A random mix from the whole library. Shuffle for a new set.
He asked the AI to cancel his Adobe plan. The AI got through Adobe support, got the roughly $100 early cancellation fee waived, cleared the balance he owed, and finished without a new card being added.
He sends audio messages to his AI. It transcribes them locally on the graphics card in his home server, so his voice notes become text without leaving the house.
A non-developer store owner ran Google's PageSpeed tests, printed the expanded results to PDF for both mobile and desktop, and had the AI analyze every red issue and hand back prioritized fixes as cleaned-up code to paste in. His speed score rose 10-15 points and the speed index dropped from 3.2 seconds to 1.2.
A developer told the AI to repair his stock-options analysis software working only on copies; when the mirror-rebuild tool failed, the agent wrote its own Python cleanup script that treated 614 Windows directory junctions inside the temp mirror as ordinary folders and deleted 48,218 live files in 103 seconds. The sweep also emptied the Git object store, leaving an index that listed 7,221 paths whose contents were unrecoverable.
Plumbing company owner Jon O'Neill listed the agent workflows live in his shop: email triage, job booking by text and email, truck and warehouse restocking, fleet maintenance reminders, scanning sold-job notes for missed opportunities, drafting quotes from tech notes and photos, job routing, review requests and missed-call texting. He says booking saves the most time, refuses voice agents, and keeps hard limits: quotes over $5,000, price negotiation and restock orders over $1,000 always go to a human.
His company cuts and sews shirts in America from materials bought from many vendors, shared across 10 to 20 shirt styles. Working out the true cost of a finished shirt by hand was a mess. Now an AI automation does the full calculation in about 10 minutes, exact, and publishes the cost to Shopify.
Cyrus and the AI system routes Telegram and Linear tasks to repos by label and opens PRs for review; he is more hands off across multiple projects.
He has about nine apps in the App Store and Play Store, and he is quick to say they are not one prompt builds: most of them he has hand guided and polished for months or years. He has agents reading his RevenueCat data, Stripe, GA4 analytics and Sentry logs for him. Alongside the apps he is building LocaleShot, for making multilingual store screenshots, and InfluTo, for managing influencers and automatic payouts, and he plans to shape both into platforms other people can use.
In Futurepedia's early-access test, the Dot coordinated a Dots launch video: it requested three intro versions in an AI app, selected one, sent it to an AI motion-graphics skill and started a thumbnail in another chat. The creator still revised the thumbnail and said his skills needed tuning.
The AI spent a couple of hours going through about 250 of her past newsletters and repurposing them. Her blog is now live with that material.
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.