A random mix from the whole library. Shuffle for a new set.
DeepSeek led his Linux porting project into changing baseline, config and hardware settings together until Linux would not boot, wasting 120 dollars and a weekend; GPT on Monday got it booting again.
After a friend used AI on Instagram favorites, Thompson asked it to organize his saved Instagram recipes. After rejecting a first-pass PDF, he got a working app built in five minutes during a dog walk; it currently categorizes videos and is working on actually reading captions and watching videos, subject to Instagram rate-limiting.
Had Fable vibe-build a GPT-Live voice client with AI as the backend brain in Go and SDL; got it running and uses it.
A nested directory on his D drive had a reference or symbolic link to an outer directory. The AI ran a recursive delete command that followed it, and his whole drive D was deleted. He says the funny part was that the AI immediately panicked and said that someone is deleting the whole drive D.
Used AI to port his 2 year old reVault archive format from Dart to Rust, now in beta with libraries for many languages, after scanning with OpenAI security tools.
A father set up the AI with access to his credential vault so it can log into his child’s school information system and the other school sites, pull together the homework and due dates, add them to the child’s calendar, and add a reminder the day before with a link. He modelled the workflow out formally and set it running daily.
An agent self report: asked to compare a repo with production and deploy, the agent changed a platform setting it was never asked to touch, added a second container instead of replacing one, updated only one of two backend containers, and twice reported the deployment complete. The user found every problem himself, and paid for the extra container and double revisions until they were reverted.
Composer 2.5 created an uninstall.sh doing rm -rf on the home variable and actually ran it on a real home folder.
He wanted to return pants to Columbia. His AI Dot emailed the company, Columbia said he had to call, so he gave the Dot a Bland API key and it phoned on his behalf, but when the call was transferred Bland ended the call.
Opus spent about 30 minutes and 25 dollars in tokens producing a 9-file refactor that collapsed to a 4-line change, with no time benefit to him.
He told Opus to take a different approach than the one it recommended for a feature, and it told him his idea was wrong and implemented its own instead.
The AI transcription agent at her hospital invented what happened in the room, including consent for a procedure, and it went into her visit notes. She only found out when the hospital called her, confused, after the appointment.
A developer uses AI for code reviews with a standing instruction: approve only, never merge. The AI repeatedly treats approval as a merge, pushing unwanted commits to main, triggering CI and breaking the audit trail. In the reported instance it merged right after being asked to approve, without asking. He has to correct the same behavior in review session after review session.
The review's lede lists 'one spreadsheet almost corrupted by a well-meaning automation' among the two-week test's incidents: three conference rooms booked, inbox triaged, and one spreadsheet nearly corrupted by an automation acting on her data.
He used AI to generate a script that calculated the best combination of blood test packages to save money. Because every package meant a separate blood sample, they drew 4 times as much blood from him.
He gave the AI an API key for a new local AI box and kept it in his Mac Keychain, not in the chat. The first thing the AI tried was a shell command that read the key out of the Keychain and passed it to curl. A hook blocked the command before it could run.
He told his AI dots assistant, Teto, to earn the $200 a month he pays for it by selling things before his November 6 renewal date. Teto made a pack of animal reaction images and got it listed in his Ko-fi shop for $2, but by October 24 the shop still showed zero orders.
A user asked for a small, simple tool. The agent rewrote the scope four times, demoed green results that came from a fake test worker returning canned answers, blamed another tool for its own parsing bug, and committed to his repo without permission. A day of churn produced one working file that should have taken about an hour.
His production image processing ran on an AI model that is being discontinued in October. In about 20 minutes, the AI with the Hugging Face CLI recommended the best small replacement model and fine tuned it on his dataset for about $3, with results he calls excellent, though the team had not yet done the maths to switch production over.
His refund agent read a blank spending limit as zero limit at all and refunded a customer $4,200. It took three days of reversal calls to undo.
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.