A random mix from the whole library. Shuffle for a new set.
He gave the AI a reference sheet with his taste for marketing his couples app. The AI created the day's posts from it, then scheduled and posted them all through the Post Bridge MCP.
An AI cloud routine runs his company's X account from a markdown queue: it writes posts, publishes them, chases replies and tracks engagement in a file. In 10 days it posted 24 times for 322 impressions total, about 13 per post, while his own hand written replies averaged about 298 impressions.
Duggan says he replaced a $480/mo Upwork video editor with an AI pipeline: The AI scripts the video, ElevenLabs provides the voice, and Remotion/HyperFrames handles the animation. He says the reel itself was produced this way.
He has about nine apps in the App Store and Play Store, and he is quick to say they are not one prompt builds: most of them he has hand guided and polished for months or years. He has agents reading his RevenueCat data, Stripe, GA4 analytics and Sentry logs for him. Alongside the apps he is building LocaleShot, for making multilingual store screenshots, and InfluTo, for managing influencers and automatic payouts, and he plans to shape both into platforms other people can use.
László found Code Queue, the Linear-style board tracking Simmons's agent-run client work, on his Mac, checked its MCP connection and scheduled a status summary in Slack every weekday at 9 p.m. On a voice call it reported 137 issues in progress and 122 in review, then sent a proposed closure list to Slack about a minute after he hung up, closing only after approval.
Opus 5 pointed at his own app created a similar exploit to a known file-upload attack in 3 minutes, showing the app was vulnerable.
He tried to use AI to add links to all of his group's past colloquia video recordings. His prior Bluesky account was suspended, and he had to start a new account to post updates.
A creator documents the system his content business actually runs on: a main the AI chat ('HQ') dispatches jobs to director chats for two YouTube channels, posts on five social platforms and three SEO projects — 66 jobs and 195 chats on his board — with state in files, job cards and evidence receipts, a second AI reviewing everything before it posts, and 59 scheduled tasks doing the posting and merging. One traced job went from a radar-flagged topic to posts live on all five platforms, three hours late after Chrome dropped, with every URL logged.
Family-law trainer Stephen Smith built four working tools with AI, one conversation each: a settlement schedule that shows a client how much of an $8,000,000 award is actually spendable and when, a two-sided case chronology with exhibit links, a parenting-time calculator that counts overnights and percentages, and a case-path timeline clients get at the first meeting. The examples use training data, and he warns that the AI wrote the math, so every number must be checked before a client relies on it.
He had the AI gather his SPARQL training materials and present them on a website in a way that is easier to engage with. The site is live on the SIB Swiss GitHub pages.
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.