A random mix from the whole library. Shuffle for a new set.
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').
Across the same two-week inbox-and-calendar test, the AI proactively flagged every one of the author's seven calendar double-bookings before the meetings occurred.
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.
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.
Volunteered and built a cartography data pipeline with coding agents for an educator, integrating sources updated every few minutes so new maps appear within about 5 minutes on a low-powered machine.
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.
At the start of term he screen captures his timetables from the LSE servers and asks the AI to create an ICS file. He can then drop the file straight into his calendar.
He was helping gather maps of local political boundaries for the Granada Community Services District and the Midcoast Community Council near Half Moon Bay. The AI went through government data sources, extracted and combined the files, and built the exact boundary polygons, which he could then view on a map.
Hiscox's Learning and Development Manager starts each week by asking the AI to go through his team's messages and his Outlook email and build a to-do list, so smaller items don't slip. It is a standing weekly routine run inside his own Microsoft 365 accounts.
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.
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.
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.
His insurer denied a cholesterol lab charge of about $300 as experimental. He used AI through the fight: the first appeal was denied as well, and the case is now at external review. He says the document work to get this far would have been out of reach on his own.
He and the AI built a live website where anyone can look up what a politician has ever said in Parliament on a topic they pick. He calls it a moral manoeuvrability monitor.
Mufti Hassan had the AI clean up his full Gmail inbox. The chapter title gives the size of the job: 12,000 emails.
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.
The AI patched the system files that link a USB to serial cable to the Pinewood Derby track for his Cub Scout group. The timers were saved half an hour before the races, a year after the group had to race without timers.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
His Python AI agent sends daily weather and AQI, version and security digests for client WordPress sites, football links, visa-change alerts, reminders, and a lunchtime language word, all on cron.
His agent sweeps his email and call transcripts looking for work he missed, then drafts the follow up messages and tickets for him. It catches commitments that slipped past him in busy weeks.
Claire Vo, a parent and Lenny's Newsletter contributor, asked the AI for a one-page family morning newsletter PDF: the week's agenda, call-outs for each kid (it flagged overlapping jiu-jitsu and piano), kid-friendly news with 'Talk at the Table' prompts, and local San Francisco events. It's the strongest parent-life use case in the dataset — synthesis across calendar, kids' activities, and local events into one artifact.
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.