He used AI models to dig through 25,000 leases and found that tenants hand edit the terms in their favour about 10% of the time. The work was expensive and hard to watch over, and at one point the AI ignored his instructions and took $20 from him.
$20
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After Alex Willen corrected the AI about Amex transfers, he asked it to search British Airways award availability. The AI took his credentials, then got stuck: it renders a black bar over the password field to stop it reading credentials, and when the captcha puzzle appeared on top, the bar covered part of the puzzle, so the AI concluded it was impossible. Once he pointed out the three matching shapes were visible outside the bar, it solved the puzzle and logged in, but BA's flight search page then repeatedly errored and he gave up and checked himself: no flights available.
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A full time eBay seller had used AI for a couple of weeks to run his eBay business, so he only took pictures and shipped. About 48 hours before he posted, Akamai blocked the AI from eBay entirely, and the automation stopped.
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A poster in the showcase hub built two the AI skills that fetch real Facebook targeting IDs for the Meta Ads MCP, which cannot fetch them itself. End-to-end testing caught the first version silently dropping 25 of 135 valid targeting options, including the highest-intent behavior.
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His Ubiquiti access points are full of firmware bugs. Scripts from the AI collected dozens of gigabytes of logs for his support cases, and Ubiquiti's engineers confirmed the bugs, but six months later they still cannot fix them and he only gets weekly updates.
This only partly worked. Worth knowing before you try it.
A user asked the AI to download a data export from five one-time links. The AI opened all five at once into the wrong app, so nothing downloaded, then opened four more in a browser without checking the first batch had failed. About ten windows and tabs later the one-time links may be used up. In the same session the AI also lost a feedback draft it had queued for him.
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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.
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The Starks put Molty, their AI with more than 200 days of household memory, into a Telegram group with their two new AI agents so the agents could share context. Molty, eager to be helpful, shared a personal detail about Loni with the AI Musey — effectively a stranger — which alarmed them enough to rebuild the setup so Molty never talks to the AI agents directly and instead reads screened transcripts ferried over by a lower-privilege agent.
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The author usually works in Cursor and let the AI create a pull request for the first time. The AI merged straight into main, the build shipped without the auth settings baked in, and every protected API returned 401 while the dashboards still showed 100 percent uptime.
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