The AI built him a set of local jobs on a Mac mini, and no model runs inside them. New Todoist tasks print as small tickets within half a minute, and at 7:30 each morning a brief prints and arrives by email with the day's calendar, overdue tasks, weather for two towns, and two clients' numbers from the day before, each set against its seven day average.
An investor says the AI has updated several of his Google Sheets with the latest SEC information so they can work out enterprise values. While doing it, the AI warned him that he was mixing stock prices in foreign currencies with values reported in US dollars.
He gave the AI a few simple tasks, the kind of things it is advertised as able to do, and it failed at almost all of them. It ended up costing him much more time than it would have saved.
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Ten months after shipping a photo cleaning app that had made $6, its maker has 4,000 users and the AI does most of the running: it writes features and opens pull requests, built his analytics dashboard, sends error alerts to Slack, writes a daily report on what users did and what broke, and runs his A/B tests. He decides what to build and reviews the code.
Andrew asked the AI for the cheapest price on a new iPhone and AirPods, the best trade in value for his old phone, and whether a new model was about to drop. The AI found Amazon beat Apple by about $50 on the AirPods and a trade in worth about $200 more, and he bought on Amazon himself in the end.
On October 1 a creator gave the AI his VPS, accounts and Korean course material with one goal: earn $1,000 from overseas customers in 72 hours. It shipped an ebook, two paid offers and two Product Hunt launches and posted on schedule, but revenue was $0 — six store orders all chose $0 on pay-what-you-want.
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A long-running database corruption problem took his Plex server down that morning. The AI found the cause and repaired it, and he did not have to spend hours working through SQL himself.