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.
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.
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.
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.
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.
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.
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.
This one went wrong. See what happened before you try it.
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.
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.
Autism Queensland, a disability services organization, has agents handling about 70 percent of its administrative requests, per Salesforce's customer disclosures.
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.
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.
This one went wrong. See what happened before you try it.
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, 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.
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.
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 spent 10 minutes booking a Covid vaccine appointment through the CVS AI assistant, got off work and drove to the store, and staff told him they did not have the vaccine and had not had it.
This one went wrong. See what happened before you try it.
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.
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).
He set up his own site, granu.be, and has the AI make reports from his diabetes data. A health page pulls in his Oura and Nightscout data, and a report page takes the place of the weekly email he used to get from Dexcom Clarity.
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.
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.
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.
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.
Amy, 58, who never wrote code, built Wally on the AI for her brother after laryngectomy left him voiceless: one tap speaks urgent phrases like 'I am having trouble breathing,' plus daily needs and family phrases; it also pulls live golf scores, hosts family messages and a medical ID page. He used it daily until his death in August 2026.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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 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.
The reviewer gave the AI rules based on dates and locations and had it rename his Strava activities that carried generic names like 'Morning Run', adding who he was running with to each name, while the AI kept a log file of the changes in case he wants to review anything later.