A random mix from the whole library. Shuffle for a new set.
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).
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.
Grupo Marista uses AI Enterprise agents to analyze hospital claims. Analysis that took 72 hours now takes 4 hours.
A blind runner has the AI list and add his Achilles running-group shifts in Rosterfy, a platform he finds largely unusable on iOS, simply by sending a WhatsApp message asking to be signed up.
He gave the AI his home address and asked for 5K and 10K loops from his house using OpenStreetMap data. It worked for 27 minutes and gave him both routes as a map he could view and as GPX and GeoJSON files he could download.
Her mom normally needs a care service to take off her compression stockings. With the AI she found a way her mom can do it alone in an emergency, her mom tried it and it worked, and her brother no longer has to come over when the care service fails.
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.
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.
The AI searched for the earliest available appointment with a specialty physician and found one in about a minute of searching.
Vo asked the AI to set up a gentle sleep-training goal for her eight-and-a-half-month-old, noting the family room-shares in a small house. The AI created a gentle action plan with automated reminders tailored to that constraint.
X poster someone set up an AI morning digest that links blood-glucose data from Apple Health to food spending pulled from Plaid and DoorDash emails.
He forgot to charge the batteries for his road bike's electronic shifting before a ride last week. After a weekend of back and forth with AI, he now has a dashboard that can alert him when things need to be charged.
A hands-on PeloBuddy test had the AI build a split strength program anchored to real Peloton classes, producing a designed PDF in about 5 minutes and scheduling 12 classes back-to-back on the user's calendar.
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.
As an aside in a design interview, the AI designer Alex Cornell describes using his own the AI to track his golf game shot by shot while working toward a single-digit handicap. The AI produces round recaps, shot data and practice breakdowns (segment from 21:40).
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.
A 14 person dental practice on Daniel Island had $612,000 of diagnosed treatment that patients had never booked, and the staff's own AIs (six the AI, four the AI, two the AI) now read each day's patient notes every evening, offer open slots to the longest waiting patients and book on a yes. Of the $612,000, $188,000 of work is done and $241,000 more is booked, and same month bookings rose from 38 percent to 71 percent.
Marty (MartydudeVR, 6.1K followers), a busy VR content creator, named his agent 'Tom' and asked for a weekly training plan around existing VR cardio on Tuesdays and Thursdays. Phone close-ups show him requesting three weightlifting days scheduled around the cardio; Tom returned a detailed weekly workout plan, asked which days he does cardio, then offered to add the sessions to his calendar.
He had the AI take a 45 minute run from a chat and save it as a structured workout in his Flow State calendar: a 10 minute warm-up, six rounds of 3 minutes at 5:00/km with 2 minutes easy, and a 5 minute cool-down. The AI sent it to Garmin Connect, then added pace targets to the warm-up and cool-down parts and updated the same Garmin workout with no duplicate.
A commenter describes a local desktop app the AI helped him write: a script runs daily to pull his LoseIt nutrition and Garmin workout data into a local database, and an MCP link lets the AI review each day in a small browser UI, give advice, and plan runs or swims toward his goal of losing 40 pounds.
Lianna Torres (down 70+ lbs, still working toward her goals) asked her agent 'Clover' for a personalized workout at 5'3"/188 lbs targeting stomach fat and overall toning. The app asked about injuries, then generated 'Day 1: Full-Body Foundations' (bodyweight squats, incline push-ups), which she followed on her TV at home.
A dad’s the AI searched for dentists near him for his son, verified which ones accept their insurance on the offices’ own sites, and made the appointment on its own from its web browser, the first time it had done so. He got the confirmation by email and text without calling anyone.
A solo builder started runclub.events in May 2026 with an idea and no code, opening the AI for the first time. Sixteen weeks later the app is in production with 990 commits, more than 53,000 lines of code, and 160 features live, helping run club members connect on upcoming races.
His gym opens class bookings at 6am the day before and the popular classes fill fast, so he used to set an alarm for 6 just to book. Now an agent does the booking for him every morning and he sleeps until 9.
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.
Commenting on the 26 use cases post, he says he has the AI building dashboards from all his Samsung Health metrics. He has one for weight, BMI and body fat percentage, another for daily steps, a third for exercise, and a separate one with gas gauge style dials showing weight loss, daily steps, exercise minutes and activity calories burned. He shared screenshots.
Her AI produced a 'Starter Week - Cardio & Stamina' plan (Sat Sep 26 - Sat Oct 3, 2026): three cardio and three Pilates mornings, no equipment, 15 minutes, beginner level; the reel shows her morning briefing and the workouts done at home.
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.
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.
He downloaded his Apple Watch Fitness app data and used AI to make visualizations from it. One chart shows his short rides to work, grocery stores, the doctor and the dentist.
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.