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