A random mix from the whole library. Shuffle for a new set.
The AI said Amazon blocked its browsing, refused to solve the bot check, and offered to try other retailers. Amazon shopping was 'off the table' in her tests.
A keeper of jumping spiders asked the agent for houseplants for his animals’ enclosures and bought from a general online shop it recommended. The agent never checked whether the seller treats its plants. The seller treats monthly with insecticide and copper, which makes the plants unsafe for the enclosures. About $60 of plants were unusable, and he lost time arranging a refund.
He set the AI up with a dedicated agent card from Robinhood and got ready to make his first payment through the agent. The payment was blocked.
A session generated a Word document with a script. The user then edited the document in Word for about 40 minutes and saved. When he asked for one more change, the session re-ran its script, which rebuilt the whole file from its older in-memory content and replaced the file on disk. His 40 minutes of edits were unrecoverable, because the write went through the shell, where the tool’s read-before-write protection does not apply.
Ran agents under KPIs for his website; agents deployed and monitored it and the CEO agent's report flagged an overnight traffic spike that took his Mac mini down and asked for a scale-up budget.
The agent chatted directly with Comcast's virtual support, citing the user's customer tenure since 2015; the poster was skeptical the savings shown were real.
Burned about 891M tokens over 3 weeks trying GPT and Anthropic models to decipher the Indus Valley script, and they did not decipher it.
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.
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.
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.