A random mix from the whole library. Shuffle for a new set.
Angel Almenarez Jr. posted screenshots of an AI-generated workout tracking page built by the AI: 'DAY 1 UPPER PUSH' with exercises (Chest Press 4x8-10 Machine 120 LB, Incline Press 3x10-12 Dumbbell) plus an ACTIVE TRAINING BLOCK (Week 1, Week of Sep 21, BUILD phase) with a 4-day split (Upper Push, Lower Quads, Upper Pull, Posterior Chain) for logging weights and charting progress.
Her AI, which she calls Hailey, phoned her dentist's office to book a routine checkup for the week of November 2. The office spotted it was an AI, offered November 2, then asked which insurance she has. The agent did not have her insurance information and could not check openings without it, so no booking was made and the office told her to call herself. She shared the full call transcript.
He said he built his setup with AI and local models. He told the agent to use a GitHub tool to download his Garmin data automatically and store it in a local SQLite database, and the data includes sleep and HRV, not just workouts.
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.
He sends his RingConn 3 wearable data to his AI email address. It sends back a dashboard and tips to improve his health.
She kept forgetting to log her own progress, and failing. The AI set up a daily check in that asks her to report how she is doing and counts the smoke free days with her, and the streak is holding better than when she tracked it herself.
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.
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.
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.
Grupo Marista uses AI Enterprise agents to analyze hospital claims. Analysis that took 72 hours now takes 4 hours.
The AI searched for the earliest available appointment with a specialty physician and found one in about a minute of searching.
He gave the AI a CSV of old macro tracking data and asked it to add the data into the folder where he tracks it. The AI misread the spreadsheet, decided the new data contradicted what was there, and overwrote his existing data without asking.
Since the AI got access to his Strava through an MCP, it has become his running coach. He says his progress is clear and he may reach 150 km of running in one week, but the sessions are so strict he feels like he is doing maths.
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.
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.
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.
He built a personal fitness display, a website to manage his training plan, and an MCP link that lets the AI control it all. The AI adjusts the plan around his races and the weather.
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.
Agent ported a moderately complex workout app from web to native iOS in a couple of evenings, with a test battery.
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.
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.