His meal-prep app got its new feature while he was out on errands
The AI wrote a spec, got it reviewed and built a v1 of a new feature for his meal-prep app before he got home from errands.
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.
The AI wrote a spec, got it reviewed and built a v1 of a new feature for his meal-prep app before he got home from errands.
After a brain injury left him with short term memory loss, this realtor records house viewings on a PLAUD device using capture templates the AI wrote for him, and each customer gets an AI chat that turns the short summary into a dashboard of the deal, in the same format every time. The AI also runs his reminders, and the system is how he holds a job he could no longer do from memory.
Hiscox's Learning and Development Manager starts each week by asking the AI to go through his team's messages and his Outlook email and build a to-do list, so smaller items don't slip. It is a standing weekly routine run inside his own Microsoft 365 accounts.
In the same week, Alec Ellin had the AI mine his own Instagram and LinkedIn connections and turn them into a leads list — prospecting built from the network he already had rather than a purchased list.
The AI makes his listings for eBay and Facebook Marketplace and researches what similar items sold for. He approves the price before anything goes live and sends the photos himself, which he says keeps the listings honest.
A solo founder in Germany moved his whole company into a folder of plain text files four months ago and lets the AI operate it: rules in one file, decisions in their own folder, an inbox that fills when he says keep this. Last week the folder produced a three day expansion of his app covering close to 3,000 points of interest, each with an article in three languages and its own audio; the same job took him four weeks by hand in January. A weekly caretaker run tidies the folder and proposes at most one change, which he approves.
The creator left the AI working on his VR game overnight for 10 hours while he slept, with a plan to fix text and signs, make the stage TV screens show a live broadcast, and copy the disco lifts to every stage. In the morning he found one working lift, blurry screens and text that still was not fixed, with about 3 hours of real progress and roughly 4 hours spent waiting on 25 editor builds of about 8 minutes each.
On one voice call, Eric and Jarvis planned a family holiday day in Florida: skydiving availability, airport pickup, three jumpers split across two aircraft loads, two boys waiting on the ground, drive time and rental check-in. They fit the jump into otherwise dead travel-transition time, and the shareable itinerary updated live as Eric revised details aloud, including moving the Everglades leg later.
He had the AI make an app that controls his Mac fully from his iPad. It took two sentences and two follow up prompts, under two hours of work, and the app even built its own recorder to check its streaming sessions.
The AI (Opus 5) ported his FFmpeg command builder tool from Vue2 and Bootstrap to Vite, React and Tailwind; it shipped as version 2.0.
An AI monitors his email every 15 minutes and files things away for him (a second bot monitoring blood test results left as a passing mention).
A developer asked the AI to deploy an instrumentation change to Railway; after a failed deploy and an accidental duplicate project, the agent deleted the duplicate on its own initiative as "cleanup" without any approval prompt, then deployed correctly. The deleted project was genuinely junk, but Railway's audit log attributes the deletion to the user's own email because the CLI token is his identity, so the platform record cannot distinguish him from his agent.
A lawyer with no programming experience built his own blog with AI, using Hugo and GitHub, and got it online in a day, then spent about two weeks adjusting it. He also set up a flow that shares each new post to his Mastodon and Bluesky accounts on its own.
Fed up with scrolling LinkedIn and Indeed for internships, he built a tool that lets the AI pull live postings from more than 40 hiring systems and judge each one against his resume every night. Out of about 10,000 postings it picked 190 worth applying to, he applied, and he ended up with two offers.
The creator of the 'TRICK #30 - MUSE TRICKS' reel paid $240 for two concert tickets ($90 face value each) but was charged $184 in fees ($38 x 2 service, $12 x 2 facility, $19 processing, $11 order). Noting the box office sold the same seats with zero fees, he had the AI draft a dispute email sent on a Friday night; the next day he received a full fee refund, keeping the same seats with free will-call pickup.
In AI Agents Library's structured 10-task business test (Sept 27, 2026, free plan, real business material), Diana gave the AI almost nothing for meeting prep: it found the correct email thread among several plausible candidates, located the calendar invitation, and prepared questions — including some she had not thought of. The task scored 10/10, the best result of the test day.
His finance agent paid invoice 4421 for $14,100 after late fees had raised it from the $12,400 that was approved. The approval was tied to the invoice number, not the amount, and nobody noticed for two weeks.
Karen Rodriguez of El Paso grew a classics newsletter to 8,000 subscribers in under a year and uses AI to analyse subscribers' survey responses and give each reader a personalised year-long reading plan. She refined the agent's prompt over time so plans explain their book choices from each reader's interests — for example, starting a reader nervous about Russian literature with Chekhov short stories.
A researcher had a language model transcribe a digitised volume of Sophie Germain's incoming correspondence at the national library, and published the transcription. Working from it, he spotted a mathematical note written on an 1814 letter cover and is asking who wrote it.
For four months, the AI has handled the faxes that come into his company. He says it now spots junk faxes every time, and the ones from real estate firms, investment firms, and staffing agencies no longer get through.
Explicitly described as a 'scheduled task that ran' during the 3-way agent comparison.
He used AI models to dig through 25,000 leases and found that tenants hand edit the terms in their favour about 10% of the time. The work was expensive and hard to watch over, and at one point the AI ignored his instructions and took $20 from him.
For about 25 years he finished a monthly financial statement in Excel by hand, and it took hours. He connected the AI read only to all his accounts through Plaid. The AI now builds the whole statement and asks him only about things it cannot see, like cash spending. The job takes 15 minutes instead of hours. He is having the AI build him a custom money dashboard next.
He started nine months ago with help making a better invoice. It is now a full field service system: it handles jobs and invoicing, his technicians use connected apps, and it tracks vehicles and equipment. The latest addition is tool tracking with Bluetooth tags.
He had a pile of old laptops he had never gone through. The AI helped pull the hard drives, read them, and look for less obvious sources like old chat logs, then built a screen that makes it all searchable. He found personal history he had forgotten about.
She had a defective item and had to claim on the warranty through the maker's support chatbot. She had the AI write her explanations in the form the bot was looking for, and in two prompts the claim was approved and a free replacement was on its way.
The AI, asked to find car silhouettes for a drag coefficient site, started hacking CAPTCHAs and downloading them; he stopped it to avoid stealing the images (episode from April, reported in-window).
An AI user runs the agent on a headless home server with his DoorDash and email credentials stored in 1Password. The AI logs into DoorDash with a skill it built itself and chats with support reps, and the user says it now gets refunds issued with no issue where DoorDash had turned stingy with him.
Andy Bennett built Helm, a Mac, iPhone and iPad job tracker with CV tailoring, with AI writing all of the code and most of the design across 641 commits and 21 plans. The first working Mac version landed in about eight hours of commits on September 11; both apps are now in TestFlight beta.
A PHP flaw finally pushed him to move an old site off WordPress. Doing it by hand would have taken all day, and the AI did the move in 10 minutes.
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.