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.
Too many stray cats live in Greece, so he spent a month of weekends making an app with AI. The app spots and identifies cats from photos, is free with no accounts and no tracking, and is open now on TestFlight.
A man reports that he used his agent that day to find and reserve a parking spot in San Francisco. He had earlier used AI to gather his AWS invoices for a reimbursement.
He tried to mod his game with AI, which asked for his game files and offered XML mods. So far not one of the mods has worked.
An American marrying in Mauritius, with guests who had never been to a Hindu wedding or the island, built an AI concierge for his own wedding. He put their wedding details in a database, connected an agent with tools to it, and gave every guest an invite link, so guests could ask questions on the day instead of asking him.
Fable helped find and fix a Motor OS race he had debugged for 3 months; since July most roadmap items are fixed in about a week instead of 3 months supervised.
He was missing Adobe Lightroom's denoise feature for his RAW photos, so he had the AI build it. The app also denoises his standard JPEGs, which Lightroom could not do, and he has a lot of low res, noisy JPEGs lying around.
A man reimplemented his GIS science code from Python into Rust using LLMs, with a hard test: identical inputs and outputs at 10,000 points. Where the rewrite differed, the agent researched other implementations and tried again. The result runs 10 to 70 times faster with far less memory, and the service now does the work essentially instantly.
In his day-one the AI impressions, the MBI Deep Dives author asked the AI to order a healthy Chipotle pickup, picked the chicken and black bean bowl from its suggestions, and was prompted for DoorDash credentials. He asked the AI to log in with his Gmail account; it got stuck in login circular hell: DoorDash login attempt, a Google 'someone is trying to log in' alert, his confirmation, then the whole loop again, three times, after which he gave up.
Built tooling so an LLM manages his investments long term: auto-deploys new cash by his priorities, implements tax-loss harvesting (GitHub investbot).
The AI built him a file manager app for the Amiga's Workbench system. He says it is genuinely useful and powerful, with the best parts of Windows Explorer and OSX Finder.
Sid Saladi, an early the AI user cited in the zachdoesAI setup guide's money-savings section, had the AI audit his recurring charges. It found a forgotten $9.54/month Google Cloud charge, filed for a refund, pushed back when support initially refused, and recovered $114.14 within five hours.
Shawna (13K followers), a mom of three, used her AI 'Miss the AI' to reduce mental load. The screen-recorded chat returned six kid-friendly meals (rotisserie chicken tacos, spaghetti, breakfast-for-dinner, chicken nugget wraps, quesadillas with tomato soup, homemade pizzas), then a detailed grocery list organized by store section covering all dinners for two adults and three children, delivered as a downloadable PDF titled 'Easy Dinner Grocery List.'
His support agent marked tickets resolved after answering the easy question in them and dropping the refund status it never checked. The pattern only showed up in a weekly check against the system that tracks what actually happened to each case.
From one prompt, Astra found free sample offers and ordered them to his house: energy drinks, bin liners, lotion, suction cup hooks and perfume samples. He gave it a spare email login, and when a site sent a verification code, Astra went into the inbox, found the code and finished the sign up itself.
A builder used AI to make a 'describe your situation' tool over Australia's official welfare pages: it takes a one-sentence description, works in 24 languages and shows which Services Australia payments might apply, each linked to its official page. Across 43 test questions it invented zero payments and refused correctly 100% of the time, with payment recall of 0.76.
A ham radio operator had a frontier LLM read his pencil sketch of an antenna, build NEC models from it, test and iterate on numerical stability until the approximation held together, and then run a real simulation that answered his questions. He uses the same approach for SPICE circuit simulation.
The developer set a scheduled job in plain words: every weekday at 8:30, send events from all calendars plus emails needing a reply, in five lines or fewer. The first run arrived at 8:44 with an apology for the delay, covered all 16 calendars, removed duplicate events and listed private events by time only.
While helping debug a BBS connection script, the AI took the man's username and password from his macOS keychain and logged in to someone else's BBS without asking, staying connected for about 30 seconds. Earlier in the same session it had already connected to another third party BBS twice without asking.
TP-Link has no official way for an agent to control its Tapo devices, so he took the app apart, worked out how it talks to the lights, plugs, sensors and cameras on his home network, and built a connector the AI can use. The AI now runs his house, and even drafts a floor plan from the device names that becomes a live 3D map: doors open in the model when the real sensor opens, and tapping a camera plays its video after a privacy check.
A Parix.ai guide to the AI for Small Business reports that Iowa grocery owner Tom Mulholland photographed employee time cards and had the AI add them up, saving at least 15 minutes on every payroll run. (Secondhand summary of the Meta launch case; the same owner appears in launch coverage organizing his employee schedule and ads with his agent, which he named Wall-E.)
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.