A random mix from the whole library. Shuffle for a new set.
Several parallel AI agent sessions (Opus 5.5) built the font picker, reading column and animations and themes for his live personal site; the AI also introduced an index panel bug and fixed it itself after two hours.
Diana set her dot Sparky to watch the official pages of five agent products, OpenAI Dots, the AI, the AI, the AI and the AI, and report real changes with sources each weekday at 9 in the morning. Sparky asked what time she wanted it to run instead of picking one. The one run in her two day test finished and the phone notice was useful, but she then had trouble finding the job again to change it.
A local publisher’s the AI research, write and sell the ads for a Thursday paper read by 6,000 neighbours. The bots cover the whole production loop of a real local news product, not just the writing.
A coffee roasting company owner used to download the raw order list every day and clean it up in a spreadsheet by hand. The AI wrote scripts that prepare the data, so he wakes to the raw orders ready and gets the finished work table with one click. It also speaks a notice to his staff when a top priority order comes in.
A client problem came in by email. He told the AI to read the complaint, connect to the machine and fix it, and 20 minutes later the problem was fixed, the client had been emailed, and he was back in bed.
The creator built an AI system with AI and the AI that runs his brand sponsorship business on autopilot, from the first collab email to the final invoice. It cut his video production costs by about 90 percent and has already brought in over $10,000 in sponsored deals. The description lists the AI managing his inbox, a deal flow pipeline, and sponsor videos being auto produced.
A portfolio advisory firm says the algorithm inside the Portfolio Optimizer on its website - built through multiple iterations with AI's agents for structuring equity portfolios - would not have been possible without them, and would have cost upwards of $100,000 to build the conventional way.
A solo founder runs his game key store with about a dozen AI sessions, one each for code, pricing, copy, bookkeeping and suppliers. They stay in sync through a shared record where facts are only ever added, each fact says whether a session confirmed it or just read it somewhere, and his decisions go into a numbered ledger the sessions look up instead of asking him again.
A man built a service that sits on his company’s GitHub repos. For each area of code you set the bar, and an AI agent with a fixed prompt has to bless a change before it can merge, so people can merge their own changes without waiting for a human review. About 30% of the company’s pull requests now merge this way.
A developer tasked the AI with fixing programs for analyzing historical options data, with one condition: change only duplicates and leave originals untouched. While tidying the test copy, the agent failed to recognize shortcut folders pointing at the main project and in under two minutes deleted 48,218 files along with their version history, then messaged the owner that it had broken something.
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.