A field service worker loaded the AI with every user and service guide for the products he repairs, plus all advisories and known issues. He runs each job's action plan through it: The AI checks the parts are on the original parts list, flags advisories, and builds a step by step PDF for the repair. On a product he barely knew, its diagnosis named a different component than the plan he was given. After six hours with his engineering team he followed the agent's call and it fixed the machine.
From the same day to day list, with the exact wording shared so others can copy it: every weekday at 11 am his AI checks AMD, Intel and Dell, and only pings him if one moves 5 percent or more or there is major news, staying silent otherwise. He presents it as the model for how he uses the agent: quiet ongoing jobs with a clear trigger, not a stream of updates.
A three-person flipping operation runs on a custom app steered through AI over MCP: it identifies what is actually inside vaguely described government surplus lots by hunting service tags in the auction's spreadsheets and model numbers in its photos, values each lot against sold comps, and overlays a buy/watch/pass call with a max bid on GovDeals as they browse. It also ranks repairs by ROI, turns SD-card photos into listing pages that a human approves, and prints a pack-in sheet with QR ads for their other listings when something sells.
A man in bed wanted different music from the MacBook across the room. Apple’s Remote app could not find the Mac, then could not connect. He opened the AI on his phone, used AI mode to reach the AI running on his Mac, and asked it to control the Music app and play a different playlist. It worked within seconds.
Miguel Sosa (32K followers), a busy student-athlete, created an AI named 'CR7' (cartoon avatar). After telling it he had soccer training the next day, he asked for dinner help; the AI suggested grilled honey chicken with pasta and marinara, produced the ingredients list, and gave step-by-step cooking instructions.
A man working away in Atlantic City heard about new PHP security holes and worried about the services running at home. Over his private network link he told the AI to patch anything running PHP on his home network. Ten minutes later everything at home was patched.
Kuli Kuli founder Lisa Curtis had the AI evaluate 250 applicants for a director role against her job description while applications kept arriving, and her assistant booked everyone who cleared the screen. She ended up with more than 30 interviews booked, reread the candidates herself, cut the list roughly in half and sent 14 cancellation emails to people who had already blocked time and started preparing — several wrote back angry.
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A player with no modding knowledge told the AI what he wanted for his Big Ambitions game and set it to Opus high. Five minutes later he had a mod that worked in the game, shared on Steam Workshop as Learn on the Job.