A random mix from the whole library. Shuffle for a new set.
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.
Automation consultant Archit Mittal's post-mortem: his collections agent read a distributor's ageing report from a scheduled export; the night the export job silently failed (accounting machine restarted), the agent re-read the previous, perfectly formatted file and escalated firm-to-cold WhatsApp dunning messages to a long-standing buyer who had paid on time by NEFT. The buyer's 'already paid' reply with the UTR number wasn't matched by the keyword-based dispute classifier, so a colder message went out two days later — and the buyer quietly split their orders to a second distributor before anyone noticed.
Gave the AI sudo on his dev machine: it commits, pushes, checks pre-push test results, deploys as another user, checks smoke tests, and adjusts the Cloudflare pipeline and environment variables.
In 'Using the AI for Business' Ep. 1, the AI researched Etsy's best-selling Wix website templates using real sales numbers, identified the winning niche and delivery method, and planned a resellable template product line for Jackie (the build itself is Part 2).
Agency president Rich Brooks runs an AI project, the AOC Podcast Producer, trained on his own past episodes: he drops in a transcript and gets back SEO fields, five takeaways, a ranked keyword table, posts for three platforms, a blog draft in his voice and five sign-offs. Editing a post takes him 5-10 minutes instead of 2-3 hours of writing, and the Friday LinkedIn newsletter built from it has over 1,300 subscribers with no promotion.
The owner of three Korean beauty treatment shops says she used to end most days having skipped the blog again; now she hands the AI a few treatment photos and one line of treatment information and a post in her stores' tone and her own voice comes back nearly finished, which she then saves as a Naver draft. Posting frequency is visibly up, the setup handles the recurring work, and she now teaches the same sequence to her staff.
A user running the AI in manual mode, where every edit needs approval, found the agent rewriting rule files and creating a script without confirming anything. The model had read the session's permission mode once at the start, when it still showed 'default', had no way to see it change, and when challenged answered from that stale reading and guesswork instead of checking.
A freelancer lets the AI put together his monthly timesheets and send them to his clients. Once a client signs a timesheet off, the AI creates the invoice for it. The same setup records his meetings and turns them into summaries with action points and calendar deadlines.
The owner of an HVAC and plumbing company in Northern Virginia had his AI work through the company CRM and send more than 100 personal follow up emails from his work email, each one naming details from that customer's own appointment. Replies came in the same day. One turned into a $2,000 sale and a few more jobs started moving again, with replies logged back in the CRM.
A professor wrote his syllabi and prepared folders with the readings, rubrics and primary sources, then had an agent upload and organize everything on Canvas. Work that used to take him a couple of hours per class now takes about a minute, and the agent used Canvas features he did not know existed.
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.