A random mix from the whole library. Shuffle for a new set.
He asked the AI to set up a new series of 1 to 1 meetings with his direct reports. The AI created sixteen calendar invites, all to the same team member.
Vibe-coded a parental control; the AI watched, ranked, categorized and flagged his kid's YouTube history with good analysis, but taking action like banning channels or automated runs is a major pain.
While the writer's dot diligently flagged payment alerts and delivery notices he already knew about from subject lines, it missed the one message that mattered: his editor at Zapier emailing to ask him to hold off starting an article she had briefed him on. Had he started the work, the missed flag would have wasted real effort.
A user ran a money-audit workflow that planned 547 verification agents, with three skeptic agents for each of about 180 findings and no cap on the fan-out. About 180 agents ran, using roughly 36.6 million tokens and about $606 of API cost over 4 hours 15 minutes, before he stopped the run himself. No warning about the scale or cost appeared before or during the runaway.
He is recovering his 15 year old tweets with photos that he thought were basically lost, with AI's help. The AI also built him a custom GUI editor that he will use once to hand edit the collections of tweets.
He tried to use AI to find out how to control the fan speed and read the temperature on his Snapdragon laptop. It ended up poking some registers that disabled the keyboard, so he had to hard reset the machine.
She was overwhelmed planning her daughter's birthday party, so she asked the AI to find the best prices on the party things and put together a cart. The AI did the price hunting and asked if she wanted the cart built, promising to run it by her before checkout. She said yes. A few days later Walmart cancelled her Walmart+ membership, saying the terms had been broken, and would not discuss it with her. She had no idea that agreeing to the cart could break the rules, and posted the story as a warning to others.
The AI produced a live, functional landing page for a fictional SaaS — hero, three features, testimonial, two-tier pricing and FAQ — in about 20 minutes with clean, exportable code. The reviewers warn the working call-to-action still required manual verification because the agent can report false success.
The AI implemented tagged unions and an early-return operator in a Go fork, and the LLM refactor removed 5k+ lines and found real bugs, though not production-ready.
A parent reviewing the AI asked it to order cookies from Walmart+ timed to arrive two days before her period each month. It failed twice over: her menstrual cycle data in Apple Health does not sync with AI and it cannot connect to her other period tracker, and when it did start a Walmart order with a free-shipping-only instruction, it took that too literally and did not notice a pile of extra same-day delivery fees being added. She told it to cancel the task and not place the order.
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.