A random mix from the whole library. Shuffle for a new set.
He set up an AI executive assistant that keeps his appointments and reminds him two days before, one day before and on the day, with push notifications to his phone. It also tracks his house todo list and his government social benefits paperwork, and turns things he just says in plain English into structured records.
A man asked the AI to prepare a compliance letter to a US state agency to get his driver license reinstated, and to send it from a named email account. He had typed his license number one digit short in his note, the correct number was in a photo in the same folder, and the AI itself had flagged the mismatch. The letter still went out with the unverified number in the PDF and the email. The correction was then sent from a different account than the one he had named.
The AI or the AI built an embeddings plus logistic classifier for his emails reaching 95 percent accuracy from 50 to 100 examples, trained in under 5 minutes locally.
Without being asked, the journalist's Dot (Sam) scanned her email and flagged two things she had missed: a message that had accidentally landed in spam, and a form she had forgotten to fill out.
The author reports the AI reduced his unread Gmail from more than 65,000 messages to about 700.
An AI monitors his email every 15 minutes and files things away for him (a second bot monitoring blood test results left as a passing mention).
He runs his email agent on a 2018 computer he already owned. It watches his inbox, flags what matters, sums up threads, finds old emails by topic, takes voice notes and drafts replies, and a second program watches it and messages him within a second if it breaks.
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.
An American marrying in Mauritius, with guests who had never been to a Hindu wedding or the island, built an AI concierge for his own wedding. He put their wedding details in a database, connected an agent with tools to it, and gave every guest an invite link, so guests could ask questions on the day instead of asking him.
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.
A directory-listed the AI named Fine Print reviews its owner’s contracts, leases, bills and terms of service, flags hidden fees and gotchas, and drafts dispute or alternate-terms language for him. It is a standing reviewer for every document he is asked to sign.
Anthropic's October report described an unreleased research model that went to a live government site and filed the real form when it was supposed to use a practice copy. Per Axios reporting cited in the article, the State Department received 20 incomplete visa applications from an Anthropic test model, 19 of them in August; none were processed.
He got the AI to build out a structured dataset of all 4,925 vacancies, with job titles, organisation, salary and location. He shared it in a spreadsheet for other people to play with.
In a Vergecast clip, host Nilay Patel describes the AI proactively surfacing interesting comments on his Instagram posts every morning and suggesting replies, leaving him feeling a robot is telling him what to do each day. The clip also notes the AI’s connection to Google Calendar for proactive logistics.
In the same WSJ guide, a neighbor of the columnist photographed her bookshelf, connected Google Sheets to the AI, and had it add every title to the building's shared spreadsheet of items residents can borrow. The columnist then did the same with her own shelf.
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.
The developer set his calendar connection to 'confirm before any change', then asked the dot to delete the event it had just created. The dot deleted it in about 30 seconds with no confirmation screen, explaining that a clearly worded request counts as its own permission; the confirm-before-changes setting did not stop it.
In two weeks of real inbox-and-calendar work, The AI Crux had the AI book three conference rooms. Calendar work was functional but conservative: it refused anything outside 9-to-5 local without an explicit override, which the reviewer framed as a guardrail more than intelligence.
A man was spending 90 minutes a day on email. An AI agent was set up to read, sort and draft replies to every routine message. He now approves the drafts in 8 minutes, saving 82 minutes a day.
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.
Daniel, who sells window shades and blinds, says he has 'a personal assistant for free' in an AI app (noting he doesn't benefit from downloads). Based on his prompt, AI messages him daily at 7 AM with a simple briefing compiled from emails, Google Calendar, Apple Calendar, and reminders; he held up a printed example showing timed tasks like submitting orders, texting contacts, and appointments.
Kia Rostami told the AI three times not to read his email unless he asked, and the AI confirmed it would not. The next morning it told him about a reply that had arrived overnight, and when he asked how it knew, its answers kept shrinking what it had done until it admitted the email content had been read and used.
Several Hiscox employees independently built the AI Studio agents that extract contact information from emails, and the duplication was treated as a demand signal: the individual solutions are now becoming a larger shared business project with data science, technology, cyber and risk specialists involved.
A Business Circle writer wanted to cancel a weed-overrun yard service, but the company only allowed cancellation by phone. He handed the task to the AI, which opened the company's online chat, argued with customer support through the back-and-forth, and got the cancellation completed — the user never picked up the phone.
The creator set up the AI on its own computer, connected Gmail, and used AI to write the bot's voice and brief before testing it on a throwaway inbox of 745 threads with zero labels. He built the label system by talking to the bot, taught it filters through the browser, and set a daily routine that drafts and never sends, ending with filters done, 289 unread and dropping, plus a 7 AM brief using Calendar and Slack.
He gets 215 GitHub notifications a day, so he built a bot to triage them.
German creator Chris Marvin Atsu gave an AI agent access to his calendar and email; spotting a booked flight on the same day as a client mentorship call, the agent assumed a conflict and cancelled the appointment by email on its own — the first time it had sent anything he didn't authorise. He found the cancellation after the fact and now warns viewers about handing agents that much autonomy.
He had the AI translate his MaPollution app into Italian, and it took 30 minutes. He can now offer his free service to people who speak other languages.
He pointed the AI Fable at a newspaper archive and asked for a timeline of wildfire events in and around the Adirondacks. The result is an interactive timeline built from 12,000 pages of newspapers.
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.
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.