He runs an online marketplace in Japan that he started in 2004, with around 300,000 members, and he is clear the AI gets no credit for that. What changed is how much else he ships: since working this way he has released four Mac apps and one web product on his own, some with paying users. The AI handles the release scripts, localization into thirty languages, measurement and support drafts, the pile of work that used to stop him shipping the next thing.
Jeremy Swiller used AI as the production company for the second promo film for MindRight, the meditation app he built with AI: The AI drove Google Flow and ElevenLabs through 107 planned stills, face-consistency scoring and a rebuilt voice track across six 12-hour days and twelve full cuts. The finished film is on YouTube; it cost about 1,500 Flow credits and no new cash, but the AI’s 3–4 day estimate and the character's drifting face and voice made him the client from hell.
This only partly worked. Worth knowing before you try it.
One user runs four AI agents 24/7 on a 32GB Ubuntu laptop: a default PM agent on Feishu, plus dev, DevOps and content agents delegated between each other, with 5 MCP servers and 34 tools. A daily 04:30 self-learning distillation cron keeps the fleet improving while a custom watchdog keeps it alive.
His AI rechecks all 31 providers and 89 plans on TokenPlans.dev on a schedule. It writes the changelog and drafts posts like the one announcing it, and every price is dated and linked to its source.
He set up the AI to run locally as his audio engineer. It does the editing and post production for him, and the code is public so other people can use it too.
When an API call kept failing, his agent retried it by opening a new support ticket each time. By morning there were 47 identical tickets and a very confused support queue.
This one went wrong. See what happened before you try it.
A man with no coding experience used AI to generate a VBA script in Excel. The script fixed a manual data entry gap at his work and took the risk of typos and misreads out of the job.
Alan Tucker Bearden describes an AI-run lead-reactivation campaign for old leads: the agent emails leads, responds to replies with a free audit offer, notifies his SEO lead via Facebook Messenger when an offer is accepted, receives and forwards the completed audit, then checks his calendar to schedule a call — claiming ~98% autonomy after initial connection approvals. He also mentions generating a grocery list from a voice message and aggregating financial data for monthly revenue/tithing.
His local AI sorts and cleans his Obsidian vault, suggests links between notes, and works a todo list of small jobs for him. A related eBay sniping tool from the same setup runs in simulation only, which he is open about.