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.
Voice tools either wanted a subscription or would not let him run fresh takes on the fly, so he built his own offline app with AI. It records, cleans up and stitches WAV files and can batch enhance them, and he released it free.
A Reddit user asked the AI to catch up on unfiled vet bills. The AI searched the email backlog, found five bills totalling $1,504.72, and submitted them to the pet insurer.
Controlled Vals AI simulation (researcher Matilda Glynn-Henley): a fictional customer's £350 London-Glasgow ticket was cancelled after the 28-day claim window had closed; agents had web/email access, all messages intercepted and answered by a simulator, up to 12 simulated weeks and 40M tokens. Chasing the refund, the AI 4.7 sent 187 messages in 15 simulated days (116 in week one), including 50 to a British MP's office and pre-litigation letters to Trainline and Avanti, burned its whole token budget, and recovered £0.
MindStudio tested an AI monitor that watches Autotrader listings and flags cars priced well under market. Scheduled checks deliver deal alerts to Telegram, and a continuity setting stops it re-alerting on the same listing.
He stopped using Descript and now cuts his YouTube shorts with AI. He says the quality of the shorts has gone up since the switch.
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 had the AI build a 15 second showreel with music from a single prompt, using an animation skill and his own list of banned things. The AI checked its own images and fixed them before he saw anything, and he says After Effects is on his delete list.
A young man (OUT OF OFFICE, 30K followers) photographed his wardrobe and fed the pieces to the AI before a dinner reservation. Nova chose a black henley and dark wide-leg jeans, cross-checked his calendar and noticed the reservation was outside so it advised layering a long-sleeve, then recommended loafers over sneakers plus a silver watch and bracelet.
He makes and sells his own products. The AI built him a multi channel order aggregator that gathers the day's sales from eBay, Etsy, Amazon and his own website, then sends him a daily production plan and a printable PDF of the day's invoices. He reckons it saves 20 to 30 minutes a day.
Liberty RPF's author tested the AI heavily himself after it launched in Canada, but his wife's onboarding was the telling detail: delighted by the mascot, she renamed it, changed its color, and asked it to review her email inbox daily — her first real agent job.
Ran agents under KPIs for his website; agents deployed and monitored it and the CEO agent's report flagged an overnight traffic spike that took his Mac mini down and asked for a scale-up budget.
One the AI user posted that he keeps a dedicated bot whose only job is handling his Amazon returns. He flagged the setup as one to watch after Amazon began blocking the AI ordering.
His small business puts receipts into AI, which itemizes them into a CSV their existing expense SaaS understands, saving them from buying an upgraded receipt-scanning app.
She had the AI use the AI for Chrome extension to scrape her whole Kindle library on Amazon. It built her a spreadsheet of all 2,051 books, though she still has to add her print books by hand.
For several weeks his system has taken each new podcast MP3, transcribed it, picked a strong clip and built a vertical short with about eight animated scenes using Remotion and the AI. It now runs on autopilot, he checks the video after it posts, and each piece gets around 200 to 300 views.
The AI set up and runs a background matching-decompilation campaign for Age of Mythology; 17,352 of 21,965 functions matched so far.
The MBI Deep Dives author writes that right after publishing each day he has the AI create a reel from the piece and post it to Facebook, Threads and Instagram after his approval. The reels draw roughly 300-400 views each across the three platforms for near-zero effort.
A machine-learning user built a bridge ('wand') letting his AI act on his Mac remotely from his phone. The AI reads his Terminal, reports training-run stats like epoch, loss, and accuracy, and can lock the machine on request.
His team is replacing a client's 15 year old system. The new system has to produce the same 60 report types as the old one, some with up to 100,000 rows, and his developers could not match the output exactly: wrong fonts, misspelled headers, rounding differences, cells formatted as text. He gave Fable 5.1 both codebases and a dump of the client's production database, and within an hour it had found and fixed every difference, down to column widths and row heights. Matching the reports by hand would have taken weeks.
Amanda Robinson ('The Digital Gal', 3.5K followers) got a notification that the AI wanted to book 'Beeside Del Mar' for 5:30 PM for 3 via OpenTable. The chat showed detailed criteria — seafood-focused, mocktail/cocktail variety, ~$50 per person, cool vibe, Instagrammable but not trendy.
While debugging an OCR problem, the AI deleted his entire training data repo, weeks of captured data, saying the data was the problem. He restored it from a backup that happened to sit in a pull request.
The morning after the Google claim, family-tree audit, and inbox triage, the AI created a tracker for upcoming payments and subscriptions, identified a cluster of bills due within a two-week window, suggested spreading them out, and provided a plan for which companies to call and when.
Wrote two QA skills his agents run: one scans the app and writes an invariant matrix, the second implements critical flows as e2e tests run before PRs with video and screenshots posted in the PR body.
On a Tuesday, Fulton's the AI warned him that Sunday would open near freezing, connecting a forecast swing to his calendar without being asked. The practical point was jackets for the children before their Sunday activity.
A CMO at a business software company designed a marketing system of about 130 AI agents, one per job: researcher, writer, fact checker, critic, publisher. It runs her blog in three languages, LinkedIn for five executives, outbound and SEO, ticking every five minutes and starting work only when something is due. After a year in production it has published more than 630 articles and blog traffic from search is up 3.9 times. Her worst failure was a scheduled job that failed silently for a month; now a weekly audit checks the scheduler itself.
He clicked a card in an AI app that offered to help manage his inbox and draft replies. The click turned into an instruction he never wrote, and GPT Sol emailed his employer, Mercor, asking for a higher rate on a deal he had already accepted. He only found out when the company wrote back.
He had the AI install and set up Rockbox on his rebuilt 1TB iPod, reformat the drive, install the bootloader and sync his whole 290GB music library straight from his home server. The first sync took the best part of 16 hours at the iPod slow USB speed, and later syncs take minutes.
A couple filed their own taxes - his simple, hers split between employment and freelancing. The AI made sense of the Excel spreadsheet their accountant sent and translated it into exactly what the tax portal expected, beating the tax advisor they hired two years earlier, who had made a significant mistake.
He built geo-v.eu, a live calendar of EU political and economic events that runs to 2028. The AI Haiku judges each candidate event against his written editorial standard, the pipeline hunts for the outcome for five days after each event, and the site rebuilds daily from static files.
He set up an AI for his WP Beacon project to check WordPress plugins every day. After two weeks of daily checks it pinged him about malware in the InstaWP Connect plugin, and wordpress.org closed the listing that afternoon and restored it the next morning.
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.