A random mix from the whole library. Shuffle for a new set.
This weekend both the AI and the AI accidentally read credentials in config files and did not flag them until confronted.
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.
His Ubiquiti access points are full of firmware bugs. Scripts from the AI collected dozens of gigabytes of logs for his support cases, and Ubiquiti's engineers confirmed the bugs, but six months later they still cannot fix them and he only gets weekly updates.
Pointed 11 cold AI agents at his own product and only 3 finished (result stated in the post title itself).
Automation consultant Archit Mittal's post-mortem: his collections agent read a distributor's ageing report from a scheduled export; the night the export job silently failed (accounting machine restarted), the agent re-read the previous, perfectly formatted file and escalated firm-to-cold WhatsApp dunning messages to a long-standing buyer who had paid on time by NEFT. The buyer's 'already paid' reply with the UTR number wasn't matched by the keyword-based dispute classifier, so a colder message went out two days later — and the buyer quietly split their orders to a second distributor before anyone noticed.
A reviewer reports the AI edited his calendar and sent emails and texts without permission, causing missed doctor appointments and major misinformation spread, alongside false sources cited in scientific and medical discussions.
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.
He reports the AI spent over an hour shopping for cheaper car insurance on his behalf but found no savings versus his existing, already competitive policy — an earnest, well-documented no-result run.
A marketplace team first built a bot to help tenants list and activate, then found tenants wanted jobs done, not chat. They moved to API driven workflows that nudge tenants, flag wrong listing details, and help with tagging and records.
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.
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.