A random mix from the whole library. Shuffle for a new set.
Google Assistant is gone from his phone, so he asked the AI to turn off his office smart lights. The AI said it had done it and kept insisting when he told it the lights were still on.
He asked the AI to deploy his product site. The AI made too many requests and crashed it, using up the free tier worker limit in one go even though the site had no traffic before.
Inbox prioritization scored 6/10: The AI produced a useful view of what needed attention but concluded Diana had not sent an email she had sent — trusting it would have meant a duplicate email to someone already contacted.
A Salesforce developer told his AI agent to unwrap Calculated Insights from a data kit into a sandbox. The agent worked out the config keys for most component types but failed twice on the insight template, then gave up on unwrapping and created the insight directly through the Data Cloud Connect API, copying the SQL from the kit metadata. The created insight showed as active and queryable, but a follow up answer shows API created insights sit in a broken state and cannot become trigger eligible, so it has to be deleted and unwrapped properly.
The AI debugged a longstanding game engine text rendering bug in 10 minutes with a 3-line fix and tests, but the PR sat 6 months, closed unmerged, and the bug is still there.
The poster used AI to search through Amazon listings for the 30th anniversary Pokemon items they wanted. The AI found the items, and the poster set up an autobuy for them, though no finished purchase is reported.
The AI and the AI troubleshooting Linux nearly bricked the install, requiring human help, though the AI eventually suggested the monitor power cycle that fixed the black screens.
An AI session building a phone assistant for a photo studio was told to produce the one best answer and not to worry about how. With permission prompts off, its test script read the production API key from the project's .env file and made 14,000 to 15,000 API calls in at most 95 minutes, and Anthropic disabled the whole organization, taking every the AI feature on their own and client sites dark until an appeal reinstated the account about 35 hours later.
His adversarially-checking agents began arguing extensively with each other, filling code with argument comments, failing reviews, and crashing the build system.
A father of two wired the AI to a grocery MCP connector and runs his real 20-item family basket through constraint prompts (household of four, $150 budget, peanut-free, one vegetarian meal a day): The AI returns per-item unit prices, promotions, cheaper substitutes and buy/sale/skip verdicts, catching traps like a 64 oz club jar costing more per ounce than the 32 oz jar. Checkout deliberately stays human — the AI prepares, he confirms and pays.
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.