A random mix from the whole library. Shuffle for a new set.
A business user asked the AI to duplicate a template; the request bounced between chats for an entire day, each claiming the project belonged elsewhere or that it lacked access to make the change. Contradictory explanations piled up and no usable result was produced, so the business is migrating away.
Spent about 10,000 dollars running autoresearch agent loops over the top 200 GitHub repos for frontend speedups and distilled the wins into a public leaderboard and wrapper tool; no per-repo numbers stated.
He spent 10 minutes booking a Covid vaccine appointment through the CVS AI assistant, got off work and drove to the store, and staff told him they did not have the vaccine and had not had it.
A team used an AI 2.5 tool to go through large sets of public comments. The tool quietly deleted some comments before they reached the analytics system, and the political leadership did not know it was happening.
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 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 same user asked his Dot to publish one article to his own site, DEV and Medium; the workflow had worked in one shot the previous week. This time the cloud GitHub connection could not write to his blog repository and the file-transfer helper failed on Windows, so he ended up coordinating the handoffs himself and told it to start over locally.
Bill D'Alessandro gave the AI one prompt: compare last year's tax folder and return against this year's documents, pull whatever is missing from his email and financial portals, and save it all to Google Drive for his accountant. It got about 90% of the way there.
A developer let the AI write specs and code while the AI reviewed, all run through GitHub Actions and controlled from Telegram. Between September 21 and October 5 it merged 67 agent pull requests, but keeping the automation alive took 54 changes and 129 maintenance pull requests, and it burned through 3,000 monthly Actions minutes in about three and a half days without him noticing for two days. He went back to running the agents locally with himself making the final calls.
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.