A random mix from the whole library. Shuffle for a new set.
A father of a 5-year-old used AI to generate a fresh bedtime story every night, sometimes with audio mode reading aloud - until his daughter started asking for 'that story we listened to before' and the favorites were buried across scattered chat threads. He built a small website, FifiStory, as a persistent shelf: the stories live in one collection that can be read or listened to, and he keeps adding to it as they use it. He made it free and public, no account or paywall.
He built an enterprise SaaS for a niche industry. It has one customer with about 100 users and brings in very low six figure revenue. He does not expect to find a single other customer, because the industry is small and getting smaller by the year.
Her boiler had stopped heating the water. She sent the AI about 15 pictures step by step, followed its instructions to turn it off, switch a few handles and reset the pressure, and the boiler worked again.
Opus 5.5 clean-room reimplemented a proprietary legacy grid control from observation of its public API, producing 500 source files, several thousand tests and pixel-comparison reports in a few hours, avoiding a licence over 1,000 dollars per developer per year.
A parent of three was copying school, cram school and nursery dates from paper prints, LINE and email into Google Calendar by hand, and nearly missed a field trip lunch. He built Hanamaru: the family posts a photo of a print in Slack, the AI pulls out the dates, and it registers them on the right child's calendar, asking in the thread first when it is not sure.
Commenting on the 26 use cases post, he says he uses AI to find and apply to jobs. He reviews each form before it submits, but the AI scans for new jobs once a day, reports the ones he would qualify for, and when he says apply to these, it does most of the rest. It remembers his preferences, like salary range. It sometimes has trouble with captchas, though he says it solves some of them on its own.
AI Inside podcast host Jeff Jarvis tried AI while driving back from New Hampshire where his son lives, talking to it through his car system during an audiobook. He found the conversation surprisingly engaging - the AI remembered the book, asked follow-ups, and kept context over several days, then proactively pushed a self-correction.
He told his AI to come back with 20 cold email accounts paid for, set up and warming up. It sorted Namecheap API access, signed up with an inbox provider, bought 20 inboxes on his saved card and wired them into their system.
His home network had eight VLANs and no firewall rules between them, scoring 70 out of 100 on an audit with segmentation at 0 of 25. The AI, working through a UniFi MCP server, designed a default deny zone setup, previewed each rule, and wrote it only after he confirmed. Three audit runs took the score to 93, though one change briefly broke DNS on a live VLAN before it was rolled back.
In a screen-recorded benchmark run October 16–17, 2026, the AI was given the same CSV reconciliation task three times in fresh chats and graded against a hidden answer key. It passed all three runs at a median cost of about $0.48 per task at list price.