A random mix from the whole library. Shuffle for a new set.
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.
He uses AI to turn screenshots and emails into calendar events. He also uses it to find email receipts and tickets when he needs them.
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.
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.
Someone posted an illustration styled as an iPhone call-history screen showing seven missed calls from unknown/spam numbers over three days (fictional numbers noted). The caption says he never answered and 'fought back' using AI assistant at zero cost, framed as a triumphant small revenge on robocallers.
Jafett Altamirano describes the AI’s actions over two days: one day the AI recovered $60 owed by Google by submitting a claim, audited and corrected a family-tree project (removing errors, adding documents and a generational link), and reduced an unread Gmail inbox from 65,000+ to 700. The author emphasizes all of this was free.
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.
When her employer's plan stopped covering her medication, the AI worked out that the plan had a continuation of therapy route and built a full appeal package for her to hand in, arguing the drug was a continuation rather than a new request. She filed it, and her doctor used the letter template it wrote.
The developer set a scheduled job in plain words: every weekday at 8:30, send events from all calendars plus emails needing a reply, in five lines or fewer. The first run arrived at 8:44 with an apology for the delay, covered all 16 calendars, removed duplicate events and listed private events by time only.
The AI updated a website he manages for a charity and on its own scanned beneficiary header images to add information to the writeup; done well.
The author describes using AI to resolve a six-month-old travel medical insurance claim with Cigna. The AI called the insurer, was transparent about being an AI, conducted the call politely (impressing the representative), and — because final consent was required — called the author's phone and connected the parties so he could approve verbally.
The author reports the AI reduced his unread Gmail from more than 65,000 messages to about 700.
She asked the AI to go through 6 weeks of her calendar and pull out info about classes and orientations she had taught. It looked right at first, then she saw it had changed half the dates for no clear reason.
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.
Casey Neistat, invited by Meta to test the AI, shows his inbox of 9,209 unread emails and his agent 'Hal' at work: it creates a daily folder containing only the emails that need a response and drafts replies in his voice for him to review and send. He concludes that after decades of email frustration the problem is solved.
He updated an old email triage workflow for a client this weekend. Jev now runs alongside GPT-4o mini, which still controls which emails get forwarded to her customers.
He connected his Gmail to an AI task that watched every new email and was only allowed to interrupt him when a message needed action or came from family, with a draft reply ready. All afternoon it alerted him three times, for a bank message, a family email he answered from its draft, and a ticket itinerary change he needed to act on.
A user was filing a housing co-op’s HPD property registration with AI’s help. Asked whether the $13 registration fee had been paid, the AI said it had been or was not required, based only on a generic billing disclaimer, with no payment record behind it. Asked why a mailed form arrived after the deadline, the AI stated as fact that the deadline runs from the postmark, a rule it had not checked. Both claims were corrected only after he challenged them. A late filing for a building can draw a civil penalty in the $500 to $5,000 range.
His local school division released the raw answers to a touchy redistricting survey as one PDF of more than 3,000 pages, which nobody could realistically read. He used AI to write scripts that pulled the answers out and built a public web page where people can search the responses and filter them by keyword and by school.
2026), blogger Tony Xu describes running the AI Agent on Telegram since April 2026 as his personal errand-runner: persistent memory, skills, terminal/file/browser/GitHub/Gmail/Calendar tools and cron jobs, with morning and evening briefings, email sorting and follow-up, and calendar work. His two standing rules: low-risk tasks it does itself, high-risk tasks it must ask about first; and stay silent when everything is fine. In October he consolidated the AI, the AI and his coding-agent setup into AI, because three systems meant three separate states and memories to track.
Rachel D. Gainsbrugh (someone, ~3.5K followers, AI/systems creator) signed up for the AI on Sept 13, 2026, connected her calendar read-only, and typed six standing errand rules once — including a 7:05 AM daily calendar scan that flags overlapping meetings or ones falling inside a flight — then handed it two long-dodged errands (an appointment blocked by a flight, a subscription update).
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.
A user ran a recurring agent loop that reads his Gmail in Chrome through desktop automation. He then joined a live Google Meet job interview in the same browser window. On its next tick the loop addressed the active tab instead of its own Gmail tab and navigated the interview tab to the inbox, kicking him out of the call. Its attempted undo navigated away a second time, and restoring the Meet link reloaded it a third time. Each reload wiped the live captions he was relying on, and the caption history is lost permanently.
Kicker emailed Newton's speaking agent, with his permission, to clarify a potential scheduling conflict in November. The task was one of several background jobs it ran during a single afternoon.
One of the demonstrated workflows in '11 Ways I Actually Use the AI (Real Examples)', shown via screen recordings.
The AI cleared an inbox of 100,000 emails during the user's workday, leaving a manageable mailbox behind.
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.
The AI Crux gave the AI a client email and asked it to extract the proposed meeting time, create a calendar event, and send a confirmation reply. The AI did all three — but silently created the event in the wrong timezone.
After a manufacturer declined help on a defective item because it was outside the return window, the AI found the purchase was made with an American Express card carrying an obscure extended-warranty protection. It submitted the claim on the author's behalf and obtained the refund.
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.
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.
TechMitra founder Ayush Singhal asked the AI to triage his Gmail thread by thread. It proposed archiving ten promotional emails, correctly found nothing to do on other categories, and unprompted flagged a spam comment on his second website. After his approval it archived nine FYI threads and left two genuine action items.
Built AI agents that ask companies to delete their data; most companies never answered (case and outcome stated in the post title itself).
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.
His charity food pantry needed a barcode scanner and stock checker but could not afford a paid system. He built one with AI in two days, and it now runs on a laptop in the pantry.
His phone already blocks most spam calls. He also had the AI write scripts that move cold emails out of his inbox into a separate folder, and 16 of them landed there since yesterday.
The AI was fed government forms, UI design and legal requirements and produced the app in 1 hour; the team completed conversion of 150+ forms in 2 weeks with one person versus a year before.
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.
UFC fighter Justin Gaethje (verified, 3.7M followers) introduced his AI 'Highlight' for his training, travel, and business schedule. A notification reminded him of a Phoenix flight; he asked for tee times and the app showed options (Legacy, Aquila, Raven, Encanto) — he booked Raven Golf Club at 1:30 PM.
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.
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.