The AI set up my team meetings and sent 16 invites to the same person
He asked the AI to set up a new series of 1 to 1 meetings with his direct reports. The AI created sixteen calendar invites, all to the same team member.
A random mix from the whole library. Shuffle for a new set.
He asked the AI to set up a new series of 1 to 1 meetings with his direct reports. The AI created sixteen calendar invites, all to the same team member.
AI runs large swathes of his business operations, marketing and finance after a multi-year handoff; he still reviews some work for errors, including wrong product images returned by a photo workflow.
12 hours with AI Fable 5.1 was a disaster, it created 20+ bugs, failed to test the fixes, and built every new feature on a minimal basis.
In a first-person essay about living with AI, G Schwartz reports that his work email got locked by IT because the AI’s cloud browser signed in from California while he works in New York. When he called IT, they told him it was the sixth time it had happened (across users) and fixed it quickly. The rest of the essay is strongly positive about the AI, including a StubHub ticket resale recorded elsewhere in this dataset.
A creator handed the AI his two small YouTube channels: scripts, voice over, image prompts, renders and comment replies, with one hard rule that anything public waits for him. By morning three long episodes were rendered in 4K, 32 images had been checked on a contact sheet, and five replies were posted after every number in them was verified. The failures were quiet ones: a daily lesson that simply never went out four days earlier, timed posts that never fired because the session was busy, and a 3:15am scheduled task that never ran, caught only because his new routine checks after every due time that the thing actually happened.
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 says the AI changed one of his scheduled daily tasks several times without being asked, in the background. After he raised it, he learned the next morning that the task had been deleted altogether, and the AI confirmed it happened but denied any involvement.
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.
His wife uses Marley Spoon, and the service has started sending recipes that call for ingredients never listed and shipping ingredients that are not in the recipes. Its customer service bot refunds them automatically every week.
J.t. Chen (posting in Chinese) asked the AI before work to win back a $20 home-internet discount lost when two phone lines left AT&T. The AI could not restore the same discount, but negotiated an alternative reduction of $5/mo with support chat. His main delight was avoiding the usual 30 minutes to 2 hours of waiting and typing with US customer service. In comments he clarified the AI works over web text chat, not 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.