A 20 page report the AI wrote got his stolen motorcycle claim paid in full
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.
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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.
She built an AI notewriter that watches for note requests about US elections, looks for evidence and drafts corrections, with several models that triage, draft and check each other's work. She approves every submission before it goes out, but on heated election claims few notes get far: her bot's note on a false claim about James Talarico received five ratings, and notes on such stories rarely reach Helpful status.
Cat (green glasses, plaid shirt), preparing for an interview with limited time, introduced 'Brio' (pink abstract avatar) as her AI. Screen recordings of a messaging app show her asking Brio to block calendar time; Brio confirmed a 2:00-3:00pm block and offered to run through questions.
Eleanor Konik had the AI and AI team up on dashboards for local nonprofits. The AI did the early research and dug up grant chances the groups had not seen, like a group that pays for field trips to battlefields, a free textbooks program for private schools, and creative arts projects, and the lists were put behind a password for her friends to use.
Hemant Kadam, demonstrating his 'craziest use case' after a couple of days on the AI, opened the app to a Sarvam DevOps Engineer application page. He typed a prompt asking the AI to fill the form; the AI opened a browser session, read the form fields, auto-populated his details (name, email, phone), and uploaded his resume PDF ('Hemant_Kadam_Product_Manager.pdf').
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.
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.
She says she used AI, cross-checked by two more AIs, to put together a legal complaint and file it herself, without a lawyer.
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.
Calling sellers about his orders was one of Josh's biggest pain points — so the AI took it over: it called a seller to correct his shipping address, and called a seller to resend his missing orders.
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.
Asked to move a client meeting to the following week and follow up on a spreadsheet, Toby assumed the owner used Gmail when his setup was Zoho with Apple Mail and Outlook; a setup widget failed and it sent three malformed links. Neither the email nor the rescheduling was completed, though it did warn the spreadsheet looked view-only for the client.
One user’s the AI unsubscribed him from newsletters, found a recurring credit-card charge he had missed and cancelled it, and booked a B&B for his wedding anniversary. Three different errands, one agent, all completed.
Ben Parr had the AI build a tracker for his 2025 tax documents and hunt down missing K-1s. The agent organized the paperwork and chased the missing forms.
He is juggling several legal cases of his own, and his lawyers do not have time to answer him every day. The AI transcribes audio, organizes his evidence and writes the case summaries he hands to them. He calls it the best tool he has ever had, and says stopping would mean going back to doing all of that alone.
He built geo-v.eu, a live calendar of EU political and economic events that runs to 2028. The AI Haiku judges each candidate event against his written editorial standard, the pipeline hunts for the outcome for five days after each event, and the site rebuilds daily from static files.
Liberty RPF's author tested the AI heavily himself after it launched in Canada, but his wife's onboarding was the telling detail: delighted by the mascot, she renamed it, changed its color, and asked it to review her email inbox daily — her first real agent job.
He had the AI collect his will and trust documents and check them against state statutes. The review found missing signatures, an illegal clause, and outdated law references, and he fired his attorney the same day.
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.
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.
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.
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 WSJ reviewer gave the AI four dates and times plus her preferred sitters for a notoriously convoluted childcare-booking platform. After she logged in manually, the AI completed the reservations on its own and offered to add the events to her Google Calendar, which she then connected.
The AI called car dealerships and plumbers to collect quotes for the user and scheduled a dentist appointment, the calls and booking done in about five minutes of the user's time.
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.
Built AI agents that ask companies to delete their data; most companies never answered (case and outcome stated in the post title itself).
He had the AI work out how the When2Meet scheduling site works and turn it into a skill. Now the AI can read his calendar and fill in the When2Meet availability grid by itself.
She asked the AI if it could cancel her Mint Mobile account. The company's chat agent had told her she needed to call in. She gave the AI her Mint details, the AI opened its own chat with the company and got the cancellation done, with no phone call and no talking to people herself.
Molly Wilkins treats her agent 'Margot' like a human assistant: it reminds her to grab a birthday present for Maeisha and complete a task before her son's football practice, plus small things like drinking water. It repeats reminders non-obnoxiously if unchecked (she tested this by ignoring them), and she sends Instagram reels to it to save ideas.
He asked the AI to screen his unread Instagram threads one morning. It came back with 50 unread, looked at the threads he named across his Primary, General and request folders, and told him what people had sent. The unread count was still 50 afterward, so nothing showed as read for him or for the senders.
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.
Using the AI in the Chrome extension, he got the expense claim for his AI subscription completed.
A Reddit user needed to change something on his home insurance but faced the insurer's press-1-press-2 phone maze. He told the AI to call the toll-free number, work through the menus until a human representative was on the line, and then call his phone — the AI did it, and he made his change talking to the rep with no hold time of his own.
Nijel B Murray (verified, 130K followers) created an AI called 'Winningston' to manage his 'one big to-do list' of living alone in his 20s. Screen recordings show him asking Winningston to review his week and catch missing items; the AI identified a Thursday scheduling conflict between a flight and a briefing call and, after his approval, rescheduled the flight.
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.
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.
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.
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.
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.