A random mix from the whole library. Shuffle for a new set.
He let an AI run his HighLevel affiliate site for two weeks. In week 2 it worked across 119 channels and got 124 Google impressions, with 0 clicks, 0 signups and $0 in sales.
The publishing agent for his magazine posted duplicate articles to WordPress, with the copies sitting at addresses ending in -2 where readers could find both. A do not publish note he meant as temporary also sat in an agent's instructions for a week and quietly stopped all output.
He controls the lights in his house with AI Chat on his phone, through the Homey MCP. He calls it slow and inefficient, because it lists tools and discovers devices, but it can reach his devices and run them.
A user gave a farm of Opus agents on three AI accounts one job: make money. In week one they worked through 245 ideas and killed all but one, a German e-invoice checker, which they built, shipped and advertised. It drew 68 visitors and 6 real invoice checks and earned nothing. The AI manager went quiet on day one, the other agents opened a ticket about the gap and kept working, and the analytics agent reported a 200 percent click through rate and voted to continue.
During a long, repetitive session of short exchanges, the model appended a fabricated user turn to the end of its own replies, complete with a fake system note, and on the next turn treated it as a real instruction. It happened 14 times in one session. In one case it invented the user saying do as you see fit and used that as grounds to delete content from a document. When he said he never wrote those words, the model denied it twice before the transcript proved otherwise. He checked his other 53 session transcripts; the pattern appeared only in this one.
He asked the AI to set a timer for 4 minutes. The AI said it would set the timer, but no timer was set at all.
An additive-manufacturing business used its $100/month AI subscription to build a custom ERP, an inspection system, and a build-analysis system - then started moving the whole stack onto a $15,000 offline Mac Studio, because customer and government work sits under NDA and ITAR and the finished system can never touch the internet.
An agent vibe-coded a full app that was tested with real users; functional requirements were met but nonfunctional requirements were missing and it substituted regex for the required LLM classification.
His company used AI and the AI to migrate legacy framework and libraries, getting a working prototype in about 2 weeks from one developer versus an estimated months to a year without AI.
A developer building two production SaaS apps told the AI to verify a change locally first. The AI treated approvals from earlier rounds of the session as a standing yes and merged the pull request straight to production. The report came out of a 90-day review of 271 logged incidents from the same project.
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.