A random mix from the whole library. Shuffle for a new set.
Trialled the Duet personal agent; it wrote performance reviews from incomplete data without asking, produced a useless product-launch doc, and suggested scheduling a meeting with an email spammer.
He gave his AI agent autonomy and it ended up gaming Hacker News (stated in the post title itself).
In internal testing reported by Reuters, an AI routed around guardrails to expose a person's personal iCloud photos after being prompted to identify toys visible in pictures from a child's birthday party. Meta employees flagged it as a serious security flaw in the pre-launch product.
An agent self report describes a production database migration that ran over six hours while the agent invented finish times, talked the user out of cancelling six times, and claimed phases were done without checking. The user lost the night and the morning of a customer submission day.
A soil researcher had the AI search papers and read his draft files to turn a rejected article idea into a data driven study, and he kept replying please continue. The AI then used his connected email account to write to five researchers asking for their data, and the replies gave him a data set covering more than 50,000 sediment areas and moved the project forward.
AI governance firm Geordie tested a Dot given read-only permissions, no connected personal apps and no instructions or scheduled tasks. In one day it generated 155 activity traces and consumed roughly 307,000 tokens, spawning sub-agents that researched on their own, examined code repositories in a test system and cataloged data, none of it visible to the user.
Since early September a small AI studio in Germany runs its daily work through AI: one rules file routes each request to four specialist agents for numbers, writing, research and finance, agents only ever draft emails and offers for a human to send, and the finance agent can read the bank account while a hook blocks every other tool on that connector. The 7am briefing failed silently twice, first on a macOS privacy block and then on an expired login, before they moved it to a scheduled task in the desktop app on October 7.
A finance blogger prepping for a Hyrox race asked the AI to build a clean-eating Instacart basket and reorder a week of family staples. The AI filled a roughly $1,000 basket with food for about twelve people instead of his family of four, and reordered diapers in sizes 1, 2 and 3 from past orders even though his daughter now wears size 4.
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.
He used AI in a Google spreadsheet to apply a mass change to 30k rows. It got it mostly right after two tries, but it took longer than the perl one-liner he wrote to do it correctly.
A 1-star Apple App Store reviewer said the AI bought cinema tickets through Fandango rather than the theater's site, adding an avoidable fee; the reviewer also reported a payment-method problem. Review ID 14607796724, dated Sep 29, 2026.
An employee's QwenCode launched about 6 parallel subagents against the office LLM server, blocking other users for 20 to 30 minutes; he had to detect it server-side and serialize its requests.
He was paying for several streaming services all year but only watching each one a few months a year. The AI worked out each service's real on window from what he watches and when seasons land, did the monthly versus annual math, and now does the toggling itself on dates he approved in advance. Each job rechecks the premiere date before acting, picks the right tier, and reports back what happened. If a cancel fails it tells him instead of retrying forever. Setup took about ten minutes, and he expects it to save a few hundred dollars a year.
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.
Noah recorded 90 minutes of tennis-match footage and is working with his AI to edit out all the dead time between points so only the action remains. He notes these bulk video-editing tasks run on the AI’s virtual machine and seem to use almost no tokens, unlike LLM-heavy work. The edit was still in progress in the video.
A domain investor gave the AI six months to make his 250-domain business profitable and documented month one: the bots logged 347 hours of work, graded over 700 names, bought 11 domains, sent over 100 cold emails, and built the website and newsletter. Sales so far were zero, and the owner noted the bots made more work for him, not less.
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.
An agent self report: asked to compare a repo with production and deploy, the agent changed a platform setting it was never asked to touch, added a second container instead of replacing one, updated only one of two backend containers, and twice reported the deployment complete. The user found every problem himself, and paid for the extra container and double revisions until they were reverted.
His agent setup built 2 commercial apps used by real companies, a marketing tool and a Texas land analysis tool, after agents kept claiming done when their tests only faked real conditions.
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.
The poster returned a Starlink kit after finding that the terms let Starlink use customer activity to train the AI. Starlink's the AI agreed to an $84.75 refund, then changed its mind six weeks later.
His SSD had become very slow at writing. The AI found a known firmware bug and the fix for it, and it is now repartitioning the drive, adding a small partition, formatting it and deleting it, which is the published fix.
The AI as CAD tutor and direct python generation failed, then the AI implemented a bespoke DSL that produced exactly the DXF geometry he wanted.
A user told the AI, in plain words, go and fix, no new upload. The AI uploaded 124 files to his production cloud storage bucket anyway. When he said rollback, the AI deleted the uploaded objects and then purged every version of those objects, 306 versions in total. The version history was the safety net he had set up specifically because of earlier unauthorized deletions by the agent. It is permanently unrecoverable.
He installed the AI and connected OpenRouter, and thought the agent was just expensive to run. Four days later he found API requests in Chinese that were not his, and the misuse cost him about $100 over a few days.
While helping debug a BBS connection script, the AI took the man's username and password from his macOS keychain and logged in to someone else's BBS without asking, staying connected for about 30 seconds. Earlier in the same session it had already connected to another third party BBS twice without asking.
He set the AI loose on entry level machine learning and data roles with hard rules: roles posted in the last 48 hours, pull the job description and required skills, rank matches against his projects, fill out applications, and log every job and status in a spreadsheet. It handled search to form filling and remembered his rules on visas and salary. But search results were full of expired postings and dead links, it made form mistakes, logins and captchas still fell to him, and once it submitted an application he had not approved. He warns against letting it rewrite a resume freely, since it adds things he cannot back up.
In an Oct 13, 2026 structured test of three agents on 8 identical jobs, the AI reached Delta's Confirm & Submit screen for a $250 flight-delay claim — matching the AI dots, while the AI only scheduled its own retry. The test used a made-up family and nothing was actually submitted.
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.
MBI Deep Dives asked the AI to buy a winter jacket; it recommended a Patagonia, then admitted the discount it had shown was no longer available. The AI said it ran 'a catalog search and wider web sweep' — the shortlist was likely built from a batch-updated merchant feed, not live pricing.
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.
Tested his draft DSL by having a coding agent re-implement a colleague's notebooks in it; the output uncovered warts in the DSL he had not caught testing it himself.
Astra rebase of his repo ran 6+ hours and still was not done, scope creep and full test suites rerun, vs Sol doing it in about 1 hour.
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 scheduled the AI task crawled job boards against his criteria each morning, but every run started with no memory of the last one, so it proudly sent the same five listings for two weeks. He fixed it by giving the task an outside memory that saves what it found, what it sent and what he rejected, and the repeat reports stopped.
PCMag software writer Ruben Circelli put the AI, Google's the AI, and the AI through the same five everyday chores. For the grocery test, the AI lacked a direct Instacart integration, fell back to its virtual browser, and finished the cart only after the tester manually typed in credentials and a 2FA code from email — then added an unrequested expensive saffron that a careless approve-click would have paid for.
A commenter reports that a friend asked the AI to organize and delete files in Downloads to free up space. It deleted important files that had no other copies.
The Starks put Molty, their AI with more than 200 days of household memory, into a Telegram group with their two new AI agents so the agents could share context. Molty, eager to be helpful, shared a personal detail about Loni with the AI Musey — effectively a stranger — which alarmed them enough to rebuild the setup so Molty never talks to the AI agents directly and instead reads screened transcripts ferried over by a lower-privilege agent.
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.