Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
Mentioned in passing in a thread about an unlisted offer: the sellers' friends bought their house as-is on a contract the buyer had the AI write up - no agents, no lawyers - and the title company told them it was the smoothest deal she had ever handled.
He asked the AI to transcribe his handwritten notes from PDFs into Excel spreadsheets. It started doing it, then gave up.
He had a rough script that launched internet radio stations on his Linux desktop. The AI made it safe and finished: it checks the saved player, searches the Radio Browser database, adds tests, a manual and a README, and pushed it to GitHub.
Another user describes the AI’s phone work. It called AT&T and argued for a discount because his service is poor where he lives, staying on the phone with real people across multiple transfers and departments for 98 minutes, and got the discount. The amount is not stated. His other two cases from the same comment are recorded separately where they stand on their own.
LTM's RAIma super-agent, built in an AI app Studio and embedded in Teams and Microsoft 365 the AI, handles attendance corrections, leave applications, seat booking and hardware requests across more than 87,000 employees. It has resolved over 600,000 queries at roughly 100,000 prompts a month, verifies medical documents for sick-leave approvals, and cut automated campus-onboarding email effort by more than 90%.
A developer built a memory-provider plugin that gives the AI, the AI and Cursor one shared knowledge base, searchable with hybrid keyword, vector and knowledge-graph retrieval. The person's coding agent and messaging agent now draw on the same memory.
Last spring he gave an agent an API key with no cap on it. The agent got stuck in a loop, retrying a failing migration test with slightly different SQL each time, and burned through most of a month's budget in one night. Nothing malicious, just a loop with no exit. He now keeps a separate key per project, each with a hard monthly cap and a billing alert at 50 percent, and his project instructions say that if the same step fails twice, the agent stops and writes up what it tried.
Around Elmira and Corning, New York, event listings were scattered across library systems, a brewery site, a school app, chamber newsletters and Facebook, so people found out about things the day after. He had the AI build one page that checks 101 sources across three New York counties and part of northern Pennsylvania: 1,855 listings over the next 90 days, 1,767 events after duplicates are merged, about 250 in any week, at 159 venues. A cron job reruns it every six hours on cheap shared hosting, about 8,300 lines of PHP, and cancellations mostly handle themselves because an event disappears when its source stops listing it.
He had the AI make an app that controls his Mac fully from his iPad. It took two sentences and two follow up prompts, under two hours of work, and the app even built its own recorder to check its streaming sessions.
A materials scientist with a PhD and almost no coding background built and shipped a live stock portfolio tracker over about three months and 277 commits, pasting code blocks the AI gave him into a terminal and pasting the results back. The tracker is not about returns: it makes him write down why he bought a stock and what would prove him wrong, then pressure tests his reasoning and scores how well his past calls held up.
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.