A random mix from the whole library. Shuffle for a new set.
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.
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.
This summer he put the URL of FIFA's World Cup schedule into AI. The AI made him an ics calendar file with all the games in his own time zone.
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.
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.
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.
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.
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.
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.
The Neuron's reviewer asked his Dot Herman to deal with a simple email; Herman wrote a short reply in his voice and sent it before he had a chance to review. The message was fine, but he immediately set a standing preference to see outgoing messages before they are sent.
One of the demonstrated workflows in '11 Ways I Actually Use the AI (Real Examples)', shown via screen recordings.
In Vox's two-week agent feature, one tester asked Instinct to show possible replies after it flagged a couple of emails. The agent sent the responses it had written instead of displaying them for review first.
An operator had the AI set up a set of websites that pull publicly available but painful-to-access government data, present it in easy-to-read form, and send weekly emails - turning civic data nobody uses into a small publishing operation.
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.
He uploads his own data and points the AI to specific sources and documents, with examples he made before to show the format he wants. The AI then builds the tables and graphics for his Education Rights Project, public pages on education rights and funding in US states, with policy briefs, slide decks and interactive widgets.
The AI’s tools produced printable booth artifacts for a nonprofit he advises; in about 30 minutes he had a professional PDF uploaded to FedEx Kinkos for printing.
He needed to know if a library near him had outlets. The AI offered to call, gave him the choice of an AI voice or a person and a male or female voice, showed him what it would say, then called the next morning, confirmed the outlets, and gave him the transcript.
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.
The municipal election had a huge list of candidates and felt overwhelming. She asked the AI to study them and build a short quiz that asks voters their views, then ranks the candidates to match, with links to their platforms so people can check.
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').
LLM reverse engineered the LADBS API protocol and extracted the permit content he wanted, thousands of records extracted.
Outside code, his biggest win is boring paperwork. The AI filed his reserve duty refunds, sorted out his national insurance payments and did his flight check-ins, working in his own logged in Chrome. Each job is about ten minutes of work, which is exactly why he kept putting them off. He gives each area of his life its own folder with a CLAUDE.md and a notes file, so the money stuff does not mix with the rest.
Dots monitors his communication channels and surfaced buried and filtered email messages that were important.
Created a UK council planning applications scraper with AI, which also built a debugging front-end and MCP interface he checks regularly for run status and coverage gaps.
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.
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.
Ekaterina Li (someone) ran AI as a full personal assistant for one week, delegating eight tasks from idea to execution. In the thread's comments she adds that she pays $20/month for the AI and considers it sufficient for everything she asked.
Nick Olsen built a system where the AI auto-generates and prints a daily briefing each morning: motivational quote, today's calendar and task list with checkboxes, week preview, Facebook/Google ad spend and performance, fitness checklist, summaries of children's school emails tailored by child, email-derived reminders (bills, urgent items), a daily comic, and a blank notes section.
He pays per token for small API jobs. One of them reads his incoming SMS messages and decides which ones are calendar items, like dentist appointments and the weekly school notices. The whole setup cost him $1.50 over six months.
His agent, with read-only email access, notifies him about important email about twice a day, including contractor mail and AWS alerts.
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.