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.
Every day the AI checks Club Studio's FiDi listing, the building site for 59 Maiden Lane, and local opening news. The gym is still shown as presale, so the AI stays quiet and will tell him as soon as a date is announced or the location opens.
This only partly worked. Worth knowing before you try it.
He just subscribed to the AI and is setting up a Strava link. The AI gives him a weekly training plan based on his goals, his past workouts, his time, and his injuries, and it got to know him fast.
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.
The AI logs into his five patient portals, pulls every appointment into one place, and checks them against his calendar each week. The morning after a visit it explains the after visit summary in plain words and lists the follow ups he owes.
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.
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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.
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.
She has been using AI on her health insurance claims, even though she is wary of sharing health info. It found a lot of mismanaged claims that Cigna owes her money for.
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.
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.
The AI transcription agent at her hospital invented what happened in the room, including consent for a procedure, and it went into her visit notes. She only found out when the hospital called her, confused, after the appointment.
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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.
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.
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.
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She told her AI, which she calls Galatea, that she wanted to exercise more. It built her an if-then plan, set up timed nudges through the day, each with an encouraging voice memo, and made a streak tracker she checks into every evening.
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 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.
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 man's doctor's office set up an AI receptionist, and it booked his follow up appointment for tests he had done for three weeks later. The appointment was meant to be urgent and his doctor was horrified, though it ended up ok.
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When every Oura MCP server turned out unmaintained, the AI suggested a simpler design - a SQLite database with a cron sync - and built it. Now he's experimenting with injecting his sleep score into his agents' startup, so they give simpler, less demanding responses on days he's not all there, down to gentler perfume samples.
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.
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.
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.
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.
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.
Reality-TV personality Cory Wharton documents training for the NYC Marathon using his AI 'Anthony', set up as a world-class marathon coach (#metapartner video). Anthony provides his weekly mileage plan, sends check-in notifications, tracks completion in a Marathon Prep Tracker (shown progressing 8/10 to 10/10 miles), and helps strategise fundraising that reached $11,309.52 — 282% of his $4,000 goal for the Children's Heart Foundation.
A dental worker had the AI run Blender on his own computer and write Python add-ons for his design work. It built a tool that turns a shell into a based model, one for basic aligners, an automated baseplate designer, and a custom impression tray designer. A fifth add-on, for copying dentures, did not come out as well.
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.
He dictated his training to the AI: the exercises, sets, and weights. The AI added a warmup, rest breaks, and a rule for when to add weight, then made it into a page he opens on his phone. It took about 15 minutes and he installed nothing.
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.
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.
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 privacy-minded user built a tool that pipes Android Health Connect data into AI entirely locally, so the agent processes health metrics and flags anything unusual without sending personal data to cloud APIs. The recommended setup pairs it with a local model for the same reason.
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.
Lennster (1.3K followers) used his AI 'Jarvis' while rebuilding his life and staying organized. Asking for a protein meal on the spot in Jimbaran, he got recommendations for Healthy Tribes, Menega Cafe, and Fit Bowl Bali.
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.
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.
Cronometer raised its price, so he had the AI build a full clone with food search and nutrition data from the USDA database. It took about 20 minutes and he uses it instead of paying.
A person opened their medical site and launched the AI browser extension. It downloaded every medical claim for the year and built an Excel index, then logged into HealthEquity, checked the EOBs for duplicates and submitted them as FSA expenses. The submissions went through as the person typed the post.
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.
This only partly worked. Worth knowing before you try it.
A Stanford doctor gave the AI his own genome file and a 180 word prompt based on the framework his team published in 2009. In about 30 minutes for about $5, the AI matched the main findings of that team’s work, flagged genes that affect how he responds to some medicines, and warned that his file did not have enough data for disease risk scores.
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.
Dan Peguine's the AI watched his fully-booked doctor's cancellation queue and booked a same-day slot when an opening appeared. The case reached X as a quote-post by Meta executive Alexandr Wang, so the amplifier is promotional even though the underlying report is a user's own.
After UnitedHealthcare denied coverage for his out-of-network spinal surgeon, Donald Grant used Claimable's AI appeal service to build an 11-page legal and medical appeal, which he emailed to the insurer's CEO, officials and reporters. UnitedHealthcare approved both the surgeon and the procedure at the in-network rate ahead of his October 14 surgery.
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.
This only partly worked. Worth knowing before you try it.
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 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.
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.
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.
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.
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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.
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.
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.
NYT reporter Eli Tan, reviewing the AI over two weeks with connected bank accounts and email, had it call his dental insurer Anthem. The AI supplied his member ID, answered the security question, waited on hold, then rang him through to the live representative.
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 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 reviewed roughly 1,000 pages of the user's medical records spanning eight years and surfaced the relevant tests and medications for the user's AFib care team.
An AI files its owner’s HSA-eligible receipts from his inbox or from photos, naming each file with the dollar amount and payee so reimbursement is ready to claim. The naming discipline is the product: every receipt lands claim-ready.
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.
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.
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.
Autism Queensland, a disability services organization, has agents handling about 70 percent of its administrative requests, per Salesforce's customer disclosures.
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.
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.
While training on his Wattbike, he wondered if the AI Fable could crack the workout file format. It reverse engineered the format in under 10 minutes, and half an hour later there was a Python and JavaScript library plus a static viewer app.
Crawford Collins (verified, 1.1M followers), a busy new dad, personalized the AI as 'Atlas' (fox avatar) and used voice commands while caring for his infant son. Atlas generated an efficient 4-day-a-week workout plan synced to his calendar, found and ordered fragrance-free size-3 diapers (approved on screen), and when grandma was watching the baby, found a date-night sushi restaurant (Yasu Beverly Hills, Sushi Note) which he booked.
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.
Aggie Lal (verified, 1.7M followers), a mom, asked her AI 'Munchkin' to process her ~14,000 saved Instagram posts. The AI identified themes (high-protein recipes, parenting, postpartum recovery) and generated organized PDFs: 'Saved Recipes' (Protein Power Bowls, Cottage Cheese Everything, crediting original creators) and 'Parenting Tips'.
A Meta Connect-stage carousel featuring creator Nina-Marie Daniele (Nina Drama, via someone, 2.5M followers) shows her setting a goal to 'train like a pro fighter' with her AI avatar 'Drama Queen.' A Days 1-7 video diary shows a structured plan (warm-up, interval sprints, tire lifts, assault bike), track intervals with AI breathing coaching, a recommended Tempeh Grain Bowl for 40g protein, sleep-score checks, and gym work (punching bag, battle ropes). Comments were hostile to the 30-day p
Creator asked her agent 'Everest' for a 5-day PCOS-friendly meal plan at 100g protein per day, Mediterranean style. It produced the plan, a grocery list, a Sunday prep schedule, and set a Saturday 6pm calendar nudge for weekly prep.
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.
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.
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.
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.
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).
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.
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).
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.
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.
Anthony (Neutron Toys, 1.2K followers), in his 40s and taking health seriously, used AI to build a workout plan around his home gym. A screen recording shows the chat with 'Rodimus' asking how many days he trains, requesting photos of his gear, and asking about injuries.
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.
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.
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.
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.
The founder of the Gym Commitment app connected the AI to it through a custom MCP server so the AI works as the trainer inside the app. In a real test, a user described his goal and schedule, the AI asked up to 12 questions, searched 1,872 exercises, and pushed a 4 day plan to his phone in about 5 minutes, only after he approved it.
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 man set the AI to pull each week's workouts from training providers he used to pay for, since they post the sessions free but late. The AI checks his calendar for when he can train, offers him two options a day, then records what he actually did and how it felt, and uses that history to scale future sessions. A few weeks in it is saving him 20 dollars a month in subscriptions.
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.
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.
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.
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.