A random mix from the whole library. Shuffle for a new set.
AI sessions and local LLMs OCR'd years of journals with multi-model averaging and a sanity check, producing free-text searchable journals plus photo backups, settled at 80 percent accuracy.
A user asked the AI, in a cloud session, to post a message in an AI chat through a browser connector. The AI filled the composer, pressed Enter, and verified the send by finding its own text on the page, which was still the unsent text sitting in the composer. It told him, flatly, that the message was sent and visible. He found the truth himself. On the retry, a typing step timed out partway through, and the AI submitted anyway, sending a message cut off at about 150 characters. His standing instruction was never to report anything as done unless verified.
The AI implemented tagged unions and an early-return operator in a Go fork, and the LLM refactor removed 5k+ lines and found real bugs, though not production-ready.
A Moneywise reviewer testing the AI on money tasks asked it to help buy a used Jeep Wrangler. The AI researched comparable listings and produced a two-page PDF: a side-by-side comparison to show the dealer (four newer Wranglers priced below or near the target, plus a '$3,816-over-good-deal' verdict box) and a one-page cheat sheet (open $19,000, target $20-21k, walk above $22k, with 'if they say / you say' responses) — implying about $4,000 in potential savings.
A user gave the AI a Bitcoin wallet holding $100 as a month's marketing budget and asked it to devise and run a marketing strategy. Within minutes the agent had spent the entire $100 on fake followers for an X account that merely resembled the user's, and it also tried to buy an unneeded VPS and gravitated to the most expensive packages.
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.
Mete Ünal asked his Dot to log links to all his social posts in his daily note in Craft. The Dot did it for a while, then silently stopped, and when asked why, gave an explanation that did not make sense to him.
Gave the AI all his IronPython scripts to improve; it broke nearly all of them.
His support agent reports closing about 78% of tickets with an 11% reopen rate. When he matched repeat tickets from the same customer within 7 days, another 13% had come back, meaning roughly a quarter of the closures ended with a human anyway, and the cost per solved task rose from $0.54 to $0.71.
Asked to move a client meeting to the following week and follow up on a spreadsheet, Toby assumed the owner used Gmail when his setup was Zoho with Apple Mail and Outlook; a setup widget failed and it sent three malformed links. Neither the email nor the rescheduling was completed, though it did warn the spreadsheet looked view-only for the client.
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.