Ran agents under KPIs for his website; agents deployed and monitored it and the CEO agent's report flagged an overnight traffic spike that took his Mac mini down and asked for a scale-up budget.
This only partly worked. Worth knowing before you try it.
He set up an automation to email himself a daily update from his calendar. Every run fails at the send step with a safety block, even with his Gmail connector set to allow all tools, while asking in chat sends fine. He rebuilt it several ways and every version stops at the same point.
This one went wrong. See what happened before you try it.
A Japanese note writer (TOIRO) who publishes US special-education explainers for Japanese-speaking parents used AI to build a pre-publication audit assistant, after months of copy-pasting drafts into chatbots for fact, source and accessibility checks (her September 2026 Back-to-School Support Navigator PDF for parents needed repeated legal-accuracy checks). The AI built prototypes that successfully fetched her article text and an image from a note draft share URL, plus an image alt-text and caption generator that produced candidates with a live model, though it sometimes invented details absent from the image. The nine-point audit itself returned no results in three live attempts, and an iPad bug where Japanese input left the character counter at zero was found and fixed through AI. Offline tests pass (43); the live audit is still unverified.
This only partly worked. Worth knowing before you try it.
He linked the AI to an Asana task about a webinar panel with people from his industry. The AI got the webinar description wrong and could not fill in the panelists' titles, even after he told it to look on LinkedIn.
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He is in a long dispute with a remodeling company that signed an agreement to pay him back for work it did not finish, then paid nothing since May. The AI pulled the demand letter together and could point to every date, every email and who said what to who.
This only partly worked. Worth knowing before you try it.
He wanted to return pants to Columbia. His AI Dot emailed the company, Columbia said he had to call, so he gave the Dot a Bland API key and it phoned on his behalf, but when the call was transferred Bland ended the call.
This only partly worked. Worth knowing before you try it.
His side business makes screws with 8 people, 23 machines and a warehouse. Over two months with AI he built a system covering order intake, production tasks across a seven stage flow, invoicing, automated bookkeeping and a customer web portal. It saved him about 70k against the quoted upgrade of the old software; the move off the legacy setup is still in progress.
This only partly worked. Worth knowing before you try it.
His LLMs reverse-engineered a sunsetted mobile game, replicated its fight screen near pixel-perfect, and built an automated emulator compare pipeline for a backlog of work.
This only partly worked. Worth knowing before you try it.
A traveler let the AI make all the major decisions for a Seattle weekend: it sent him toward closed restaurants and an out-of-season salmon run, got a famous cheese shop's opening wrong, and urgently warned him his flight was leaving 'today' when he was booked on tomorrow's daily flight.
This one went wrong. See what happened before you try it.