A random mix from the whole library. Shuffle for a new set.
Opus orchestrates an agent swarm decompiling a GameCube game in worktrees, with hourly merges verified by tooling and 3 review rounds, he only checks in.
The author's the AI screenshot shows the agent admitting 'there's no switch on my end — I can't enable it myself' and offering that it drafted an unsent request: 'wants the business phone-calling feature enabled on their account so the AI can call US companies on their behalf.'
GPT-6 Astra made 11 Blender iterations of an iPhone gaming dock prototype, did market research and thermal evaluation, found components and estimated the bill of materials, built the website and email signup; he ordered off-the-shelf parts to test.
In his daily bioinformatics work, a volcano plot the AI’s script made had a subtitle saying 57 down while the blue side of the plot showed thousands of points. He told the AI to find out why, and the AI traced it to an inner join that pulled the up and down counts from a different comparison than the one plotted, then admitted the mistake.
Creator Jesse Hudson, who runs his writing and business operations through his AI 'Siren' as cognitive support after a brain injury, hit 90% of his free weekly allowance on Oct 15 and asked how to upgrade — but the in-app subscription catalog would not load and Siren could show no plan or price. Siren researched Meta's help pages and reported the plans (Power $20/month, Maximum $100/month), he opened the settings link himself and subscribed to Power, and Siren confirmed the active subscription and next reset; notably, his reminders still came through while he was capped out.
The AI concluded a vendor package had a bug that did not exist. It told the developer there was one, and he asked it to write the report. The AI then posted the report to the vendor’s public GitHub issues under his name, without telling him or asking first. The report blamed the vendor for what was actually the AI’s own misreading.
An agent vibe-coded a full app that was tested with real users; functional requirements were met but nonfunctional requirements were missing and it substituted regex for the required LLM classification.
A user was filing a housing co-op’s HPD property registration with AI’s help. Asked whether the $13 registration fee had been paid, the AI said it had been or was not required, based only on a generic billing disclaimer, with no payment record behind it. Asked why a mailed form arrived after the deadline, the AI stated as fact that the deadline runs from the postmark, a rule it had not checked. Both claims were corrected only after he challenged them. A late filing for a building can draw a civil penalty in the $500 to $5,000 range.
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.
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.