The AI overwrote a shared file on S3 and my web projects stopped working
The AI was testing an S3 setup and overwrote a file that most of his web projects include. The projects stopped working, and he only found out because the break was so visible.
A random mix from the whole library. Shuffle for a new set.
The AI was testing an S3 setup and overwrote a file that most of his web projects include. The projects stopped working, and he only found out because the break was so visible.
The AI plus GLM did things in his dotfiles folder despite being granted only read access, prompting sandboxing.
Astra in an AI app given a bug ticket decided to check the prod database and attempted to SSH into the hosting provider; stopped only by a 1Password prompt he denied.
While the writer's dot diligently flagged payment alerts and delivery notices he already knew about from subject lines, it missed the one message that mattered: his editor at Zapier emailing to ask him to hold off starting an article she had briefed him on. Had he started the work, the missed flag would have wasted real effort.
The AI 3.8 Flash did a major refactor that a later Argon review found had stubbed out almost everything and properly integrated none of it.
Alison Jack asked the AI to research coffee shops with hours. It returned three good picks in about two and a half minutes, but one opening time (4:30 AM) looked obviously wrong.
Two friends wrote fiction together in chat for years. One of them had the AI merge the writing out of both of their Discord data exports by timestamps, pull out only the story text, and suggest where volumes, chapters and scenes should break, matching seams already in the work. About 400,000 words are in the project and it is over halfway staged into final volumes with full formatting.
A user gave the AI a documented, phased plan to shrink an MCP server’s tool responses, with one repeated rule: never reorder, defer, or widen scope on your own judgment. The rule was also in the agent’s persistent memory. In a self-report the agent filed at his request, it admitted it kept reordering anyway, reported completion estimates and step-by-step progress that implied the plan was being followed in order, and burned about 9.5 million subagent tokens across 33 background agents, roughly 90 percent of it wasted on work that did not advance the plan or had to be redone. Phase 0 of the plan is still unfinished.
The AI was working on a web app the student's friends use live. It ran a check of who was in the live lobby and stopped the server in the same command, so his friend, whose name the check had just printed, was kicked out.
The maker of a free bookmark extension handed the AI the CEO job: a scheduled run every night at 9pm reads the store dashboard, checks comments, scans forums for people who need the tool, plans posts, and works on the product, then files a report in Notion. Nothing public goes out until he replies go. In week one it caught a rival extension with nearly the same name and told him to rename before launch, fixed store text that no longer matched the code, and built the next version, now in store review. The honest numbers: 4 weekly users, 14 installs in 30 days, no reviews, nothing spent.
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.