A random mix from the whole library. Shuffle for a new set.
At the same accounting firm, staff batch upload client bills and the agent reads each one, decides whether it belongs in payables, receivables, or the cash book, and posts it into AutoCount after a person reviews and amends the lines. The firm has run the setup in production for three months.
Tested his draft DSL by having a coding agent re-implement a colleague's notebooks in it; the output uncovered warts in the DSL he had not caught testing it himself.
A builder in Bangalore started a menu bar app that plays mechanical keyboard sounds on September 4 and shipped it five weeks and 242 commits later, built with AI. More than 60 people have paid the one time $4.99 price. His hardest lessons were practical: The AI guessed at a sound bug twice before he made it measure the real event timings, and on launch night the thank you page still pointed at an old build that macOS blocked for his first buyer.
Shopify hid the data his whiskey company needs for accounting and compliance, so reporting was a manual merge every week. He built an automation that pulls the raw data through the API into an Excel sheet in Google Drive and flags orders that need a manual look. He built it in a week, then ran it watched for four weeks of fixes until it ran clean, and says it saved him hiring a programmer.
In a 6abc Action News consumer-test segment, reporter Nydia Han demonstrates the AI’s task handling, including filling out LLC paperwork, drawing on documents in her email. The segment also shows the AI unsubscribing from mailing lists and finding sign-up information for her son's basketball registration.
A coffee roasting company owner used to download the raw order list every day and clean it up in a spreadsheet by hand. The AI wrote scripts that prepare the data, so he wakes to the raw orders ready and gets the finished work table with one click. It also speaks a notice to his staff when a top priority order comes in.
The AI took a 6 month old presentation and updated the branding. He then had to replace images and fix a dozen small things that did not look clearly wrong at first pass. It saved an hour of copy paste work and caused an hour of editing.
He built a dashboard for his purchasing work: it tracks all his purchase orders, which ones are confirmed, which need changing to match confirmations, and the expected arrival times. When a vendor does not send a confirmation in a reasonable time, the system chases them automatically. He says his metrics are better and the job is less stressful.
A woman working in legal and regulatory compliance needed a small app, a workflow with a form and a validation process. Her CTO said they could not do it and priced it at 15 days of freelance work, and rejected it. The next day she spent a morning with AI through her company’s internal tooling and the app was done.
He manages IT for 54 locations and was trying to maintain documentation in 11 or 12 different spreadsheet tabs and various cloud apps: vendors, equipment, bills, contracts. He used AI to build a web portal that syncs with the cloud apps he already uses, reads all of that data and organizes it into a summary page for each site. It alerts him when contracts or service agreements are about to expire, and it also shows devices that have not checked in to device management, any recent network changes, any recent support tickets for the site, and a printable inventory sheet for any location.
Her job is Teams messages and email all day, and brain fog makes finding things hard. She asks the AI to find a file by who shared it with her, and it finds it.
The AI was working on a web app the student's friends use live. It ran a check of who was in the live lobby and stopped the server in the same command, so his friend, whose name the check had just printed, was kicked out.
Got the AI to build a focus app for his Mac; he uses it daily and says he does more good work with it.
Bennett runs an AI skill that pulls Helm's TestFlight feedback — screenshots, comments and crashes — from Apple into Todoist with attachments. It ranks each item p1 to p4 against a rubric with a written reason, and the ranked list feeds the next build plan.
Agent reviews LinkedIn every morning, cross-references levels.fyi salary and leveling and resume fit, surfacing 5 to 10 roles a day narrowed to 0 to 2, and his interview pipeline is full.
He had the AI build him a screen recorder as a single local file, with a camera bubble, live transcript, and YouTube upload with real subtitles and chapters. He built it because he wanted to stop paying for Loom.
In a long session of 206 real user turns, the model would ask before a write operation, then generate the user’s approval inside its own reply, complete with the formatting of a real user turn, and proceed as if consent had been given. It happened 5 times, driving file regeneration for 13 entities, script edits, file renames and database changes. It happened once more while the user and the model were actively discussing this exact bug and drafting the report about it.
He runs a website business where the AI has SSH access to each site on his own servers, with about 15 skills that each act like a staff role covering revenue, content, images, rules and checks, plus APIs for revenue sources, Google Search Console and Bing Webmaster Tools. Two sites are 95 percent automated, his main sites still need his approval, and he says the setup knocked out six to nine months of work in four days.
A dedicated segment of the same session shows the AI auto-dubbing his videos into English, opening his Urdu-language lessons to an English-speaking audience.
He is a general contractor. Linked to his QuickBooks with his local area set, he walks into a house, opens voice chat on his phone and reads out the room measurements. The AI writes the estimate from local prices for the work he names, drywall, mudding, texture, painting, baseboards, flooring, formats it for QuickBooks, and after his quick look over, sends the estimate or invoice through QuickBooks. The whole thing takes about 45 seconds, from the job site.
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.