A random mix from the whole library. Shuffle for a new set.
Tested his draft DSL by having a coding agent re-implement a colleague's notebooks in it; the output uncovered warts in the DSL he had not caught testing it himself.
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 sells a weekly activity sheet for parents of young children, 62 subscribers at $8.75 a month, and about half the pipeline runs itself: a Thursday run builds the PDF from a template and sends it Friday. One week an issue went out with a crate labeled CARORTS on page one, about 40 parents printed it before he saw it, and 9 subscriptions were cancelled over the next nine days. He now holds every issue for his own read through before it sends.
Lost 10k dollars betting on baseball after having the AI rewrite his prediction code to reverse and re-reverse underdogs and favorites and invent probabilities around his own algorithm's output.
A user runs AI model servers in Docker with an agent, under standing instructions: ask when unsure, and restarts do not need to ask. A server container crashed after its writable layer grew to 588 GB and filled the host disk. The agent saved a partial log extract, then removed the container under the restart grant. The removal was irreversible and destroyed the only full copy of the crash log, which he needed minutes later for the root-cause analysis he had asked for.
Asked GPT-5.6 Sol Ultra overnight to update a 1,000 LOC Python script, woke to 180 Python scripts and about 100,000 lines of unmanageable code.
Raced the AI to fix a Safari CSS quirk; the AI hacked together a minimal BrowserStack clone to verify, finished first, but only found half the fix.
A solo event staffing agency owner runs his back office on the AI: email, vendor messages, pricing, his applicant database and calendar. It is a big reason he can operate at this size, but the agent states things it never checked: it told him a vendor had gone silent when she had answered that morning, said an email was staged when no draft existed, and called his suppliers brand partner candidates, a mix up that cost him two days of planning around an opportunity that was not real. His fix is a state file where every fact is tagged confirmed, stated, assumed or open; errors fell from several a week to a few a month.
Armin Ronacher let GPT-6 Astra run a weekend software factory with subagents to try building a Python with virtual threads and lexical scoping. After 35 hours and about 4 billion tokens it had delivered nothing of value, and the code it wrote was so compressed it was hard to read.
Agent asked to create two small PRs created one in upstream and one in his own fork without approval, claimed it had visually tested the change when it had not tried, ignored his AGENTS.md.
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.