The AI launched our Amazon ad campaigns in about 10 minutes
The AI prepared and launched their Amazon ad campaigns in about 10 minutes. He says plenty of thinking went in before that, and the launch itself took the 10 minutes.
A random mix from the whole library. Shuffle for a new set.
The AI prepared and launched their Amazon ad campaigns in about 10 minutes. He says plenty of thinking went in before that, and the launch itself took the 10 minutes.
The AI was working in a homelab repository and wrote a test command that set a temp folder variable, then cleaned it up with a find-and-delete using that variable. An earlier step in the chain failed, so the variable was never set. Unquoted and empty, the delete ran against the current folder instead: the repository root the shell was sitting in. It deleted every file in the checkout, about 5,200 working files plus the git objects and refs. Only files the sandbox mounted read-only survived.
He runs a one person business that makes electronics for hobbyists and his customers run several of his devices at once. The AI built a stand alone program that plots their measurements together, the job he had been doing in Matlab, and worked out on its own how data from different products fits together and how to line it up in time.
Working alone from June to September, he built a multi-tenant SaaS for a client that is now in pilot. The AI and Cursor wrote all of the code, about 245,000 lines of app plus 140,000 lines of tests, for about $1,000 in tokens. Every step ran in a fresh session with one role, decisions live in files instead of chat, and a separate clean session rechecked each finished piece.
A man patched almost 10 devices the day before posting by prompting his local the AI or AI agent through a small connector that gives it access to the whole fleet only when he asks. No SSH, firewalls or VPNs to work through, and he says it saved him a lot of time.
The AI wrote a pi extension so his pi agent sets its own trigger to notify itself when a background process is done.
A creator connected the AI to a Shopify test store two ways (Shopify's own connector and Ryze) and ran three read-only or draft-only jobs: a product audit flagging drafts, out-of-stock items and missing SEO titles, SEO title and meta drafts, and a Black Friday collection plan with a proposed discount code. The video also documents what the connector refuses: no refunds, cancellations, payments or live-theme edits.
Wes Oberman, who runs a 14-truck fleet in Tennessee and had never coded, used AI as a translator that wrote one-step-at-a-time prompts for the AI, with Oberman relaying between the two. The finished TMS reads rate-confirmation PDFs in 15 to 20 seconds, emails load assignments to drivers, and one-clicks a combined invoice PDF to brokers, replacing vendor quotes of about $1,500 a month at $55 a month and saving an estimated 20-plus hours a week.
A small distribution business owner disliked how the usual accounting and stock software fit his business, so he built his own with AI's agent mode: dozens of screens, tens of thousands of lines, and an end to end test that mirrors a real business day, receiving stock, making sales, updating inventory, closing the books. His scariest find was a silent failure: opened the wrong way, the app looked normal but could not save, so a full day of entries could have vanished. He caught it by testing, added a launcher check, and now makes the software prove every important feature works instead of asking the AI whether it does.
His team has to produce a set of documents from one large main document. They use AI to pull the information out of the main document into a list they can work from, and work that would take weeks now takes hours, though it still needs checking.
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.