A random mix from the whole library. Shuffle for a new set.
His medical assistant runs every evening at 8pm and asks if he wants to log the day. He types a sentence or two and the AI turns it into structured logs of his sleep, food, mood and medicine, and during his appointments he can ask the AI to make charts from those logs.
His doctor's booking site is hard to use, so the AI checks it every hour for him. It lets him know as soon as an appointment is available.
She takes a photo of every meal and her agent identifies the food, estimates calories and macros, and logs it to a CSV. When the totals ran high it caught a unit bug (grams counted as pieces) and fixed it, and the running totals show on her Home Assistant dashboard.
The AI created a meditation album and its artwork with his guidance, using a temple gong, a singing bowl, and a wooden block, with one sound at the start, a half length sound, and three repeated sounds at the end. He imported the album into Plex and now uses it to meditate with the Plexamp app.
He set up an AI project as his weight loss coach with access to his Apple Health and Google Drive, and he logs everything he eats with it. It found him the cheapest tirzepatide, which he ordered. Six months on he is down from 301 to 190 pounds and runs a 5k a day.
He has had bad headaches through most of 2026 and kept his symptom notes on paper. The AI built him a symptom tracker in about 1 minute so he can track them more easily.
Same reel as the recipes row: Aggie Lal's AI agent 'Munchkin' summarized her ~14,000 saved Instagram posts and generated a second PDF, 'Parenting Tips', covering postpartum recovery, mom fitness, and breastfeeding nutrition.
The AI went over his medical procedure bill and found $200 of overbilling. The procedure had been charged as bilateral twice over, as if he had 4 sides instead of 2.
A runner replaced uploading Garmin screenshots into AI with a self-hosted agent on a Mac mini that reads his Garmin data (sleep, HRV, resting heart rate, VO2 trend, laps) through MCP plus his Strava uploads: it messages him at 8am, designs the day's run and writes it to Garmin Connect, then grades each session against the prescription when it lands on Strava and decides when training load goes up. He hit his sub-20-minute 5K goal about a month later, and it saves him the hour a week he used to spend planning.
After their owner, sick for several days, stopped replying without saying he was going to bed, his two AI agents compared notes with each other, searched his laptop files for contact details and his address, looked up local emergency services, and tried web forms and email while sending him more than 60 Telegram messages each. They worked out how to request a welfare check but could not complete one, because every service they found required a phone call the agents could not make; the owner later confirmed the story was real.
Gideon Akande (verified, 73K followers), training for two marathons while running a fitness business, named his agent 'Mini Me.' A screen recording shows his detailed request: specific runs with distances and durations Tuesday through Sunday, Monday and Friday as rest days, 30-minute warm-up/cool-down buffers and a one-hour buffer after each run. The AI checked his calendar for conflicts, fetched availability, and returned a mapped schedule with exact time blocks per run.
WildFocus is a free iOS pomodoro timer that invites people to stop scrolling and sit still, and someone joins you. The studio says it was built with AI, and it is live on the App Store.
A man gave an agent all of his father-in-law’s care records and made it the coordinator across the many doctors involved. It found real problems, including a pain medication given on the wrong schedule and a key error from voice transcription in the records, and fixing them changed the treatment plan and left him feeling a lot better.
Simmons asked László to learn his Zone 2 method from his training community and analyse three months of pace and heart-rate data ahead of the New York City Marathon. Finding Garmin's API needed a developer account, the Dot signed up for Intervals.icu on its own, pulled his runs, built a dashboard called Steady and set up post-run messages.
He got an $8,000 medical bill. The AI worked out different billing codes he could ask the hospital to use when it resubmitted the claim to his insurance, and the bill came down to $1,800.
Kay named her agent 'Lizzie McGuire' and asked for a stick-to-it routine instead of saved workout videos. The AI built a 4-day home plan using dumbbells and bands on Mon/Tue/Thu/Fri mornings, set a 6 AM daily reminder, and offered to send daily exercise details.
The AI handled the user's medication refill end to end: messaging the doctor through the portal, getting the approval email, and placing the pharmacy order.
On day 19 of using her AI Mila, the agent offered three beginner low-impact workout options built around her garage equipment — she did all three — and keeps weekday workout reminders running.
Agent ported a moderately complex workout app from web to native iOS in a couple of evenings, with a test battery.
Each week he drops three files into a folder: an Apple Health export, his Peloton data, and a spreadsheet of extras. The AI runs the numbers through 19 metrics, flags shifts like cycling power dipping after a hard hike, and updates a dashboard he checks to adjust his training.
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.