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).
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.
He used AI to generate a script that calculated the best combination of blood test packages to save money. Because every package meant a separate blood sample, they drew 4 times as much blood from him.
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.
Lulu (mom, holding her young child on camera) set up an AI avatar named 'CB' in an AI app: she shared her weight (237 lbs) and goal (180 lbs), answered questions about frequency (4-5 days/week) and location (home/mix), and got a personalized Mon-Fri strength and cardio plan. She logs 'Workout complete' and gets confirmations back.
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.
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.
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.
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.
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.
Anthony (Neutron Toys, in his 40s) chatted with his agent 'Rodimus', which asked training frequency and injury history and requested photos of his home-gym gear. From four equipment photos it generated a detailed 5-day split with specific exercises, sets, and reps; Day 1 (Chest + Triceps) was logged on 09/19/2026.
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).
A man fed a video of his golf swing into AI and worked on what it told him to fix. His average score dropped from the low 100s to the mid 80s, a gain he says he would once have paid thousands of dollars for.
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.
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.
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.
He spent 10 minutes booking a Covid vaccine appointment through the CVS AI assistant, got off work and drove to the store, and staff told him they did not have the vaccine and had not had it.
The AI compared 25 breast pump models from six brands against the user's insurance coverage, narrowing the choice to pumps that would actually be covered.
Agent ported a moderately complex workout app from web to native iOS in a couple of evenings, with a test battery.
Holdy logged the AI into his medical provider's portal and had it pull his itemized bills and question every line. It found several cases of double billing, asked for discounts, and has saved him over $4,000 so far.
The AI books the user's tennis club clinics and pays for them, keeping the user's regular sessions in place without weekly admin.
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.
His brother cannot walk, talk or use his hands after a progressive illness, and can only turn his head left and right. Using the AI to write the code, he built a set of apps his brother runs with two head mounted buttons: a phrase board, web browsing, texting for the first time, and dozens of games. The project became a nonprofit that gives the kits away.
An Italian user connected the AI over MCP to three sources of truth — Garmin for activity and recovery, Yazio for food, a FitDays scale for weight and body composition — and gave it a coach's rulebook in CLAUDE.md plus a git repository as memory, where every session ends with a commit recording decisions and rejected alternatives. Daily check-ins and a weekly review recalculate his real TDEE from actual intake and weight change, change at most one parameter at a time, sync approved workouts to his Garmin calendar, and stop everything for a doctor if red flags like chest pain or a ten-day HRV slide appear.
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.
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.
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 phoned the hospital to confirm insurance coverage for the user's X-ray and escalated past the hospital's own automated system to reach a human who could answer.
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.
MMA creator Nina Marie Daniele (verified, 5.3M followers, 48K likes) set a 30-day goal to train like a pro fighter; the AI assigned an AI coach 'Drama Queen' who built Day 1-7+ programs (warm-up, 5 interval sprints with 1-min rests, tire lifts, assault bike), recommended a 40g-protein tempeh grain bowl, and tracked a low sleep score of 45. Her final interval time beat her prior best (7:42 vs 8:48).
Grupo Marista uses AI Enterprise agents to analyze hospital claims. Analysis that took 72 hours now takes 4 hours.
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.
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.
Pavuluri Gopikrishna had the AI build a photo-based calorie tracker, then cancelled his paid calorie-tracking subscription because the agent-built one replaced it. The build-to-cancel pattern shows the AI replacing a recurring SaaS cost.
He sends his RingConn 3 wearable data to his AI email address. It sends back a dashboard and tips to improve his health.
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.
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.
LeAura Luciano messaged her agent 'mini me' while traveling, asking for a workout plan fitting her travel schedule and available equipment. The AI produced Day 1 Upper / Day 2 Lower sessions with specific exercises (goblet squats, dumbbell RDLs, cable woodchoppers, incline treadmill walking), which she performed in the hotel gym.
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.
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.