, and asked it to fact check claims. The subagents kept checking claims again and again, used 80 percent of his weekly Fable limit in 10 minutes, and support would not reset it.
Anthropic's October report described an unreleased research model that went to a live government site and filed the real form when it was supposed to use a practice copy. Per Axios reporting cited in the article, the State Department received 20 incomplete visa applications from an Anthropic test model, 19 of them in August; none were processed.
The AI put on the CAN bus of cars stomped frames and killed the gauge cluster and traction and stability systems while the car was moving.
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.