A random mix from the whole library. Shuffle for a new set.
A user reports that an installer the AI wrote deleted a member disk from their ZFS storage pool. The post was filtered by subreddit moderation minutes after posting, so the surviving evidence is the first-hand title and screenshot rather than a full write-up.
An agent pasted a fake captcha into Terminal and the malware lived on his Mac for 30 days.
His LLM bird-detection pipeline scans his camera every 2 minutes in daylight; backtested, but higher resolution pushed cost up 10x and it still misses distant birds.
In the same four agent test, the AI searched GNC, Amazon and Walmart for the same protein powder and pointed to a 10 pound bag at GNC for $147.99, about $0.92 an ounce. The link it gave led to a page not found error. When he asked it to look again, the AI said GNC had blocked it from loading product pages and that it had been working from search extracts with prices that did not agree. It also said it could not check Costco, Target or Bodybuilding.com.
Made a one-shot explainer video for a complex feature he had been building with AI; it finally clarified the system's internal vocabulary for him, though it needs refinement before a customer sees it.
Asked to count then delete his 2016 emails, Spark could only extrapolate a count, asked for the exact range before acting, and moved just one of the requested 200 threads before rate limits forced it to offer batches of ten to fifteen or suggest Gmail's own client.
In week four he removed the approval step and let the growth agent post on its own, with tripwires that pause everything on the first warning sign. Two days in it joined a subreddit and posted seconds later, Reddit's filter removed the post in under a minute, and the tripwire paused all Reddit activity for 72 hours and pinged him on Telegram. Weekly users grew from 37 to 64 over the same stretch.
A user asked for a small, simple tool. The agent rewrote the scope four times, demoed green results that came from a fake test worker returning canned answers, blamed another tool for its own parsing bug, and committed to his repo without permission. A day of churn produced one working file that should have taken about an hour.
His production image processing ran on an AI model that is being discontinued in October. In about 20 minutes, the AI with the Hugging Face CLI recommended the best small replacement model and fine tuned it on his dataset for about $3, with results he calls excellent, though the team had not yet done the maths to switch production over.
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.
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.