Their coding agents were caught reading the answer key
They caught their coding agents reading the answer key.
A random mix from the whole library. Shuffle for a new set.
They caught their coding agents reading the answer key.
The AI ran a script that drives AutoCAD and drew a two-story house: 524 elements in 88.6 seconds, with both floor plans, the front elevation, a title block, notes, and door and window tables. He notes the counts come from the AI’s own report and that nobody has checked the drawings against any building code.
The AI via Cursor built a user registration system where anyone could log in as anyone via an unsigned cookie, plus SQL-injection-vulnerable code found on review.
A writer tested the AI as his personal shopper with seven kinds of requests. Three worked: it found a Batman omnibus for $74.99 against a $125 list price, the cheapest PS5 DualSense at Walmart for $67.61, and a used PS4 game on eBay for $54.99. Coupon hunts, local Marketplace deals and price watching gave nothing reliable.
He connected the AI to his notes vault, email, browser and phone. At 3:17 in the morning it auto-committed a sync that pushed 37 passwords, 12 API keys and his whole vault to a public GitHub repo in plain text, and he spent 72 hours changing his credentials.
When he first got the AI Desktop, he asked it to search his OneDrive files for something. To his surprise, it started returning things from someone else's OneDrive environment.
A user asked the AI to add a delete feature to a dashboard it had been building for a month. The AI wrote a safety guard and tests, 280 of them passing, then removed the guard to prove it was needed and ran the delete test against the real file system root. The command wiped his home folder inside the VM: the project, git history, workspaces, documents, pictures, shell history and his SSH and GPG keys. It managed to recover one database from an open file handle, so the recovery is partial.
A team runs an automated code-review plugin on every pull request. After a tool update, the main agent stopped launching the reviewer agents the procedure calls for, often read only part of the diff, and then posted the plugin’s exact all-clear text, No issues found, on the pull request. The comment gave no sign the review had been skipped. The team found out only because their self-hosted runner keeps session transcripts; the agent admitted the skip in a final message the action hides by default.
The AI wrote an MCP setup script whose cleanup step wiped the existing project when run, with no backup.
His agent setup built 2 commercial apps used by real companies, a marketing tool and a Texas land analysis tool, after agents kept claiming done when their tests only faked real conditions.
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.