The AI drafts his app's blog daily and only pings him when a draft needs him
The AI writes daily blog post drafts for his app and checks draft approval status every 2 hours, pinging only when something changes.
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The AI writes daily blog post drafts for his app and checks draft approval status every 2 hours, pinging only when something changes.
Vibe coding a real product, a 3D game on the App Store with 20 species and zero revenue.
A digital-health CEO reports his businesses have no full-time developers, DevOps, designers, analysts or product manager: scheduled AI agent shifts handle deploys, an agent-built CRM, per-business-line email sorting, meeting scheduling, technical support and publishing news four times a day. The work runs on three $200 AI subscriptions — $600 a month against roughly $38,500 a month at US median pay for the replaced roles.
A real-estate agent shows the follow-up system he runs on his own CRM: new leads are added to Follow Up Boss by pasting a text screenshot into AI, a lead-scoring skill grades each one A, B or C, and a daily 7 AM sweep of the CRM hands him his hot leads with personalized follow-up texts and emails already drafted in his voice. The video walks through the connector, the skill install and automating the daily drafts.
He asked the AI to make a technical diagram with gpt-image-1. After ten tries the version that shipped looked clean but had quietly dropped the exact claim the diagram was meant to show, and he only caught it after publishing.
He asked his AI to edit an entire video and it did the work, from picking the takes to lowering the music in the quiet parts. The video is the third in his series about building his toolstack with an agent.
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.
The operator of a small Japanese company has used AI daily for three months across quote tooling, documents, internal pages and accounting help, and never edits a file himself: after every failure he tells the agent in chat to remember the lesson, and the agent writes it into its own handover note and memory (now 250+ memory entries and a note past 1,000 lines). The scars are specific: work built under the wrong account, duplicate tool instances breaking half the controls, and aggregated data lost to a 30-day chat retention setting.
Someone cold-pitched ~50 local businesses with websites the AI built; 2 bought. The website-flipping idea came from the AI itself; he just made the calls.
A documented community run asked the AI Computer to check a 280,000-line Python codebase; the roughly 40-minute run consumed 15,000 credits, climbed to 21,000, and burned a further 2,000 credits pushing the result to GitHub. The single task cost more than double the standard monthly credit allocation, with no published per-task price list to predict 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.