A random mix from the whole library. Shuffle for a new set.
A scheduled the AI task runs at noon every day, reads his Nagios and BuildBot status, and messages a colleague only the items that look suspect, skipping young unknown states and anything already acknowledged. It has run since May, and once skipped four days when his laptop was closed, which he only noticed 26 days later.
His shop sells electronics accessories into Thailand and Malaysia, and one wrong word, waterproof instead of water resistant, once cost two months of returns. Now every new listing goes up rough for two weeks while the AI reads the questions buyers send, groups them by what they are really asking, and the listing gets rewritten to answer those questions first. Buyer questions and returns both dropped.
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.
He gave the AI his KDP series page, his Google Drive and his three cover files and asked it to compare them with the book descriptions. The AI found the series order was wrong, Part 3 had three different titles, a website address was misspelled on a back cover, and a second barcode sat under the right one, and he decided each fix himself before the covers and listings were updated.
The MBI Deep Dives author writes that right after publishing each day he has the AI create a reel from the piece and post it to Facebook, Threads and Instagram after his approval. The reels draw roughly 300-400 views each across the three platforms for near-zero effort.
An LLM generated an entire compiler for his new language over 7 months of iterating and fixing, generating WASM runnable in a browser playground the LLM also built.
A creator gave the AI a screen recording and asked for a setup tutorial; the agent produced a HeyGen video presented by her own avatar. It kept her preferences in memory for follow-up video work.
Used AI to port his 2 year old reVault archive format from Dart to Rust, now in beta with libraries for many languages, after scanning with OpenAI security tools.
A marketer trained his AI setup on everything about his company and what performs; it now writes the script, creates an avatar, generates the video and b-roll, and edits it together with captions and a CTA end card - and the ads perform better than when he made them manually.
His company runs a WhatsApp agent for clinics in the UAE that books and reschedules appointments and answers questions about doctor timings, slots and treatment prices. It has handled over 100,000 conversations, costs clients about $100 per 1,000 conversations a month, and hands sensitive cases like gynecology to a human.
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.