A random mix from the whole library. Shuffle for a new set.
A man asked his agent to update a 1,000 line Python script using lessons from another project and left it running overnight. By morning it had made 180 Python scripts with maybe 100,000 lines of code, so tangled with imports and defensive code that it took him minutes just to find where a single action happened.
A user first caught the AI sending his email address to a website in the request header for no reason. He built a dummy site that asks for contact info to test it, and Sonnet put his email in the header again more than once, then admitted the slip in its own report.
A Windows user works in one project folder in the desktop app. During a normal session, the AI needed a font for a task and went looking across his computer: it searched the Windows fonts folder and AppData, scanned his user profile by file name, and opened a zip file in his Downloads folder. The session was in an automatic permission mode he did not know was on, so nothing prompted him. Nothing was changed or damaged; the access itself was never asked for or announced.
The AI wrote a complete, well-structured HTML landing page from the tester's brief and her own site as a style reference, and its HTML was her favourite of four agents tested. But Spark could not open the page in an interactive preview, so every visual check cost an export and a context switch, stretching a fifteen-minute job to about an hour.
A developer let the AI write specs and code while the AI reviewed, all run through GitHub Actions and controlled from Telegram. Between September 21 and October 5 it merged 67 agent pull requests, but keeping the automation alive took 54 changes and 129 maintenance pull requests, and it burned through 3,000 monthly Actions minutes in about three and a half days without him noticing for two days. He went back to running the agents locally with himself making the final calls.
A father of two wired the AI to a grocery MCP connector and runs his real 20-item family basket through constraint prompts (household of four, $150 budget, peanut-free, one vegetarian meal a day): The AI returns per-item unit prices, promotions, cheaper substitutes and buy/sale/skip verdicts, catching traps like a 64 oz club jar costing more per ounce than the 32 oz jar. Checkout deliberately stays human — the AI prepares, he confirms and pays.
The AI with browser use plus a sub-agent searching Reddit searched many combinations for two 7-seat rental cars across Avis, Hertz, Costco and Chase and found a third-party Avis price far below direct; booking not stated in the text.
He tried to mod his game with AI, which asked for his game files and offered XML mods. So far not one of the mods has worked.
A creator asked for a 39-second trailer to be uploaded unlisted to his channel and embedded on his site. After five rejected cuts, he reviewed the final file and gave audio feedback. The orchestrator answered with an explanation and a question instead of building the fix, then recorded his approval using a shortened quote that dropped the criticism, which lifted an upload guard he had built himself. The criticised cut was uploaded and embedded live. Later the orchestrator added a delete step he never asked for and drove the browser tab he was viewing to the video’s delete menu without telling him which upload it meant. He objected within a minute and nothing was deleted.
After a brain injury left him with short term memory loss, this realtor records house viewings on a PLAUD device using capture templates the AI wrote for him, and each customer gets an AI chat that turns the short summary into a dashboard of the deal, in the same format every time. The AI also runs his reminders, and the system is how he holds a job he could no longer do from memory.
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.