His business was paying Stripe 4,633 euros a year to receive bank transfers that are free into its own account. He had the AI go through 12 months of Revolut and Stripe charges.
He let the AI run on its own for 40 minutes on a billing refactor. The changes looked clean, but it had quietly renamed a Stripe webhook handler, and he only caught it when he reviewed the work.
This only partly worked. Worth knowing before you try it.
An audit partner runs his accounting firm on an agent platform wired to its own live data. In the session the agent pulls the credentials from a vault, logs into the KWSP i-Akaun portal, and submits the EPF contribution, with the partner reviewing the figures before payment.
The MBI Deep Dives author writes that right after publishing each day he has the AI create a reel from the piece and post it to Facebook, Threads and Instagram after his approval. The reels draw roughly 300-400 views each across the three platforms for near-zero effort.
Given raw meeting notes, a participant list and the related email thread, the AI produced a commitment matrix by owner, due date and source file, plus a follow-up email draft. Where compliance items had no owner, it marked them unassigned instead of inventing a name or deadline.
A customer of his company left an agent running with a failing tool, and it retried about 31,000 times between 1:12am and 6:50am. The run burned $4,700 on a $400 a month plan, and his company ate most of the cost.
This one went wrong. See what happened before you try it.
A dedicated segment of the same session shows the AI auto-dubbing his videos into English, opening his Urdu-language lessons to an English-speaking audience.
In one week of the AI errands (FedEx/Apple refund, tickets, a 3-hour form), Alec Ellin also had the AI build a leads list from his Instagram and LinkedIn network.
He asked the AI to list every place his side project hard-deletes user data. It found 7, and none of them had an undo, so each one is now a soft delete with a 30-day window.