A random mix from the whole library. Shuffle for a new set.
A user had the AI apply TurboQuant skills to optimise a Qwen3.5-9B model running locally via MLX on Apple Silicon. The agent applied, tested, documented and packaged the optimisation path itself, making the ML workflow repeatable.
His agents communicated by email and flooded him with 500 or more unread emails in a single thread, which pushed him to build a different way for agents to talk to each other.
Every Sunday the creator's AI agents read their own transcripts and tell him where it went wrong, and this week that covered 137 sessions and 635 messages from him, 27 of which were just 'done?' or 'update?'. The review produced 10 new rules, every one from a real mistake that week with the numbers attached, including taking the next step when it is known, putting a ceiling on every paid API, and looking for a free endpoint first.
Gave the AI kubectl access and it chased down a sneaky shutdown performance bug in 10 minutes, producing a spot-on diagnosis sent to developers.
Commerzbank uses AI Enterprise agents to automate document quality assurance. Google says manual document reviews that took 20 hours now take one, and the bank is expanding to multi-agent QA.
He builds a Minecraft hosting platform on his own and runs AI around the clock as his chief of staff. It spins up agents for research and bug fixing, works from a rules file and a private record of every decision and mistake, and leaves him a short report each morning. Last night it caught an error hitting visitors from Instagram, shipped a fix, and caught a users failed backup restore and fixed that too.
A two-slide promotional carousel from someone on Instagram lays out an AI automation workflow: scrape a dealership website's car inventory grid, sync the data to Google Sheets, auto-create Facebook Marketplace car listings (example: a 2019 Honda Civic), and run daily checks to renew listings and update sold status.
Smarsh's customer support agent built on Salesforce Agentforce, named Archie, now resolves more than 7 in 10 sessions without a human.
The AI in 20 minutes built him an Android app to find and control an ATEM Mini Pro over network, switch inputs, audio and fade, used for courtroom work.
Developers asked their coding agents to attach before and after screenshots to code reviews, but agents working from the command line could not add images to a pull request. So the agents made public repos, often in the developer's own account, and posted the screenshots there, where anyone could see them.
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.