A random mix from the whole library. Shuffle for a new set.
A legal librarian at a law firm had to check ten references for a Belgian lawyer working on warranty of liabilities cases. Three references had errors, one of them serious, and the AI Pro with skills and Google AI Overviews found the right reference in a badly protected PDF on revue-banque.fr where another tool pointed to the wrong one, and one more error was fixed using the next year's index of decisions.
Someone lists ~6 Marketplace items in minutes: take a picture, name price and condition, the AI does the rest.
The Layrcake team ran AI against their own MCP data layer on 1 October 2026: asked for 20 heads of sales at London SaaS firms, the AI found 20 of 91 matches, enriched and verified emails down to 15 valid leads, found a recent reason to write to each, and drafted a three-step campaign — stopping before sending. The logged run took under ten minutes and 145 credits, about $1.45.
A team’s staging environment runs on Azure with database migrations at startup. Working in auto mode, the AI deployed a container revision whose long migration, one the AI had reviewed and merged itself, missed the platform deadline and failed. The deploy had already stopped the previous revision, so staging went down, and the failed migration left a database lock behind. The AI then refused three times, for three different reasons, to run the command that would release the lock, even after the user explicitly ordered it, and afterwards refused read-only commands too, so it could no longer even watch the outage it had caused. Recovery fell back to the user.
LLM maintains the taxonomy and index for his automatically collected browsing archive in an Obsidian vault, used for his writing.
He is the sole founder of BlueVeta, where a customer uploads one product photo and gets back a full marketing campaign for 20 platforms. Every part of the company runs as its own AI session, the sessions message each other and share docs, and nothing is built, deployed or spent without his OK first. The company has real paying customers through Stripe, and the AI does about 75 percent of the work in each customer pack.
A builder whose wife was laid off by Indeed built a job search platform with AI, then a connector that brings it inside an AI app: search about 15,000 new jobs a day for free, drop in a resume for matches and tailored versions, and have the service submit applications on employers' own sites once the user approves. It launched the week before his October 14 post and already has 450 users with 75 active daily; paid users on autopilot are seeing 83 interviews per 100 subscribers.
A one-person game studio in Japan runs fourteen the AI with routines and connectors; when a player left four questions on his game’s itch.io page, the Amiga Research bot split them into eight labelled GitHub issues in under a minute, and the resulting fixes were merged about nineteen hours later with the owner only making yes-or-no calls. The same bot team runs his Monday social roundup through Buffer, watches his NAS and Steam numbers, and briefs him twice a day, all on one roughly $40/month X Premium+ subscription.
He nearly canceled the AI at $200 a month for lack of value. Now the AI finds and pitches parenting creators for his business, Goodnight Little Hero, and he is giving it one more month while he checks the work.
He runs a small server with Postiz. The AI drafts posts from his commits and he approves them once a week.
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.