Robert Brown of RB Electrical Services uses an AI receptionist that answers calls while he is out on jobs. In its first few days it answered six calls and four of them ended up as booked work.
On Oct 2, 2026 a Japanese non-engineer asked the AI to run his note account for monetization; the agent picked the niche itself, then researched, drafted and self-reviewed 12 manuscripts during his 5-hour nap, reaching 42 drafts by the end of the day. It now plans topics, writes drafts, creates header images, registers the posting schedule in Google Calendar and prepares X and Threads announcements, batched a week ahead for his approval. The AI’s own safety feature stopped it from pressing the X post button; he keeps five jobs human: purpose, identity details, the final post button, personal experience and publish approval.
He maintains about ten repositories in his spare time, including work on Bootstrap, and the issue trackers grow faster than his evenings. Since October 3, 2026 a conductor AI session paces background agents that read and draft under written rules, and he gets one question at a time. On Bootstrap every open item is analyzed and a fix prepared when needed, and nothing is posted without a maintainer.
A man in Korea runs 17 AI bots for the back office of his distribution company. The bots get statements, customer emails and claim rows ready, then post each one in Slack so a person can approve or cancel it before anything goes out.
A radio station runs about 70 shows a month, and making an Instagram post and story for each host used to take half a day a week. Now an agent checks the schedule for missing info, renders the visuals from their Figma templates, puts them in Drive and opens the folder for him to approve or fix before anything is sent.
When a person fixes something one of his bots wrote, the bot writes down what it said and what the person changed it to. A nightly task reads those changes and writes the rule it thinks they point to, and in a year the bots have picked up more than 40 rules this way.
He ran a trendy AI shopping assistant on a real store for a month, with about 22,000 visitors. Revenue per visitor was $1.118 with it on and $1.112 with it off, for a net effect of about minus $120.
$120a month
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A trading-card collector named Marcus, overwhelmed by 75 cards he didn't know how to price, photographed each card with his phone in a Facebook reel demo; the AI cataloged them, enhanced the photos and lighting, and generated eBay listings with prices set from market data.
A developer new to making videos drops raw files into a folder and the AI, connected to DaVinci Resolve through an MCP server, builds complete edited YouTube videos: transcribing, picking cuts, graphics and music, using a setup it built up over his last three videos. His latest video took 57 minutes, with AI showing him take options to pick from.