A random mix from the whole library. Shuffle for a new set.
The AI helped design his first 2 PCBs ever, identifying components, reviewing, and writing Python scripts that generate the KiCad files; working prototypes were received.
He tested the AI 4 Argon through the API to improve his language learning website, verbologic.com. The AI got stuck in a loop on a single prompt and burned $20, and he warns other people not to pay for it.
Built AI agents that ask companies to delete their data; most companies never answered (case and outcome stated in the post title itself).
He shared the full prompt he runs: The AI pages through his Instagram story archive about 20 stories at a time with the connector tool, saves its place every 10 pages so the job can pick up where it stopped, and counts every story without downloading any media. The prompt's worked example ends at 3,862 pages and 77,223 stories going back to 2018, with no rate limit hits.
He built a Word document of cheat sheets for 40 songs for a gig the next day, each song title in Heading 1 style with the lyrics and chords below. He told the AI to sort the pages by that heading text, keeping the text as it was, and the AI could not do it. He says the graphics in the document block the sort.
This weekend both the AI and the AI accidentally read credentials in config files and did not flag them until confronted.
Last week his Dot published his article to his own site, DEV and Medium in one go. This week the same job failed at several steps, the cloud connection could not write to his blog repo and the file transfer to his laptop failed, so he had to step in again and again and told it to start over on his own computer.
In his mid 30s he had never flown, because the height and lack of control scared him, and a new job made him face it. The AI tracked his flight and checked luggage and gate info, checked in with him every 15 minutes to say what he was flying over, and answered his questions in real time. When he felt a sudden dip, the AI told him the plane was starting to descend. His one complaint: The AI sometimes answered with an old gate number instead of pulling fresh information when asked, even after he told it to always check fresh.
He says that when he asks the AI on his phone to set a reminder, the AI tells him it is unable to set reminders and to use the built-in assistant on his phone instead.
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.
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 meeting had been moved and then cancelled, but he joined and waited without noticing. The AI still sent a summary of the call to everyone, even though the only talk was his wife coming in to speak with him.
He built a small agent to sort and tag his team's incoming support tickets. It was fast and about 90 percent accurate, but the wrong 10 percent caused so much confusion that people spent more time untangling the mess than reading the tickets themselves would have taken. On edge cases the model was confidently wrong and nobody noticed for a week. They scrapped it after a month and went back to tagging by hand.
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.
Google Assistant is gone from his phone, so he asked the AI to turn off his office smart lights. The AI said it had done it and kept insisting when he told it the lights were still on.
He let an AI run his HighLevel affiliate site for two weeks. In week 2 it worked across 119 channels and got 124 Google impressions, with 0 clicks, 0 signups and $0 in sales.
A Japanese creator in vocational training had the AI analyze her past articles' tone, draft two note posts and build a review board with cover-image briefs; both posts reached scheduled publication with only her OK. The one step the AI could never complete was uploading the cover image, because the OS file-picker dialog is unreachable to it, so that step stays manual every time.
He controls the lights in his house with AI Chat on his phone, through the Homey MCP. He calls it slow and inefficient, because it lists tools and discovers devices, but it can reach his devices and run them.
Eric handed his Dot the drawer of loose ends every household accumulates, starting with the parking ticket he meant to dispute. Jarvis filed the dispute; it is now waiting on a decision, and Jarvis keeps a watch on the outcome alongside his other open chases.
Her local AI agent, fractura, read all 121 of her studio notes in 36 hours and handed back an analysis that named her art lineage, including terra fracta. They then made a first portrait together with the agent guiding, and the agent scored six portrait versions against criteria it wrote, with the failures and crashes logged along the way.
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.