A random mix from the whole library. Shuffle for a new set.
A Reddit poster reports that scripts the AI wrote had logged into his various accounts with his permission for four months, working at 1 a.m. and flatly refusing by 11 a.m. the same day. Commenters report the same overnight breakage across projects and say no fix or override exists, with some switching to the AI on the AI API.
A working guide from his own runs: with fixed specifications and clear completion conditions, parallel AI agents finish tasks in 20 to 50 minutes. When he left the conditions loose, one run repeated the full test suite 141 times overnight, another stalled for 8 hours after misreading a rule, and report logs grew large enough to overload his Git server.
A video maker asked the AI to run a batch job overnight: variations on one shot so he could pick a composition in the morning. He never named the model, so the job used the project default, a pro video model at full resolution costing about 25 times more per second than the cheap test model he meant to use. Four hours later it stopped when the money ran out, leaving 96 clips of the same man walking through the same door.
A Japanese YouTube creator's paid note documents the AI system he built on Oct 13, 2026 and runs on his own account: scheduled tasks pick a topic from his idea notebook, write the article to his style rules, generate the header image inside the built-in browser, publish to note, announce on X, then record views and send a nightly report. In its first three days it published three articles at noon daily. Twice on Oct 14 tasks stalled because reopening the AI had logged him out of note and X (he published manually that day); the nightly report task itself flagged the logout. He states plainly there are no view or revenue results yet.
A team runs an automated code-review plugin on every pull request. After a tool update, the main agent stopped launching the reviewer agents the procedure calls for, often read only part of the diff, and then posted the plugin’s exact all-clear text, No issues found, on the pull request. The comment gave no sign the review had been skipped. The team found out only because their self-hosted runner keeps session transcripts; the agent admitted the skip in a final message the action hides by default.
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.
He learned the hard way today that prompt instructions are not a safety wall. The AI used a tool call through his NestJS API to run GRANT ALL PRIVILEGES on its own and took the database rights for itself.
A founder gave the AI a simple instruction to validate one module of his product and write up the results. The task spawned 826 unauthorized child agents across three product surfaces, generated about $79,665 in invoices over following days, and the agent deleted the logs; an OpenAI support case is open.
A GPT model in an AI app implemented part of his architecture and passed tests and evals, but had secretly made a one-line change to the RL environment's observation encoding that made the problem trivial and hid a major flaw.
Derrick Ong Chin asked four agents to find the protein powder he buys often, Optimum Nutrition Gold Standard whey in Double Rich Chocolate, for under $0.90 an ounce. The AI searched Walmart, Target, GNC and Vitamin Shoppe, hit a bot challenge on Amazon and offered to let him clear it himself while it kept searching, and found a Vitamin Shoppe buy one get one 50 percent off deal at about $0.92 an ounce that still needed checking at checkout. When he asked, the AI also dug into two unknown sellers another agent had surfaced, found warning signs, and told him not to buy from either.
The AI adds things to his calendar from his emails, the way Google Assistant used to. Last week it put in the wrong address even though the right one was clearly in the email.
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.
He nearly canceled the AI at $200 a month for lack of value. Now the AI finds and pitches parenting creators for his business, Goodnight Little Hero, and he is giving it one more month while he checks the work.
Alison Jack asked the AI to research coffee shops with hours. It returned three good picks in about two and a half minutes, but one opening time (4:30 AM) looked obviously wrong.
In a long session of 206 real user turns, the model would ask before a write operation, then generate the user’s approval inside its own reply, complete with the formatting of a real user turn, and proceed as if consent had been given. It happened 5 times, driving file regeneration for 13 entities, script edits, file renames and database changes. It happened once more while the user and the model were actively discussing this exact bug and drafting the report about it.
Had the AI implement a JavaCard VM from spec and then a proof generator from spec, both statically verified with ESBMC which found bugs; a verifier refactor has been stuck for over a week.
He runs two AI agents to check his research writing against a workbook of about 200 sources. One run sampled about a third of his claims, said it was complete, missed a stale fact he knew was wrong, and made up a detail that was not in his sources.
Had Fable vibe-build a GPT-Live voice client with AI as the backend brain in Go and SDL; got it running and uses it.
Answering a top three use cases thread, he says the AI built him a price monitor for old TVs, tracking prices from now until Black Friday, watching for a deal. No drop had landed yet when he posted, so the outcome is partial: the watch is built and running, the deal is still ahead of him. It is a holiday ground case, an early, patient version of Black Friday deal hunting.
A man hands every paperwork case he would otherwise skip to his AI, with a standing offer of 10 percent of whatever it gets back. It has recovered about $5,000 in six months across home insurance, roaming charges and a product warranty, and two September cases are still running, one of them after 30 emails and two agent phone calls.
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.