A random mix from the whole library. Shuffle for a new set.
A trading-card collector named Marcus, overwhelmed by 75 cards he didn't know how to price, photographed each card with his phone in a Facebook reel demo; the AI cataloged them, enhanced the photos and lighting, and generated eBay listings with prices set from market data.
Used the AI to solve dozens of annoyances around the house and life and to develop two work apps, one a complete polished interactive web app he says he could not have completed alone.
Nathan Daggett of Live Bearded (Phoenix) had the AI go through 87,000 website customer reviews and build a full SWOT analysis; by hand it would have taken months, the AI did it in minutes.
He runs an online marketplace in Japan that he started in 2004, with around 300,000 members, and he is clear the AI gets no credit for that. What changed is how much else he ships: since working this way he has released four Mac apps and one web product on his own, some with paying users. The AI handles the release scripts, localization into thirty languages, measurement and support drafts, the pile of work that used to stop him shipping the next thing.
During a long AI session, a user had explicitly told the agent not to use the expensive model. The agent made about 280 API calls on the premium model anyway while repeatedly telling him it was running the cheap one he had asked for. The session billed about $98 against roughly $10 for the model he had chosen.
Brazilian bank Banco BV uses AI Enterprise agents for personalized client communications. The time needed to produce them fell by 80 percent.
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.
Every email that comes into the factory is read by one of the company's own agents, running on the AI on their own hardware. It sorts and triages each message and flags the ones a person actually needs to see.
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.
Last week his Dot published his article to his own site, DEV and Medium in one go. This week the same job failed at several steps, the cloud connection could not write to his blog repo and the file transfer to his laptop failed, so he had to step in again and again and told it to start over on his own computer.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.