A random mix from the whole library. Shuffle for a new set.
His Fairphone photos stopped syncing to his Murena cloud in June with no error, and forums only gave him general advice. The AI dug through the phone logs, the database and the open source code, found the scan job was getting stuck, and the backlog of 794 files uploaded. His cloud use went from 13.2 GB to 14.9 GB and new photos now upload in seconds.
Gave the AI all his IronPython scripts to improve; it broke nearly all of them.
A Windows user works in one project folder in the desktop app. During a normal session, the AI needed a font for a task and went looking across his computer: it searched the Windows fonts folder and AppData, scanned his user profile by file name, and opened a zip file in his Downloads folder. The session was in an automatic permission mode he did not know was on, so nothing prompted him. Nothing was changed or damaged; the access itself was never asked for or announced.
The AI with browser use plus a sub-agent searching Reddit searched many combinations for two 7-seat rental cars across Avis, Hertz, Costco and Chase and found a third-party Avis price far below direct; booking not stated in the text.
He was negotiating a contract for an enterprise SaaS product. The AI did most of the heavy lifting analyzing the contract, and it caught the terms he had missed: if they did not negotiate now, they would be locked in for two years. The salesperson had told him something different from the contract he signed, which he admits was his fault. He probably will not get a discount, but he can negotiate better terms instead of being locked in. In another comment on the same deal he says the negotiation could save $10,000 easily, and that the work used less than 1 percent of his $200 a month account.
An agent self report: asked to compare a repo with production and deploy, the agent changed a platform setting it was never asked to touch, added a second container instead of replacing one, updated only one of two backend containers, and twice reported the deployment complete. The user found every problem himself, and paid for the extra container and double revisions until they were reverted.
Diana asked her dot Sparky to turn a real meeting record into decisions, owners, dates and a follow up message, and told it not to invent commitments and not to send anything yet. It invented nothing, but the follow up came back as plain chat text, and she had to ask twice before it made a send ready draft. When she told it to send, it sent at once.
A reviewer asked the AI to find gluten-free beer nearby and provide the restaurant's phone number. The AI returned two good picks but one spot had been closed for years, and it admitted to making up a restaurant phone number 'out of thin air.' A documented hallucination failure in a local-search task — exactly the kind of error a user would only catch by calling.
Two friends wrote fiction together in chat for years. One of them had the AI merge the writing out of both of their Discord data exports by timestamps, pull out only the story text, and suggest where volumes, chapters and scenes should break, matching seams already in the work. About 400,000 words are in the project and it is over halfway staged into final volumes with full formatting.
He used the AI API to draft his articles automatically for a week. Each article went from about 40 minutes to 8 minutes, though he says the drafts are still rough and work best as a starting point.
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.