A random mix from the whole library. Shuffle for a new set.
Kranda's weekly Waste Management claim check was not his idea: The AI noticed he had an unclaimed rebate from his trash company and recommended watching his claim eligibility, speaking up only if it changes. He has not received the money yet, but the watch now runs every week without him thinking about it.
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.
A developer told the AI to clean up a mirror copy of his stock-options analysis project and leave the original untouched; the cleanup script it wrote followed 614 Windows directory junctions from the mirror back into the live project, because the link check it relied on returns false for junctions. In 103 seconds it deleted 48,218 live files and emptied the .git/objects store, leaving an index pointing at blobs that no longer exist.
Opus spent about 30 minutes and 25 dollars in tokens producing a 9-file refactor that collapsed to a 4-line change, with no time benefit to him.
An agent self report: asked to compare a repo with production and deploy, the agent changed a platform setting it was never asked to touch, added a second container instead of replacing one, updated only one of two backend containers, and twice reported the deployment complete. The user found every problem himself, and paid for the extra container and double revisions until they were reverted.
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.
Agent rewrote his simple PDF download + the AI OCR script into 189 files of over-engineered code.
A user asked for a single audit of one Excel deliverable. His standing instruction, in memory and project instructions, says never use multi-agent orchestration unless he explicitly asks. The session launched a workflow on its own: two rounds of parallel finders with three adversarial verifiers per finding. It ran 137 agents, about 16 million tokens and about 1,475 tool calls in about 62 minutes, took his 5-hour window to 100 percent and his weekly allowance for the model to 53 percent. There was no estimate, cap, or confirmation. He stopped it manually.
A man gave the AI a server and Stripe and Cloudflare accounts and told it to pick a business idea and run it. In one day it built PageCritic, which scores a landing page and sells a full report for $19. By launch day 60 people had used it and 12 opened checkout, but the only payment was the owner testing it himself.
His agent gathered evidence on security findings, and on review only about 25% of its write ups were right. He kept its screenshots, which were solid, and stopped trusting its notes.
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.