A random mix from the whole library. Shuffle for a new set.
One user combined three unrelated errands into a single standing job for the AI: photograph-based book pricing with eBay listings, ongoing Fandango ticket-price monitoring, and a water-filter replacement schedule — a personal resale-and-maintenance pipeline.
The same pro made a second the AI for quotes. It went through his recent Jobber quotes, found a couple that clients had not opened, and emailed those clients for him. The bot is set to check in with him once a week when it finds quotes that were sent but never opened.
He made a home configurator entirely with GPT-6 Astra and put it online for people selling new build homes. Buyers can open it and try it instead of only looking at a PDF.
He submitted 13 pull requests to projects advertising GitHub bounties and was paid for none of them. He and his agent built the detection workflow that post describes: check the maintainer's history, look for ghost bounties and merged-but-unpaid patterns before writing any code.
LLM maintains the taxonomy and index for his automatically collected browsing archive in an Obsidian vault, used for his writing.
The maintainer of GitProxy, a network security tool used in finance, refactored it from Node.js to Java with AI working as a pair. Six weeks of this workflow matched about 16 months of earlier manual effort. His first try with one-shot the AI generation produced about 1,800 lines a session of messy code that did not survive, and the talk explains why the interactive way worked.
Tomasz Woliński of Polish IT training firm StormIT built an AI skill, /szukaj-zlecen, that with one command searches seven freelancer portals, collects job listings, rates their difficulty, estimates budgets and suggests how to approach each one. Filters can restrict results to Polish sources or a chosen automation type, and a scoring system matches gigs to the user's experience level.
The AI made their product launch video from the codebase over 2 to 3 days of iteration, used for the launch at subscription cost instead of an agency.
His general contracting firm built an AI program that searches for signals, warms up emails and sends personal outreach to find work. It worked so well they had to turn it off twice: a $120,000 bid for a four season room was accepted, painter responses came back within seven minutes, and they now have subcontractors across the state after struggling to find 30 before.
He has a mobile app with crash reporting through Sentry. The AI watches it, and when a new error shows up, the AI goes to his GitHub repo, works out what went wrong, and drafts a fix before he even knows there was a problem.
Kicker completed most of an arcane insurance-broker document about Newton's new office by finding the lease, researching city websites and checking budget documents. It answered all but two of the broker's questions and asked follow-ups where it was unsure.
A heavy agent user runs AI as his daily operations layer: it surfaces GitHub activity and important notifications he would have missed, manages his calendar and travel schedule, and automatically books WeWork desks in whatever city he is in.
The developer building the signup platform for his wife's education seminars stopped answering emails, and they had no access to the code. With no money to hire another developer, he rebuilt the platform from scratch with AI as his coding partner, and it is running now.
He had always wanted a compact guide to probability distributions, what they are used for and how they relate to each other. The AI built the site he designed, with 15 core distributions and an extended map of 32, where clicking a distribution gives an interactive graph and clicking a link explains the relationship.
Had the AI deploy code to Control Plane with a supplied API key and it ran great; a later attempt at a real landing page was disappointing.
The AI made a bad MCP call and wiped the contents of a Confluence draft he had open in his browser. He lost two hours of work.
The user's the AI came up with the idea itself: it built websites and the user made the calls, closing two sales out of roughly 50 outreach attempts to local businesses.
Shipped a working Envoy Rust extension built with Fable in a one-shot, though the agent often stalls and leaves him stuck on other proxy work.
Casey Newton's Dot, Kicker, handled a radio-show invitation that conflicted with his schedule, turning it down while he worked on other things. Newton estimated Kicker did about two hours of work in an afternoon for roughly 15 minutes of his effort.
Brothers Plumbing, Heating & Electric was losing work to missed calls: abandon rates neared 30 percent and callbacks took over 10 hours. ServiceTitan's AI Virtual Agent now answers in seconds and books jobs around the company's real capacity, service zones, technician skill sets and job types; the abandon rate fell to 5 percent, more than 600 jobs have been booked by the agent, and the company attributes $1.33 million in revenue to it.
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.