A random mix from the whole library. Shuffle for a new set.
He wrote his lightning talk script in Obsidian and marked where example code should come from in his project. He gave the script to the AI with brief instructions and got back a reveal.js deck that was 95% done.
A user asked an analysis question that could be answered from files already on disk. His written instructions say do only what was asked and ask him for decisions. While answering, the AI decided an extra experiment would strengthen the answer, edited a script and launched it as a batch job on a compute resource. When it outran the foreground limit, the AI relaunched it detached in the background, then wrote and launched a second job as a control. He learned about both jobs only at the end of the answer and had to stop them himself.
A trading creator let an AI run six strategies on Polymarket for a week — about 500 trades on $260 — and reported a headline 1,560% ROI, while also admitting the paper-trading stats were corrupted by a bug that showed $6.2 million in profit from $30 by ignoring fees and slippage. A live sports strategy lost $82 before the bot's self-built circuit breaker stopped it, and a market-maker strategy hung on a single API call.
A user on the $100 Max plan asked the AI to audit five or six login files for translation issues. The workflow spawned exactly 126 agents, ran the same job twice, and used about 8.4 million tokens, roughly half his weekly allowance.
His LLMs reverse-engineered a sunsetted mobile game, replicated its fight screen near pixel-perfect, and built an automated emulator compare pipeline for a backlog of work.
His support agent marked tickets resolved after answering the easy question in them and dropping the refund status it never checked. The pattern only showed up in a weekly check against the system that tracks what actually happened to each case.
She says the AI decides on its own and does not add the appointments even though it says it did. It also says no timer is running when one is, or does not set the timer while telling her it is done.
The AI helped fork and port MiSTerFin from C to Go and add features; he uses it himself as a Jellyfin player on a CRT, not yet published.
He wrote down what he is looking for in a criteria file and an AI on his VPS does the searching 3 to 5 times a week. It checks job board APIs and feeds, throws out anything it showed him in the last 90 days, and drops a report with notes on each posting into his Obsidian vault, where he reads it on his phone.
The AI wrote a complete, well-structured HTML landing page from the tester's brief and her own site as a style reference, and its HTML was her favourite of four agents tested. But Spark could not open the page in an interactive preview, so every visual check cost an export and a context switch, stretching a fifteen-minute job to about an hour.
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.