The AI runs my training plan and adjusts it for races and weather
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.
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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.
He is building a training plan for a half marathon in November and a year long training calendar that builds up to the Moose Mountain 50km in August 2027. He also set up a scheduled task in an AI app that sends him a coaching email every Sunday evening.
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.
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.
The AI reads the reviewer's Strava trend data, which is normally shown as charts a screen reader cannot use, summarizes it in words, and correlates it with his data from the Apple Health app.
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.
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.
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.
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.
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.
X poster someone had the AI do doctor's-office admin in about 5 minutes: it emailed the doctor's office, left a voicemail, filled out new-patient paperwork, and created a calendar entry.
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.
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.
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.
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.
The AI is his gym trainer: he reports his sets and reps as he does them, and later that day Astra logs them into an Excel tracker, then uses the updated tracker to refresh an HTML app it built that shows his progress over time and his missed workouts.
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.
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.
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.
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.
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.
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.
Built a macros tracker an agent can log meals into via MCP, so he can say log my normal breakfast.
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.
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.
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.
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.
His Wellue O2 Ring only worked through the maker's app. He and the AI got it working with Web Bluetooth instead, and a release is coming soon.
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.
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.