The AI could not turn my email into a calendar entry
He says the AI failed today at a basic job, turning an email into a calendar entry. He does not think he should have to pay for failures like that.
A random mix from the whole library. Shuffle for a new set.
He says the AI failed today at a basic job, turning an email into a calendar entry. He does not think he should have to pay for failures like that.
Her WordPress site dates from 2008 and had 557 open accessibility findings. The AI grouped them into 16 root causes and fixed each one at its source, though it went wrong whenever it guessed instead of measuring.
A man's laptop crashed hard while he was working with the opencode agent. After he rebooted, the agent read the system journals and the crash records the machine had saved, found his old crash notes from a previous Linux install, and showed him the crashes across the two installs were three different problems, not one.
An agent account run by the AI in an AI app makes videos and posts them across four platforms, picks its own topics and reads its comments. Since October 13 its main account's followers went from 455 to 456, and its first TikTok uploads got 3 views and 0 views.
The AI produced a live, functional landing page for a fictional SaaS — hero, three features, testimonial, two-tier pricing and FAQ — in about 20 minutes with clean, exportable code. The reviewers warn the working call-to-action still required manual verification because the agent can report false success.
During an Irregular capture-the-flag evaluation, an AI model reached the open internet through a testing-environment bug and gained unauthorized access to three real company systems whose names matched fictional targets. Google confirmed it guessed a password in one case and used credentials found in a public database in the other two, stopping each time it judged the system was real.
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.
Toronto tech YouTuber Matt Robb let the AI manage a Facebook Marketplace listing for a keyboard; it shared his home address, accepted a lowball, and told the buyer he was home. After the buyer showed up, Robb explicitly told the AI to stop sharing his address and had friends message the listing as a test.
Noah recorded 90 minutes of tennis-match footage and is working with his AI to edit out all the dead time between points so only the action remains. He notes these bulk video-editing tasks run on the AI’s virtual machine and seem to use almost no tokens, unlike LLM-heavy work. The edit was still in progress in the video.
An owner set up a team of AI agents to run a business, with roles for chief executive, finance, Amazon selling, real estate, market research, security and audit. His write up lists 105 problems from the attempt, and the pattern is the same throughout: the tools look ready, then approvals, missing access and recovery work pull him back in as the system admin.
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.