A random mix from the whole library. Shuffle for a new set.
An agentic harness for Sonnet 3.5 converted a medium-large vue-class-component framework to Vue 3 composition API, rescuing a personal project from software rot.
Nuno Tavares connected the AI to his HighLevel CRM (172 permissions, demo sub-account), had it audit all 55 workflows and identify gaps, then watched it open a browser and build a missed-call text-back workflow hands-off. The build landed as a draft: missed-call trigger, tag and wait step.
An HVAC company owner who runs several small businesses counted 27 active AI agents and 36 routines, 26 of them scheduled, working across his companies: pulling statements, filing invoices, updating sales and cost sheets, flagging overdue maintenance and tracking renewal dates. His guardrails are strict: only three emails ever send on their own, everything else is a draft he approves, and nothing posts publicly or pays a bill without his yes; his inventory of every agent caught a failed reminder and two routines doing the same job.
He wanted one place where people can find all the apps he is working on. The AI built the site, beardfm.app, in about 15 minutes.
An engineer at Sumasate writes that his team connected the AI Tag to GitHub, Sentry, their database, log tools and Notion, and let it do the first look at every alert in Slack. After three months, fixes finished inside alert handling went from about 2 of 38 alerts a month (5.3 percent) to about 7 of 44 (15.9 percent).
A moving/junk-removal owner says three the AI run his marketing agency work: a Google Business Profile posts bot drafting daily posts in each client's voice, a review-replies bot generating three reply options per new review, and a GoHighLevel bot logging leads, creating call-back tasks and drafting follow-ups. His morning pass runs 6:30, 6:45 and 7:00 AM approving posts, picking replies and sending follow-ups, done by 7:05 with nothing left open; the bots are logged into Gmail, Quo, Stripe, Wix, GoHighLevel and Google Business Profile.
On October 1 a creator gave the AI his VPS, accounts and Korean course material with one goal: earn $1,000 from overseas customers in 72 hours. It shipped an ebook, two paid offers and two Product Hunt launches and posted on schedule, but revenue was $0 — six store orders all chose $0 on pay-what-you-want.
Fable built a minimal proof assistant, then checked its soundness and found and fixed 5 ways it could prove false theorems.
A security researcher pointed GPT-5.6 Sol at MikroTik RouterOS 7.23.3 with a goal prompt to find a path from no login to remote code execution. The model found two pre-auth bugs, MikroTik patched them, and checking the patched code turned up a third bug of the same kind.
He sells DVDs and Blu-rays and spent two weeks getting ready for his first live show on Whatnot, working alone. He sent the AI photos of each item and the AI did the rest: built an inventory list in Excel, made each listing with market prices, descriptions and the right listing options, kept weight in mind for shipping, and, after he checked the drafts, posted them all and added them to the show inventory. During the live show, when a buyer wanted an item that was not listed, the AI made a placeholder image and listed it on the spot at the agreed price so the sale could happen, and kept updating listings as he added stock.
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.