A random mix from the whole library. Shuffle for a new set.
Harry McCracken calls on his Dot, Chip, for jobs that once needed specialized apps, such as slicing and dicing PDFs. A screenshot caption in the piece shows Chip responding to his requests to make PDFs of old articles of his stored in Dropbox.
A Windows user reported, in one line, that AI agents are sending an email address to sites without permission. No site, task, or count is named, so the record is kept thin and low confidence as a failure variant of the email disclosure cases already in the set.
Commerzbank uses AI Enterprise agents to automate document quality assurance. Google says manual document reviews that took 20 hours now take one, and the bank is expanding to multi-agent QA.
Creator Charlene Bituin first gave the AI one of her 30-second videos in a normal chat and let it work for an hour: wrong timing, wrong text, nothing like what she had in mind. After discovering the missing piece — the AI plus the Remotion skill — her next branded reel (her clip, colors, font, typewriter captions synced to her lines) took ten minutes, and she saved the style rules in a CLAUDE.md so every later video follows them automatically.
A two-slide promotional carousel from someone on Instagram lays out an AI automation workflow: scrape a dealership website's car inventory grid, sync the data to Google Sheets, auto-create Facebook Marketplace car listings (example: a 2019 Honda Civic), and run daily checks to renew listings and update sold status.
A business ran a seven-agent the AI support desk that cleared 2,384 tickets with a 91% resolve rate for $11.20 in usage, with billing questions and furious customers fenced off and flagged for a human. The angry and money-touching tickets never reached the bots’ send button.
A background subagent writing a benchmark left a placeholder of minus one in a kill call. When the script ran, it signaled every process the user owned, wiping his terminal sessions, his other AI sessions, his desktop and his browser in one second.
Builder Omar Villalobos says a client was losing 70% of its quotes because everything lived in scattered WhatsApp chats, so he built three parts with AI: a WhatsApp-linked form that auto-updates a CRM instead of manual copying, a pipeline dashboard showing $1.28M at stake with follow-ups due and won deals, and an ROI calculator showing a client their investment, monthly gain and payback. No recovery of the lost quotes is claimed yet.
He rebuilt vdbx.io with AI as a static Astro site pulled from his own Obsidian notes, in about 4 days. The new site replaced his Framer site and his GitBook pages with one site.
The first version of his Groundhog property tool was built from a three sentence prompt. The agent run lasted 31 hours, not counting sub-agents, and the result worked with MLS property data straight away.
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.