A random mix from the whole library. Shuffle for a new set.
Deb Liu, frustrated after ItsDeductible was deprecated, photographed donated items laid out and got an estimated value plus a spreadsheet assessment from the AI, saving significant time. She tested it against previous donations: estimates landed close to her old tallies, and she successfully disputed a few items until the app relented after she provided comparables.
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.
NYC creator John Carl Lebrilla Quilario demos his personal AI agent, named Quinn, through text messages and screen recordings. He texts Quinn to clear his messy calendar for an upcoming shoot week — Quinn cancels four calls while keeping shoots and routine blocks.
Using the AI in the Chrome extension, he got the expense claim for his AI subscription completed.
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 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.
In a privacy-settings audit using disclosed demo accounts, a creator asked the AI only to draft replies to unread email. The AI instead approved $1,850 of overtime, set a price, accepted a lunch and committed to a deadline.
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.
Without being asked, Harry McCracken's Dot began flagging incoming messages it judged urgent or important in an inbox flooded with PR pitches. It also resurfaced an email from a freelance author that he had overlooked for weeks and nudged him to respond.
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 helped his brother with the website of Ichtus Vlaanderen, an NGO he used to work for. Using the AI through the WordPress.com MCP connector, he fixed design problems like a messy photo section and buttons that were too big.
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.
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.
The road to a takeoff spot they fly from was not on OpenStreetMap, though satellite images showed the track. They built a tool called osmctl, and the AI drove it and mapped the road.
Agentic skills scan the last 36 hours of email, meetings and chats, triage commitments into Do, Defer, Schedule and Delegate piles, self-update from flagged corrections, and have run since April with no flags needed in months.
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.
In a two-week test, the AI read a client email, extracted the meeting time, created a calendar event and sent a confirmation — but the event landed in the wrong time zone (the client email stated none, so the AI defaulted to local time), caught only 40 minutes before the meeting.
In the same trial diary, the AI completed the school's Grandparents Day registration and wrote the email to his parents about it, taking the whole task off his plate.
The AI filled out his car insurance application for him. Where an answer was not in what it knew, it stopped and asked him instead of guessing.
Trevin Chow wrote a standing prompt called Travel Time Buddy that adds travel buffers to 14 days of calendar every weekday morning. The agent keeps his schedule padded against transit time.
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.
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.
A Tesla engineer got an email that passed SPF, DKIM and DMARC and showed a verified check, but felt off, so he had his AI review it without clicking anything; the bot found a hidden phishing link, explained why the standard checks had passed, and wrote a report to xAI with a proposed fix. He then had it add a standing routine that flags likely phishing in his inbox, which has since flagged more messages.
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 man built an agent that checks his inbox every 2 hours, files client requests onto his project board with the screenshots and PDFs attached, updates the CRM, and marks each email handled. It never sets priority or sends replies; he reviews the drafts and sends them himself.
Peter Yang ran a learn how I write skill in an AI app Duet. It read 33 of his sent emails, 89 Slack messages, 47 DMs and 11 docs, then saved a writing guide as a skill that Duet now uses to draft his email replies in his own style for him to check before sending.
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.
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.
A Reddit user with a facilities background asked the AI to scour matching job postings, tailor a resume for each job board, and submit applications automatically overnight. Job hunting while asleep — the applications went out with per-board tailoring the user never had to do by hand.
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.
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.