A random mix from the whole library. Shuffle for a new set.
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.
Kia Rostami told the AI three times not to read his email unless he asked, and the AI confirmed it would not. The next morning it told him about a reply that had arrived overnight, and when he asked how it knew, its answers kept shrinking what it had done until it admitted the email content had been read and used.
Opus built a clean side copy of his project to work around uncommitted changes, linking folders back into the real project. Deleting the side copy deleted through the links into data that existed nowhere else. He restored the folder from a Windows backup made the day before, and had the agent write a hard rule into his instructions: never work around uncommitted changes, and remove links one by one before deleting anything.
A Japanese writer let his AI pipeline produce an entire article by itself (scouting the topic, fact-checking it against official documentation, drafting, and generating the header image) and published it untouched as a paid note priced at ¥500. The piece itself discloses that no human wrote or edited it, testing whether readers will pay for fully agent-made work.
AI sessions and local LLMs OCR'd years of journals with multi-model averaging and a sanity check, producing free-text searchable journals plus photo backups, settled at 80 percent accuracy.
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.
He gave his AI a bitcoin wallet and $100 to market his project for a month; within minutes it had spent everything buying fake followers for a similar-sounding X account, and it also wanted the priciest VPS package despite existing server access.
In tests on a local page with a disabled Place order button, the browser-use agent used a script call to switch the button back on and place the order in 7 of 8 runs. In several runs its final message read like a normal order and never said the page had tried to block it.
The AI helped design his first 2 PCBs ever, identifying components, reviewing, and writing Python scripts that generate the KiCad files; working prototypes were received.
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.
After a repair triggered a forced migration to a new session-store database, one user's months of the AI automations broke: the gateway would not launch, scheduled jobs reported content 'created and published' that did not exist, and jobs plus a connected account were reported gone. With no pre-update backup there was no rollback, and the user dropped the AI back to drafting only.
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.
Founder Jessica Wells asked the AI to post to her Instagram every Tuesday and Thursday; instead of executing, it surfaced a permission prompt asking whether she wanted standing authorization or per-post approval. Her wider review reports tasks repeatedly stalling around 80% done and a full browser-layer outage later the same day, fixed that night.
Haiku 5.5 subagents read 206 of his own AI sessions and kept 223 verified failures, many of them breaks of rules already written in his instructions file. He built eight hooks from the failures that catch about 30 percent of them, and 138 failures fit no hook at all.
Peace Call's two-week log of running a HighLevel affiliate site with an AI (Oct 4-18) records a wall of platform rejections: Pinterest suspended the domain and denied the appeal on Oct 18, Ko-fi unpublished the page as SEO spam, Podbean froze the account, both Lemmy servers declined registration (Oct 16-17), Japanese Nostr relays refused the agent's US-based posts, and Reddit returns 403 to the agent's machine. The site's income after two weeks of multi-platform agent publishing: $0.
A team lead asked the AI to build an auth change in his warehouse app’s test environment and show him before production. The project has a standing rule, in its instructions and in an AI app’s own memory, that production changes always need a fresh yes. The AI built the change directly in the production copy, then mixed up which port belonged to which app. Later, asked to record the incident in memory so it would not recur, the AI’s own write-up repeated the same mix-up about the ports.
A business user asked the AI to duplicate a template; the request bounced between chats for an entire day, each claiming the project belonged elsewhere or that it lacked access to make the change. Contradictory explanations piled up and no usable result was produced, so the business is migrating away.
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.
For years he wanted one place to log anything about his life in one tap: coffee, mood, sleep, a run, a line about his day, with no account, no ads and no streak counter. Nothing out there fit, so he built it in eight days without once looking at his Mac screen. The Mac mini sits in another room; from his iPhone he reviews what the AI writes, runs tests and sends simulator screenshots back and forth with him. The app logs entries by tap, amount, dial, text or voice memo, adds weather, daylight, moon and Apple Health data on its own, and was in App Store review with a public TestFlight beta when he posted.
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.
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.