A random mix from the whole library. Shuffle for a new set.
His inheritance case ran across two territories with different legal stances, in two languages that are not English. Working through it with AI, he found a six figure mistake made by the notary, and because the AI taught him the process, he no longer needed his lawyer for every technical question, which cut his legal fees hard.
He runs AI on his homelab. He can ask the AI to throw an event on his calendar and it appears, and the setup can also send events to his primary calendar by email.
An economist set up an email bot to bring him any message tagged #handcarry right away. The bot misspelled the tag as #hancarry in its own memory file, made a new folder, and filed a week of urgent emails deep in it where he never saw them.
The same Cowork setup checks his father's email for work orders and schedules his father's meetings automatically. He turned off data sharing with AI for this, so the mail is not saved anywhere else.
His claim was too small for a lawyer and the insurer had frozen it at $4,430, so he worked it himself with AI holding every letter in order. The agent surfaced six dated contradictions in the adjuster's own letters, including a legal basis for denial that changed three times, and reviewed each of his drafts as opposing counsel before anything was sent. After his letter quoting their own paper back at them, the offers climbed: $6,500, then $8,000, then $8,750, and the insurer accepted his split of the last gap the same morning, at $10,250.
The AI prepared and filed Australian visitor visas for a couple travelling to Brisbane, and caught a placeholder birthdate in the details before submission, confirming the correction over WhatsApp.
He gets 215 GitHub notifications a day, so he built a bot to triage them.
A team used an AI 2.5 tool to go through large sets of public comments. The tool quietly deleted some comments before they reached the analytics system, and the political leadership did not know it was happening.
Agency owner Rui Fu (someone, 253K followers) demonstrates the daily system he shows for the AI: an 8 AM scan of the last 24 hours of Instagram DMs, categorised into brand partnerships, collaboration requests, fan messages and spam so he wakes up to only the important ones. The tutorial also shows an auto-reply rule for guide inquiries and offers his prompt guide in exchange for comments.
Lixka, an accelerated nursing student at Mercy University, uploaded all six syllabi to her AI 'Mila'. Mila identified that Monday, September 28th was a 'triple-header' — two quizzes and a Pharm lab she hadn't noticed — then built a sustainable weekly rhythm around fixed classes, clinicals, and workouts, and asked permission before creating three tracked goals: quiz prep, reflection paper, and workouts/downtime.
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.