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 gave the AI his CV and a job search brief, and the agent searched Naukri, LinkedIn, and Wellfound for roles posted in the last 24 hours, scored each one against his experience, and tracked the strongest in a Google Sheet. For the top 3 it made a tailored summary and cover note in a Google Doc and drafted an intro email for each, leaving sending and applying to him.
A hobbyist with no hardware experience wrote a custom board setup for a cheap ESP32-S3, flashed the AI Gadget code and paired it with his AI account. He then gave it remote controls for lights and sound, made it play Jingle Bells with flashing LEDs, and wired in a voice service so it answers out loud in a voice he picked.
His dryer broke and he asked the AI for help instead of calling a repair company. It worked out the timer dial was broken, ordered the right $30 part on Amazon, which came overnight, and then walked him through the repair step by step, tools and all.
The writer asked his dot for help with his new broadband provider. The dot did deep-dive troubleshooting, contacting the provider's support itself, and figured out a login issue he says he could not get around on his own.
Nokia built an ecosystem of specialized the AI Enterprise agents that automate troubleshooting. Issue resolution time has been cut by up to 80 percent.
A high school student sent his study guide PDF to the AI and had it build a website with a quiz style practice interface using the guide's own questions. He says it works well and beats making practice sets by hand when time is short.
After SAS cancelled and rebooked his family's Oslo flight and a human agent said the dropped prepaid meal fees couldn't be fixed, a father asked the AI to pursue the reimbursement he had never filed since July. The AI searched all his SAS emails and found the airline had already reimbursed the fees the day of the change - buried under that day's notification spam.
Author Matt Deitke fed an entire book to the AI and had it generate a chapter-by-chapter podcast website, with subagents handling chapters in parallel. The output was a finished multi-episode podcast series derived from the book.
His parents’ ten blinds ran off one dumb radio remote. With a Flipper Zero he recorded the signals, the AI spec’d an ESP32 board to send them, wrote and flashed the software, and designed a printed case; the blinds now open and close at sunrise and sunset with a small web page for overrides. Later the AI built a phone app so his parents can just ask Siri to open or close them.
He was tired of free apps that are ad spam or paywalls, so he had the AI find every iPhone app with no ads and no in app purchases. The agent verified 149 apps and built them into a directory. Deals in it are checked daily and everything is rechecked weekly.
Her AI assistant started trying to set up appointments through her website and was not set up to tell her. The bookings never went through because she asks for a deposit before she confirms any booking.
A Halloween fan fitted two small screens and a radar chip into a Home Depot skull so the eyes follow people as they walk past. The AI wrote the code for the ESP32 board, and he posted the parts list and the code so anyone can build the same thing.
Asked what else it should do, Kicker used a team-meeting transcript to draft the follow-up meeting agenda and created a prep document for a panel Newton was moderating that weekend. Both artifacts were produced proactively from existing context.
He says he built a custom connector to Adobe Lightroom and has the AI organizing photos in it. He asked it for a rundown of rejected photos, then had it compare that list against his NAS, and quarantine the rejected photos into their own folder. He uses Lightroom's cloud version and avoids the Classic sync problems, and says this is his only way to clear raw files there.
Had the AI install DuckDB and it is now running automated exports into DuckDB for his budgeting.
His coding agent pushed a commit deleting every file on main.
One user listed what his AI did over a few weeks: filed his homestead exemption back to 2024 (about a $4,000 refund on the way plus roughly $2,000 a year), switched his car insurance to Progressive (about $1,500 a year), moved him to a cheaper power plan (about $800 a year), filed 20+ class-action claims for him and his wife (about $500 expected) and applied to 15+ jobs that led to interviews. He put the total at about $9,000, with forms prepared for his approval.
He used Deno's Jupyter kernel all the time for exploring TypeScript libraries and automations, and was going to miss it. He pointed the AI at the problem and the result is cdp-kernel, Deno's Jupyter kernel extracted to run notebooks on any V8 runtime, now on GitHub.
Emerson Berlik photographed a necklace and sneakers; the AI wrote listings priced for haggling and posted them to Grailed and Facebook Marketplace.
He set the AI Tasks up to look up Berkeley housing updates on its own and match what it finds against his own tracker. He called it scary, but useful.
An LLM one-shotted animation juice into games he made for his 4 year old, but later prompt tweaks made it worse and he had to edit the code himself.
Two vendor provided Windows programs had annoyed him for over 4 years. He pointed the AI at the Windows binary and converted each one to Python running on Linux, about a day each, weird RS232 protocols and everything, and it worked.
MBI asked the AI to recommend five accommodations within a two-hour drive, factoring in past Airbnb stays; the AI reviewed his history and analyzed saved Instagram Reels to pin his preferences, then browsed like a real person. When he spotted a farmhouse and asked if he could book it directly, the AI confirmed within a minute that booking direct was 60% cheaper than Airbnb — after which he sold his Airbnb shares.
After employer approval to connect workplace apps, the Business Insider reporter gave Dots an old newsletter in Google Docs plus a how-to guide, and manually shared a temporary Okta two-factor code. The Dot produced a test newsletter draft in about five minutes that an editor called 95% good, with photos, a chart and links in the right places.
He is moving his cloud use from the US to the EU. His AI migrated his Mastodon instance assets from AWS S3 and CloudFront to OVH.
He had an idea for an NMR experiment he had been sitting on for years. The AI did the literature review, found reference data, ran spin and spectrum simulations, checked if the idea could work, and compared it with other methods, all while he ate dinner and watched TV.
Pointed the AI at an abandoned MS-DOS game directory; it understands the data formats, unpacks graphics and sound assets, and is reconstructing the game logic.
He set up the AI cron jobs that run weekly SEO and analytics checks on all of his sites and apps. He says the checks are working well and keep him consistent.
A man's Bluetooth keyboard and trackpad can only pair with one computer, and the switching tools he found needed both machines awake to work. He used AI to help build his own tool, which moves the pairings to whichever computer is active based on sleep, wake and display events, and he put it on GitHub for anyone to use.
Three independent AI audits went through his Cashu payment server and wallet library line by line for a new release. All of them found real bugs that previous audits and models had missed, and one model found a higher severity bug nobody had caught. The release fixes what they found.
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.