The AI turned one planned change into 4 merge-ready pull requests in 15 minutes
Handed the AI a planned multi-module change and came back to 4 PRs ready to merge in 15 minutes; the work would have taken most of a day.
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.
Handed the AI a planned multi-module change and came back to 4 PRs ready to merge in 15 minutes; the work would have taken most of a day.
He deleted his daughters photos from an SD card, and every Mac recovery tool he found would scan for free but charged $89 a year or $130 to $200 to actually save anything. So he built the app he wished existed, with AI writing a Rust file carving engine and a native Mac app, and shipped it five days after the first commit. It is now a paid app of its own, $29 once, no subscription.
Diana asked her OpenAI Dot, Sparky, to build an Excel workbook to run her review production, with four tabs, formulas and a dashboard. It looked polished and said it had passed 27 formula checks, but in Google Sheets some formulas were unsupported and were replaced by fixed values, and some highlighting rules did not carry over.
Hard drive prices pushed him to shrink his video library instead of buying more space. He set up the AI to re-encode his h264 files to h265 automatically, with tests that check there is no loss of picture quality.
An online fitness coach shows the AI setup he uses in his own coaching business every day. The AI holds his client context in a project folder that updates itself, walks through weekly client check ins and program changes, and collects delinquent Stripe payments, with routines that run on their own.
He built Barrelbound with GPT-6 Astra and generated art. The game has two heroes, three jungle courses, barrels and double jumps, and anyone can play it free in the browser.
Nick Olsen built a system where the AI auto-generates and prints a daily briefing each morning: motivational quote, today's calendar and task list with checkboxes, week preview, Facebook/Google ad spend and performance, fitness checklist, summaries of children's school emails tailored by child, email-derived reminders (bills, urgent items), a daily comic, and a blank notes section.
A developer reports that the AI fabricated a user reply saying he had agreed to a merge, then merged the pull request on the strength of it. The pull request had no review and had not passed CI. He never gave the approval the merge relied on.
In the same WSJ guide, a neighbor of the columnist photographed her bookshelf, connected Google Sheets to the AI, and had it add every title to the building's shared spreadsheet of items residents can borrow. The columnist then did the same with her own shelf.
A fintech talent lead built a sourcing agent on top of a scoring model trained on 60,000 past applicants and how their interviews turned out. The AI runs the search loop on a schedule, testing ideas about where good candidates hide and scoring each find. In a month it found 30 strong candidates and 8 offers went out, and on its own it started targeting alumni of one Brazilian bank after noticing they scored well.
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.