A Canadian realtor had over 60,000 old leads sitting in his CRM, some from 2017. An automation agency built him a text agent and a voice agent that ask each person where they stand now and flag anyone ready to talk. Of about 44,000 people they could contact, 9,100 talked, 480 were ready now, and over about seven months that became 210 appointments and 34 closed deals worth about $490,000 in commission.
Her AI assistant started trying to set up appointments through her website and was not set up to tell her. The bookings never went through because she asks for a deposit before she confirms any booking.
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Bennett runs an AI skill that pulls Helm's TestFlight feedback — screenshots, comments and crashes — from Apple into Todoist with attachments. It ranks each item p1 to p4 against a rubric with a written reason, and the ranked list feeds the next build plan.
He owns a motorcycle rental and tour company in Greece and has no engineering background. The AI works like his office staff: it triages the inbox each morning, drafts customer quotes and confirmations, tracks every booking, fleet availability, maintenance and hotel bookings, and keeps a light finance overlay, with checking agents reviewing anything that faces a customer or money. A database it built replaced a dozen spreadsheets. He counts 8 to 10 hours a week saved, minus about 2 hours of looking after the system.
Diana asked for a brief about her business, not businesses in general. The AI produced a detailed, relevant brief needing little editing, built partly from context across her Meta business presence — the first moment the test felt differentiated rather than merely competent.
He runs a Shopify based company alone. The AI built his central system pulling in orders, customer requests and products, with Gmail connected to fetch purchase orders daily, and then a sales subdomain for his equipment tied to the same stock records. Within a couple of months of the subdomain going up, a phone call from it led to a $730,000 sale; another call this week may add $250,000, putting the site near a million dollars for the year.
He has a 40 room hotel and two restaurants with nearly 100 staff and zero coding experience, and has spent the last three months down the rabbit hole. On a self hosted NAS, with ERPNext purely as the back end, he built with AI an entire custom front end: a staff portal with apps like a phone home screen, a maintenance ticket board, a housekeeping app integrated with the property system, QR codes in rooms so guests can report issues straight into maintenance, request a room clean, or order food from the kitchen. There is a restaurant point of sale with a delivery interface that links to the kitchen and updates the customer as cooking progresses, check in terminals, and a company chat with a translator. Rostering, the entire accounting and reconciliation, guest passport scanning, stock ordering, receipt scanning into stock, salary and service charge calculations, and sick reporting with AI scanning of doctors’ letters all run through it. Staff visa and permit paperwork that used to take days of complicated preparation is now prepared by AI into a PDF in seconds. About 140,000 lines of unique code, not counting ERPNext.
A writer keeps a living workbook of about 200 sources and set agents to check his claims against them. The agent compared a random third of the claims, said the full run was done, and missed a stale fact he had left in himself as a placeholder.
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At the same accounting firm, staff batch upload client bills and the agent reads each one, decides whether it belongs in payables, receivables, or the cash book, and posts it into AutoCount after a person reviews and amends the lines. The firm has run the setup in production for three months.
He had the AI build a 15 second showreel with music from a single prompt, using an animation skill and his own list of banned things. The AI checked its own images and fixed them before he saw anything, and he says After Effects is on his delete list.