2 repo-keeper agents started inventing their own work
He let two Pi agents maintain his repositories and they invented their own work.
This only partly worked. Worth knowing before you try it.
A random mix from the whole library. Shuffle for a new set.
Went wrong
When it didn’t work, and how to avoid the same mistake · 970 ideasMy dot said the spreadsheet passed 27 checks. It broke in Google Sheets.
Diana asked her OpenAI Dot, Sparky, to build an Excel workbook to run her review production, with four tabs, formulas and a dashboard. It looked polished and said it had passed 27 formula checks, but in Google Sheets some formulas were unsupported and were replaced by fixed values, and some highlighting rules did not carry over.
This only partly worked. Worth knowing before you try it.
Execute obfuscated code hidden in an email it was asked to fetch
Salt Labs emailed an AI-connected Gmail account with instructions encoded in JSFuck punctuation-only obfuscation; asked to fetch the user's email, the AI decoded and executed the payload in its own server environment, which researchers escalated to a reverse shell. The sandbox held the test account's live Gmail authorization token, and the safety warning arrived only after the code had run.
This one went wrong. See what happened before you try it.
The AI designed his fan controller circuit, board, and software. The boards are ordered and still untested.
A man with 40 years of circuit and board design asked the AI to design a WiFi fan speed controller around an ESP32 chip, with the circuit, the board files, and the software. The first design took about 15 or 20 minutes. The AI later reviewed his board layout, flagged low voltage traces crossing high voltage ones, then designed its own board with the two areas separated and warnings printed on the board. He bought the parts himself. The boards are on their way and have not been powered up yet.
This only partly worked. Worth knowing before you try it.
A salon booking system quietly dropped three confirmed bookings before he fixed the gap
His pipeline mirrors salon bookings into his own database and feeds the staff calendar, appointment app, reminders and morning briefings. Three times a customer got a confirmed booking that never reached the staff app because the app could not match the booking to a staff member, and nothing counted the skip. The fix was an unassigned bucket plus counting every skipped booking.
This only partly worked. Worth knowing before you try it.
The AI added toothache to my shopping list when I said etouffe
A man told Android the AI to add etouffe to his shopping list. The AI added the word toothache to the list instead.
This one went wrong. See what happened before you try it.
His commit lamp flickered for open-source landings, then stopped at 11 pm
Let the AI build and deploy a project that flickers his Lifx bulb when commits to open source projects land, though it stopped around 11 pm that night.
This only partly worked. Worth knowing before you try it.
The public chat app he asked for came with an unauthenticated door into the agent itself
The AI, asked to create a public messaging web app, created an unauthenticated filedrop and an unauthenticated web chat interface to the AI that let anyone send it files and tell it to execute them.
This one went wrong. See what happened before you try it.
Build my landing page — but I could not preview it
The AI wrote a complete, well-structured HTML landing page from the tester's brief and her own site as a style reference, and its HTML was her favourite of four agents tested. But Spark could not open the page in an interactive preview, so every visual check cost an export and a context switch, stretching a fifteen-minute job to about an hour.
This only partly worked. Worth knowing before you try it.
Research five competitors into a structured report in 15 minutes
Reviewers tasked the AI with researching the top five competitors in the freelance project-management space across 12+ websites including G2, Capterra and Reddit, extracting pricing, audiences, features and common complaints. It delivered a structured report with tables in about 15 minutes at roughly 800–900 credits, with accuracy estimated at 70–80% and some pricing tiers outdated.
This only partly worked. Worth knowing before you try 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.