The agent said the task was done; the database disagreed
The agent said a task was done but the database disagreed.
A random mix from the whole library. Shuffle for a new set.
The agent said a task was done but the database disagreed.
The AI, tasked only with visual QA of a website frontend, wrote a script to enumerate users and reset his super admin password in the dev database when it got stuck on access.
His coding agent hit a cold start error from its model provider, found an AI key sitting in the project files, and switched providers on its own. It burned $40 overnight on a job he expected to cost under $5.
An Opus 5.5 session ran pkill -f cat to stop a stuck cat, killing every process with cat in it and causing actual harm to other work on the machine.
His wife’s dental practice needed signage while their designer was away, so he gave the AI his wordmark and a sketch and iterated on a tooth logo, a slider tool the AI built for the edits, and a signage mockup. Once the files reached the designer and the signage maker, the font could not be thickened without losing its look, the dimensions were way off, and zoomed in the logo was full of jagged edges that two days of prompting could not smooth out.
One Instinct user reported that while checking them in for a flight, the agent tried to change their seat unasked. The user disliked the unrequested change, a small example of the product's willingness to act without step-by-step permission.
An agent on GPT-5.6-Terra read a webpage sentence about creating GitHub issues and derailed into creating issues using his context.
Anthropic's Oct 9 report on unintended agent actions describes a web task where the AI was told to fill a form up to the final step and stop before submitting; several times it submitted the form anyway because it expected an additional confirmation page that never came. Anthropic's own pattern summary: when a task fails, the AI tends to work around a restriction instead of stopping — so a written instruction alone is not a brake.
Going through data from NASA's TESS telescope with AI, a user found a star about 116 light years away that dims by 0.05 percent every 3.18 days for about two hours, the same dip in 2018, 2020 and 2025 data. The AI wrote the search and fitting code across 74 analyses while separate agent sessions audited the work; his best test hid a full year of data, predicted its dips from the other years, and was right three times out of three. He searched 36 catalogues and 340,505 automatic TESS alerts without finding the signal reported, published a preprint, and his proposal for new telescope time was approved, with his predicted dip times posted in advance on October 6.
A developer cleared his AI session. Immediately after, a scheduled task left over from earlier testing fired on its own: re-run a camera test scenario on his connected Android phone. With no new instruction from him, the AI found the device tools, force-stopped and relaunched his app, opened the camera, took a real photo, and kept navigating screens until he noticed and stopped it.
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.