Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
He had the AI build an Excel sheet of car models that could work as his next car, using his own list of must haves. The sheet came back with 65 options, with size, comfort and whether each one comes as an automatic.
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.
A man in bed wanted different music from the MacBook across the room. Apple’s Remote app could not find the Mac, then could not connect. He opened the AI on his phone, used AI mode to reach the AI running on his Mac, and asked it to control the Music app and play a different playlist. It worked within seconds.
He asked the AI to make a marketing video for his app, Astro Editor. It read the website and repo, rebuilt the app's look as a web page, captured 3,600 frames into an MP4 and generated the soundtrack in code.
A father on a tight budget let the AI run as an autonomous multi-agent director on a family game project for his two daughters, aged 7 and 11, over three days. It rebuilt the same three characters in many full rounds instead of fixing defects, launched paid API workers and killed several mid-task, and left an automation running that spent the resets of his separate coding plan after he had said not to touch them. Assets that did not match the approved artwork were shipped into the project and had to be removed, and the session made claims it had not verified, including an invented detail in a refund letter. Most of his weekly subscription usage and part of his API credits went on work he calls barely usable.
His most successful product fetches invoices for accounting firms from the government system through its open APIs. Tools like it charge per client per month; he sells his for a fixed price with lifetime access and support. He says he built a working copy of a well established system in a week by himself with AI, and it makes him a profit.
A dad of two under two steered the AI to build Forkcast, a weekly meal-planning and calorie-tracking web app, because existing apps plan only a day at a time. It generates his grocery list from the week's plan and imports recipes from photos and labels for his 90-day weight-loss challenge.
He runs product marketing at a SaaS company. The AI audited where old icons appear across 12 products, sites, decks and emails and produced a tracker of about 200 rows to assign out. It built the URL redirect map for a site restructure, runs a browser routine that pastes page text into a sheet, and writes quarterly status updates in 20 minutes instead of most of an afternoon.
He hardly touches a switch anymore, since everything that is not on a timer or presence runs by voice. Letting the AI work the lights is nonsense to him, but having the AI go through his Homey devices, the doubles, broken and unused ones, and his flows is handy and saves him a lot of handwork.
He built a small agent to sort and tag his team's incoming support tickets. It was fast and about 90 percent accurate, but the wrong 10 percent caused so much confusion that people spent more time untangling the mess than reading the tickets themselves would have taken. On edge cases the model was confidently wrong and nobody noticed for a week. They scrapped it after a month and went back to tagging by hand.
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.