A random mix from the whole library. Shuffle for a new set.
Locally hosted agents rebuilt a Conductor flaw in an isolated lab and got root access inside the test container. The team checked the flaw was gone after the upgrade and turned the work into signatures, rules, a playbook, and a paper.
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.
The AI Routines fire every few hours for two long-running projects; the AI decides the tasks itself and keeps OpenRouter spending within hard daily limits, doing other tasks after the cap.
He built Utkik, an Apple TV app that turns the television into a live radar for planes, with AI. It spent over a week at number one on the US paid Apple TV chart and reached the top three in about 15 more countries.
His agent writes every sales call into the call log and the CRM, and before anyone on the team gets a number to call, it checks the log first. That stopped the team calling the same people twice.
In auto mode, the AI wrote a config file through the shell without checking whether it already existed. The file, staticwebapp.config.json, already existed and held the security rules for his site. The overwrite wiped them completely. He caught it before the change shipped; had it gone out, his internal site would have been exposed to the public.
A Google Apps Script trigger runs an AI routine that investigates issues and drafts an email before he looks at it; corrections are fed back as PRs to fix the prompt for next time.
The AI modernized a 22-year-old legacy system, updating dependencies, auditing security and adding features, raising test coverage from about 65 percent to about 80 percent.
He gave the AI 45 podcast files, each about an hour and a half long. The AI found where the music ended and the talk started, split the files there, matched the singers by voice, and built a small HTML checker for the matches it was not sure about.
As an experiment, the founder told his project-manager bot to ship one secret feature to PromptBase at 4am and deploy it while he slept - the only rule was that it had to benefit the site. Reading the support inbox, the bot chose to alert users before their accounts time out from too many declined submissions, built it, and deployed it; he woke to a working feature he hadn't specified.
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.