A random mix from the whole library. Shuffle for a new set.
Jay Kranda, the Innovative Tech Pastor at Saddleback Church, has the AI check the church's Rock RMS people-management database every Monday and Thursday at 5am. It reviews all 124 scheduled jobs in the system and reports back in plain English which ones are erroring, so problems surface before Sunday instead of during it.
A corporate salesperson who cannot code keeps all his customer files in one folder that the AI reads directly. Before a meeting it pulls out up to three things to check, and after a meeting it turns his voice memo into minutes and a thank you email and files them.
Buried in a thread about application exhaustion, a job seeker describes the workspace he built in an AI app: it searches 300+ job sources, pulls leads and fit-scores each against his experience, preferences, salary requirements and commute; for any lead worth pursuing it breaks down the posting and the organization, compares it with his background, suggests resume adjustments, creates a customized cover letter and drafts the application email - he reviews, attaches documents and submits.
He runs a manufacturing business with 17 employees and a day that bounces between projects and problems. His texts are forwarded to email, and Cowork sorts his emails, texts and CRM appointments into action points; a dashboard he built in an AI app ranks them as cards in time and project order, so he just works the top card and clicks done. It is learning how long his tasks take and how far away each one sits.
He asked the AI to deploy his product site. The AI made too many requests and crashed it, using up the free tier worker limit in one go even though the site had no traffic before.
A video summary was made for others to use in their teaching. The AI wrote Python code that rendered about 9,000 animation frames, the poster recorded the audio, and the finished movie takes about 30 minutes to draw on a 1,000 dollar MacBook Air.
Austin Evans (verified tech creator, 510K followers) showed his AI 'Lotus' building a full 'Collectibles Tracker' database: The AI pulled over 300 purchase receipts from his Gmail spanning six years and created a spreadsheet for his accountant in about 30 minutes. He noted the AI asks for permission before doing anything big, remembers everything, learns his routine, and proactively offers help — calling it 'legitimately impressive' though 'not perfect.'
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.
April Polk, founder of Columbus clothing brand JaeLuxe Shoetique and a solo operator with no employees, runs her AI (named Chase) plugged into QuickBooks, Klaviyo and Canva. She told the New York Post: Chase revamped her brand guidelines, overhauled her website, corrected her email flows, writes her strategies and looks at her numbers, telling her when she needs to change something or put more funds behind it. Polk was one of 35 owners Meta invited to test the product pre-launch.
A user gave a farm of Opus agents on three AI accounts one job: make money. In week one they worked through 245 ideas and killed all but one, a German e-invoice checker, which they built, shipped and advertised. It drew 68 visitors and 6 real invoice checks and earned nothing. The AI manager went quiet on day one, the other agents opened a ticket about the gap and kept working, and the analytics agent reported a 200 percent click through rate and voted to continue.
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.