A random mix from the whole library. Shuffle for a new set.
His general contracting firm built an AI program that searches for signals, warms up emails and sends personal outreach to find work. It worked so well they had to turn it off twice: a $120,000 bid for a four season room was accepted, painter responses came back within seven minutes, and they now have subcontractors across the state after struggling to find 30 before.
His 5th grade class studied Maricarmen and her eviction, a real case, and the pupils made work about it. He gave Notebook the AI directions to redo the class video so all of their work can be seen, and the video is posted with a PDF of the work on his class blog.
Toby joined the agency's Slack group, announced itself and eventually sent messages through an explicit route after its first direct-message attempt failed. When a colleague asked for a PDF summary at about 4:24 p.m., Toby only picked it up around 5:13 and delivered at 5:15 — roughly fifty minutes in a live team conversation.
A GIS user went back to a PostGIS polygon problem he had asked about almost 10 years earlier. Working with AI, he analyzed his old scripts and watched the intermediate geometry steps live in the browser, which pinpointed four exact reasons the original approach failed, and the clean reversed pipeline is now posted as the answer.
A print-on-demand seller wired the AI through Playground to Etsy and Printify so research, SEO, design and listing were automated; her dashboard screenshot shows the new listing sold within 3 days for $42.
Alongside his homemade TMS, Wes Oberman built a settlement payroll program that calculates every driver's pay automatically. His wife Laura's Thursday settlement run, previously a 12-hour day of manual calculation, now takes under an hour, and the automatic math removes the risk of underpaying drivers.
Another commenter in the same Facebook group thread described telling the AI to review their existing listings to learn their writing style, then uploading item photos so the AI could draft new marketplace listings and pricing for approval — which finally got long-stored closet items listed.
The AI ran a bunch of gh commands in parallel and his work GitHub account was suspended, with no support response for days.
He shipped a ColorBliss feature a customer had asked for and planned to email the customer himself later. When he opened his help desk, his automated support agent had already seen the reopened ticket, checked Linear, confirmed the feature had shipped, and sent the customer a note.
A solo reseller's the AI-built spreadsheet app is his back office: he dumps in a batch of receipts and it enters them, creates a folder for each new item, and sorts the item's photos and receipts into it alongside measurement files. The same app recommends prices, writes his listings and does resale research, which is the part he says makes the $20 a month worth it.
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.