A random mix from the whole library. Shuffle for a new set.
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 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.
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.
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.
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.
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.
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.
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.
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.
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.