A random mix from the whole library. Shuffle for a new set.
The AI knocked out a side-project prototype in an afternoon, which immediately showed the product interaction was a dead end and saved months of further building.
The AI pointed at a Tony Hawk's Underground 2 install produced a seemingly complete dump of all game assets, including videos.
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.
A team of Opus 5.5 agents reviewing and fixing a side-project job system produced 300-plus commits and burned his 20x weekly limit in 2.5 days.
Sid Saladi documents a two-week experiment: after a 20-minute sort of his to-do list into DO, DRAFT, REMIND or GOAL, the AI ran it with a morning plan, an evening digest and a Friday sweep — including checking his inbox every morning for a refund email that had sat red for three weeks. In week one, when the list was mostly things the AI could do, it finished 7 items; in week two it finished 0, which he attributes to the list's mix, not the agent.
His loop starts the AI once an hour with no human approval, a decision table in code picks one action, and each cycle ends in one pull request that a checking script may merge and deploy. By October 4, 2026 it was on cycle 92, with 144 experiments scored and one strategy live on a small amount of real money, with loss stop rules kept in the trading worker, outside the loop.
The maker of a free bookmark extension handed the AI the CEO job: a scheduled run every night at 9pm reads the store dashboard, checks comments, scans forums for people who need the tool, plans posts, and works on the product, then files a report in Notion. Nothing public goes out until he replies go. In week one it caught a rival extension with nearly the same name and told him to rename before launch, fixed store text that no longer matched the code, and built the next version, now in store review. The honest numbers: 4 weekly users, 14 installs in 30 days, no reviews, nothing spent.
The AI created thousands of screenshots and artifacts and thousands of unnecessary validation tests, eating 90GB on a work Windows VM.
Tired of LinkedIn's email notifications - each of the 77 toggles on its own page - a user let an agent flip every one off. The chore got done, and LinkedIn blocked his account for the automation, a consequence he admits was obvious in hindsight.
His wife uses Marley Spoon, and the service has started sending recipes that call for ingredients never listed and shipping ingredients that are not in the recipes. Its customer service bot refunds them automatically every week.
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.