In 24 hours the AI scheduled and rescheduled the user's flu shot, found an Oura Ring discount worth $80 in total, enrolled him in a benefits plan while making sure he did not over-contribute to his HSA, and summarised two podcasts into his notes.
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 man tired of losing his medical lab reports across emails and clinic portals built MedicalHistory.app with AI, first for himself. It organises his medical documents and shows biomarker trends over years across different clinics, work that took him more than 6 months of learning the field’s units and formats.
A runner's watch syncs while he sleeps; an app he wrote moves yesterday's Garmin data into Notion, and an AI morning brief weighs his sleep, HRV, training status, calendar, and weather to tell him when to work out that day - and how hard.
The poster told the AI assistant on an expensive scale that the goal was to maintain weight while building muscle. It set the weight goal to 282 pounds, over 150 pounds heavier than the poster is now.
This one went wrong. See what happened before you try it.
In its morning briefing the AI flagged a doctor appointment he had booked weeks ago, and he told it to remind him to cancel it later that day because a work briefing now clashed. The AI went into his email, found the confirmation, saw there was a $150 fee for cancelling within 24 hours and a cancel link, and cancelled it before he had seen any of that.
Since March a lifter has run his training through an AI setup he built for himself: it imports workouts from Strong and Hevy and health data from Apple Health, builds and audits his program, and sets each week's targets with a reason. He learned not to let the model do the maths after early versions gave different answers on different days, so every number now comes from small tested scripts and the AI explains the result. Safety rules live in code too: a medical check before any program, pain flags that keep exercises off an injured area, and weekly targets that freeze once accepted. He has since shared it as an open source plugin.
Since April he has logged meals and counted carbs in Google Sheets, and helps his wife do the same. He spent an AI session building a home app to make the logging simpler, shorter and more fun.
A triathlete uses a Garmin MCP through AI Desktop - forked because the stock version couldn't build his workout types - so the AI creates and schedules his swim, bike, run, and gym sessions, pushing them to his Garmin calendar, which syncs straight to the watch on his wrist.
A No Code MBA reviewer asked the AI to turn a six-month marathon goal into a 24-week training plan PDF. A long-horizon fitness goal converted into a structured, printable plan.
Her AI logs meals from photos, tracks workouts, and produced a Week 1 report with average calories, protein, activity days, deficit and pace; it pings her three times a day for water and generates weekly and monthly reports.
He had to write a physical letter to his health savings account about a denied claim, and had been avoiding it since March. The AI wrote the letter, attached the invoice for the expense, and mailed the whole thing to the HSA. His only job was taking over for the $2.31 payment. Whether the claim was then paid is not stated in the comment.
This only partly worked. Worth knowing before you try it.
Andrew tracked his Hyrox training in a spreadsheet by screenshotting his Whoop stats after every workout. He asked the AI to find something better; the AI connected directly to the Whoop API, and now whenever he says he finished a workout the stats land in his Google Sheet automatically, alongside strength sessions he dictates (like 5x5 back squat).
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.
Booking swimming lessons for his son sat on a man's task list, pulled from his email by the AI. The AI watched lesson availability on its own and booked a suitable lesson as soon as one became available.
He set up his own site, granu.be, and has the AI make reports from his diabetes data. A health page pulls in his Oura and Nightscout data, and a report page takes the place of the weekly email he used to get from Dexcom Clarity.
He had no family doctor and dreaded the admin of finding one. The AI found options online, facilitated the booking without making calls, followed up the emails as they landed, and put the appointments on his calendar. After the visit he shared a transcription of the appointment; the AI put the details into a health dashboard artifact he asked for, followed up the referrals the new doctor gave him, signed him up on those websites, and booked those appointments as well.
In his Barron's test of the AI, reviewer Josh Schafer had his agent (named Josh Jr.) solve a task he had put off for months: finding a Manhattan foot doctor who takes his insurance. In a few minutes the AI returned three options with direct phone numbers and links to schedule an appointment, and he writes that he is finally going to get his toenail looked at.
This only partly worked. Worth knowing before you try it.