A random mix from the whole library. Shuffle for a new set.
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.
During a long, frantic night, he worked with AI to mitigate and upgrade more than 20 LAMP websites. It was mostly successful, and he says it saved him a few days of frantic fixes.
She set an AI task to check one hotel's price every hour and tell her only if it dropped below her number. Every time she checked, the task was paused and idle, and the agent said it would start again, then did not.
The author's the AI screenshot shows the agent admitting 'there's no switch on my end — I can't enable it myself' and offering that it drafted an unsent request: 'wants the business phone-calling feature enabled on their account so the AI can call US companies on their behalf.'
She asked the AI to erase her digital footprint. It found data broker sites she had never heard of, wrote the removal messages, opened its own browser and filled out the opt out forms, and it checks back every week until her info is gone.
Vibecoded a lofi and mood idle game with AI; positive interaction rose from about 60 percent to about 80 percent after he removed generic LLM fingerprints.
Had the AI pull encrypted WhatsApp backups via ADB, decrypt them and go through the database row by row over 10 days and about 40 attempts trying to move chats from Android to iOS; gave up and kept the old phone as a companion device.
A developer threw a significant codebase at the AI. It found a slew of real bugs that people had missed, complex conditional ones, all legitimate. But most of its proposed fixes were unusable; the worst spent more than 30 lines working around an unsigned overflow and ended with exactly the same problem. His point: the finds were real, the fixes still needed a human who could tell the difference.
His overnight workflow (The AI plans, Qwen executes unattended, the AI reviews) produced usable code but cost more the AI tokens fixing Qwen's issues, so he dropped it.
The agent said a task was done but the database disagreed.
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.