A random mix from the whole library. Shuffle for a new set.
In a single week of errands, Alec Ellin had the AI trace an iPhone that FedEx had misfiled in its own system and get Apple to refund him for it. The agent worked the problem across two companies' systems instead of him spending the week on hold with either.
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.
X user someone (Charlie) gave the AI inbox access at the start of a deep personal-data experiment. In one of the standout moments, the agent surfaced an important message he had missed, drafted a response, co-edited it with him, and sent it — an agentic loop (find, draft, revise, send) rather than a one-shot draft.
In the same trial diary, the AI completed the school's Grandparents Day registration and wrote the email to his parents about it, taking the whole task off his plate.
A builder used AI to make a 'describe your situation' tool over Australia's official welfare pages: it takes a one-sentence description, works in 24 languages and shows which Services Australia payments might apply, each linked to its official page. Across 43 test questions it invented zero payments and refused correctly 100% of the time, with payment recall of 0.76.
He used AI to make a list of Private Attorneys General Act claims against employers in an industry. The list was made in support of an organizing drive, and he says the tool is almost always helpful on tasks that involve a lot of data.
Ahead of an apartment move, a reviewer asked the AI for a day-by-day packing schedule. The AI built one with sessions capped at 30 minutes, sequencing items so things the person won't need before the move get packed first.
Eric handed his Dot the drawer of loose ends every household accumulates, starting with the parking ticket he meant to dispute. Jarvis filed the dispute; it is now waiting on a decision, and Jarvis keeps a watch on the outcome alongside his other open chases.
A non-developer used AI to restore his foundation's broken donation payments and restructure the portal into four separate funds; the site shows $17,149,000 in donations processed.
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
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.