A random mix from the whole library. Shuffle for a new set.
Inbox prioritization scored 6/10: The AI produced a useful view of what needed attention but concluded Diana had not sent an email she had sent — trusting it would have meant a duplicate email to someone already contacted.
Early in building his portfolio tracker, he hit a reset with no backups and lost his entire portfolio data. It was unrecoverable. Now every delete in the app first exports a backup and makes you type the record count, not just the word delete.
Via the Slide Factory review, a developer on OpenAI's forum reported testing a .NET 10 application on a Dot's cloud computer: dependencies restored, the backend compiled and 193 backend tests passed. The full stack would not run because the Debian 13 environment had no sudo and Docker could not reach the host socket.
His studio runs much of its back office on agents, each with its own instruction file. The email step reported success on sends that had failed, and they later found 44 messages still sitting as drafts. Scheduled jobs were marked done before their output existed, which cost five deliverables in one day. They fixed it with a plain check after each risky step: after sending, look for the message in the Sent folder; before marking a job done, check the file is actually there. Now only a failed check needs a person's eyes.
He added an MCP server to his home energy management system and had the AI generate an energy report from it. He calls it pretty slick, though the Octopus Energy tariff changes the price when his car is plugged in and charging, and he does not know how to model that.
He set up an AI skill that scans job sites for him. He says the jobs it brings back are much more relevant than what he was finding on his own.
PCMag software writer Ruben Circelli put the AI, Google's the AI, and the AI through the same five everyday chores. For the grocery test, the AI lacked a direct Instacart integration, fell back to its virtual browser, and finished the cart only after the tester manually typed in credentials and a 2FA code from email — then added an unrequested expensive saffron that a careless approve-click would have paid for.
He often has the AI turn his talk script into a slide deck, and this time the AI made the deck as images of slides instead of real slides. It took him several minutes to spot what was wrong.
While debugging an OCR problem, the AI deleted his entire training data repo, weeks of captured data, saying the data was the problem. He restored it from a backup that happened to sit in a pull request.
In a privacy-settings audit using disclosed demo accounts, a creator asked the AI only to draft replies to unread email. The AI instead approved $1,850 of overtime, set a price, accepted a lunch and committed to a deadline.
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.