Real things everyday people got it to do, and how to try them yourself.
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His wife runs a travel agency in Mexico and the work had outgrown spreadsheets. He built her a full CRM and ERP with clients, quotes, itineraries, payment plans and group trips, plus an integrated AI assistant, using FastAPI and SQLite, and shared the code on GitHub.
Commenting on the 26 use cases post, he says his AI books all his haircuts: he just says book a haircut on a day at a time, and the email confirmation comes in. He does the same for movie tickets, without going through the booking process himself.
After hitting his weekly limit, a user bought $200 of prepaid extra usage credits because the tool itself told him to, to finish his work. The limit message kept appearing at every step anyway, while the balance drained to zero. A dynamic multi-agent workflow ran about 1 hour 50 minutes and burned through the balance; the AI reported that roughly 60 percent of its verification agents never executed, and the partial results that did come back were largely discarded. The $200 bought an incomplete verification.
She was using AI to archive legislative material when it flagged a serious vulnerability in a state legislature's website. She had to stop and report it.
In February he told the AI what road he was taking and when he was setting off. The AI picked lunch places within a 20 minute detour that he would reach at lunchtime, 10 of them spread over 50 miles, with an import into Google Maps.
His deal dashboard watches prices every day on the specific things he buys: shoes, pantry staples, gift cards and streaming deals. It emails him only when a deal triggers and stays silent the rest of the time.
The same pro made a second the AI for quotes. It went through his recent Jobber quotes, found a couple that clients had not opened, and emailed those clients for him. The bot is set to check in with him once a week when it finds quotes that were sent but never opened.
In one day the AI accidentally deleted one of his GitHub repos, which he says was partly his own fault for not explaining himself better. The same day it also failed to spot the cause of air bubbles on his film negatives, which he found himself by searching the web.
A five-person Zendesk team built the Custom Agent Builder with AI and the AI Agent SDK, going from proof of concept to early access in four months. Customers ran one million Custom Agent executions in the first seven weeks, reporting up to 10 percent higher automated resolution and up to 80 percent lower human handle times.
Ahead of a Nov 14 Disney cruise, he credits the AI with tracking the staggered booking milestones — excursions opening in August, online check-in, and a late-night Royal Gathering character meetup — so none of the windows are missed.
His third party payment software has a poor UI and its routing rules came as an unfriendly XML dump. In about 15 minutes with AI he got a Python script that turns the export into a single HTML page where he can scroll the routes and click into each node for its priorities and matching criteria.
WSJ columnist Nicole Nguyen asked Dots to cancel a handful of subscriptions but specified that she wanted to press the unsubscribe button herself. Dots loaded the correct account pages, pinged her when each was ready, and finished the job after her click.
Asked to compare the AI and the AI with citations in a saved Google Doc, Spark produced the table and doc but contradicted its own pricing figures and cited an electronics retailer's blog for software pricing. Challenged, it fixed the USD prices but the India rupee figures stayed unverifiable.
He built an app with AI that reads his solar inverter and batteries, forecasts tomorrow's solar generation and household use, and emails him a report. It sets the battery charge level for the overnight cheap tariff based on the forecast.
His agent runs once a week: it finds companies on Google Maps, finds a real person's contact details on the web, and drafts a personal email for each one, which he approves before it sends. Across 200 companies it produced 20 interviews in four weeks, and he spends about an hour a day on the replies.
A refund of several hundred dollars was still pending, so Cramatata casually asked the AI to call Apple customer service and ask about its progress. The AI made the call, spoke with a live representative who checked the order and its progress item by item, and only transferred the call to her when identity verification was required.
His agents receive continuous video and audio, notice an unrecognized person and take action, and commented on the sunrise while he slept.
She downloaded the AI a week after her dad died. Between probate, the service and celebration of life, and paperwork across banks, credit cards and bills, she says she would be dropping things without help. The AI keeps track of everything in the air, and makes her a three minute audio briefing every morning and night covering what she has done, what is ahead the next day, and one small way to do better. She listens while brushing her teeth and says she sleeps better.
Mete Ünal's Dot, Satori, proactively noticed an unused discount code on one of his orders, emailed the company on his behalf and secured a partial refund. His only involvement was replying 'Sure!' when the Dot asked to reach out.
He ported BlockOut, the 1989 3D Tetris, to the Nintendo 3DS with AI, with stereoscopic 3D, sound, touch menus and SD saves. He did two more games the same way, and all of them are open source under the GPL.
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.