A random mix from the whole library. Shuffle for a new set.
His AI rechecks all 31 providers and 89 plans on TokenPlans.dev on a schedule. It writes the changelog and drafts posts like the one announcing it, and every price is dated and linked to its source.
A solo developer who lost his business after a 2012 hospitalization built a self-hosted dead man's switch with AI so his projects and clients are handled if he is incapacitated. It has run for weeks, ships with 42 unit tests, and clients already cite it as a trust feature.
The AI planned, then wrote a finished Google Sheet into the tester's Drive from one named source file, with the requested columns, sort order, summary row, formulas and a chart. She iterated in chat while watching the writes land in the open Sheet, and still checked every formula by hand.
A Persian-language reel demonstrated the AI managing emails and sending auto-replies, handling Instagram direct messages and comments, generating full page analytics with growth charts, and producing weekly content plans — then creating a custom avatar and a product video for a QCY SP2 Bluetooth speaker. It connected to Gmail and Instagram.
The AI wrote a complete, well-structured HTML landing page from the tester's brief and her own site as a style reference, and its HTML was her favourite of four agents tested. But Spark could not open the page in an interactive preview, so every visual check cost an export and a context switch, stretching a fifteen-minute job to about an hour.
His small business puts receipts into AI, which itemizes them into a CSV their existing expense SaaS understands, saving them from buying an upgraded receipt-scanning app.
A man at a company that paid $300,000 a year for Looker for ten years says one engineer, working part time for a couple of months with AI, built a home grown replacement for their dashboards. The core idea checked out in a couple of weeks, and the company told Looker it will not renew.
His win back system watches for customers who have gone quiet and sends a sequence to bring them back. Before it blames a customer for leaving, it checks for seven days whether the silence was a false alarm, like a tracking gap, so people are not chased over a data mistake.
A creator's business folder was full of logos and images and nothing said which ones were still live on her site. Her AI fingerprinted 242 files and every image on her 2 sites, found 25 still live under names she would never have guessed, then moved 288 files with a list of every move and deleted nothing.
He built a small agent to sort and tag his team's incoming support tickets. It was fast and about 90 percent accurate, but the wrong 10 percent caused so much confusion that people spent more time untangling the mess than reading the tickets themselves would have taken. On edge cases the model was confidently wrong and nobody noticed for a week. They scrapped it after a month and went back to tagging by hand.
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.