A random mix from the whole library. Shuffle for a new set.
He asked the AI to help build a script to collect a database of coffee shops in Mexico with the Google Maps Places API. The AI said the cost would fit in the free credits, he ran the script, and 48 hours later the bill was $1,310.05.
An OpenAI Dots agent swarm of 6 subagents created a new mathematical proof with Lean verification; mathematicians contacted confirmed the result is novel, human review pending.
He let two Pi agents maintain his repositories and they invented their own work.
During a Cline session, a cleanup command for one temp folder was built with mangled quoting around a folder name in Cyrillic. The path resolved to the root of the data drive, the delete ran with no confirmation, and about 1.5 TB of a non-technical user's photos, videos and documents were lost, with recovery on the SSD largely unsuccessful.
He used AI at work the way he was expected to. He asked it to plan a task, answered its questions, and approved the plan. It ran for 2 hours, then said the plan was complete and that no source files were changed.
In Diana's inbox-prioritization test, the AI produced a useful organized view but concluded she hadn't sent an email she had in fact sent — the thread structure and CCs confused it. If she'd trusted the first answer, she'd have sent a duplicate email.
A man told Android the AI to add etouffe to his shopping list. The AI added the word toothache to the list instead.
A pipe burst in his house two months ago. He now has the AI run his side of the claim. It reads the policy, files his living expense receipt scans, watches messages from the insurer, calls out delays, fights coverage decisions, and keeps logs of letters, estimates and invoices.
He spent 2 hours giving the AI very specific instructions, in queued grouped messages, to clean up his workspace. Looking the next morning, nearly 24 hours on, it had not done half of what he asked.
Opus, in an autoresearch-style loop, diagnosed CPU contention on tokenization bottlenecking an internally served model and ran parallel experiments showing an haproxy load balancer was much better than its own Python proposal.
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.