A random mix from the whole library. Shuffle for a new set.
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.
Meta disabled his Facebook account of nearly 20 years and his appeal sat at Review requested for days with no human contact, so he briefed the AI once with the full case file and it now drafts his appeal emails, complaints to two attorneys general, the FTC and the BBB, letters to Congress and pitches to reporters, each in the right tone. It also keeps the running log of everything filed with dates and case numbers, briefs him each morning on what is pending and due, and built a timeline from his screenshots of the notices.
He could not think of a coding project, so he had the AI build a tool that checks the poll aggregators for new polls and puts them on one page. He now hears about new polls about five minutes sooner.
Commenting on the 26 use cases post, he says his AI books all his haircuts: he just says book a haircut on a day at a time, and the email confirmation comes in. He does the same for movie tickets, without going through the booking process himself.
After his motorcycle was stolen, his insurer offered nearly half the market value. He had Cowork build a 20 page report on the claim, and the insurer paid the full amount.
A local model helped build a self-hosted services wiki and dataset in an Obsidian vault so his partner could keep systems running if he died, set up in a few hours.
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.
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.
A church volunteer runs a weekly hybrid workflow: The AI translates six Chinese daily spiritual messages (Monday–Saturday) into structured JSON under strict rules — Bible quotations in NASB 2020 rather than translated, hymns left untranslated, ministry terminology matched — then Python inserts the text into a PowerPoint template, merges a bilingual twelve-message deck, and converts it to HTML for the church website. He keeps theological review, visual checks and final publishing approval human on purpose.
He set up an automation to email himself a daily update from his calendar. Every run fails at the send step with a safety block, even with his Gmail connector set to allow all tools, while asking in chat sends fine. He rebuilt it several ways and every version stops at the same 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.