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.
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.
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.
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.
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.
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 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.
This only partly worked. Worth knowing before you try it.
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.
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.
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.
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.
This one went wrong. See what happened before you try it.
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.
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).
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.
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 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.
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.
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.
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.
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.
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).
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.
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.
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.
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.
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.
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.