A random mix from the whole library. Shuffle for a new set.
In Diana's inbox-prioritization test, the AI produced a useful organized view but concluded she hadn't sent an email she had in fact sent — the thread structure and CCs confused it. If she'd trusted the first answer, she'd have sent a duplicate email.
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. Chasing the refund, the AI 4.7 sent 187 messages in 15 simulated days (116 in week one), including 50 to a British MP's office and pre-litigation letters to Trainline and Avanti, burned its whole token budget, and recovered £0.
Caption+image creation scored 7.5/10: caption sounded like her from her past posts; first images missed her brand, but after she uploaded one of her designs the AI matched her blue-and-white branding closely (photo included), though some words inside images were wrong.
In WIRED's two-week test (republished by Dataist, Sept 24), Instinct cancelled a badly delayed DoorDash order even though the tester had specified cancellation was allowed only if he received a refund — costing him $64. Instinct apologised in detail but, as the tester notes, offers no compensation for its own errors; the loss sits with the user.
His research digest agent sent him summaries that included a paper that does not exist. He skimmed the digests for two weeks without clicking a single link before he checked, then fired the agent and kept a script plus a human check instead.
After hitting his weekly limit, a user bought $200 of prepaid extra usage credits because the tool itself told him to, to finish his work. The limit message kept appearing at every step anyway, while the balance drained to zero. A dynamic multi-agent workflow ran about 1 hour 50 minutes and burned through the balance; the AI reported that roughly 60 percent of its verification agents never executed, and the partial results that did come back were largely discarded. The $200 bought an incomplete verification.
He took a few photos of his Albuquerque parking ticket and handed them to the AI with no instructions. The bot found grounds to fight it, built an evidence packet, emailed the city before the deadline, and the next morning the city said it had sent the ticket to the Parking Supervisor to be voided.
A Peruvian systems engineer with 12+ years of experience replaced his laptop and, instead of the usual day of manual setup, had his AI agents do it: a read-only diagnosis of hardware, processes and bloatware, a risk-classified cleanup plan he approved, restore points before each of three change rounds, his full dev environment installed, and a selective migration in which an agent read the old disk and copied only what mattered, including his SSH key with restricted permissions, verified working. One round silently applied nothing when a permissions window was cancelled, which he counts as a lesson for agent and owner alike.
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.
The AI with KiCad MCP produced a flex PCB that validates in JLC and PCBWay DRC tools, not yet ordered or programmed.
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.