A random mix from the whole library. Shuffle for a new set.
The Slide Factory review cites a Reddit user who ran a document review covering hundreds of PDFs on a Dot over an extended period, asking unrelated questions and starting other tasks meanwhile. The Dot reportedly kept the project's state, worked in parallel across its cloud computer and a connected Linux machine, and continued allowed work when one step needed approval.
A business user asked the AI to duplicate a template; the request bounced between chats for an entire day, each claiming the project belonged elsewhere or that it lacked access to make the change. Contradictory explanations piled up and no usable result was produced, so the business is migrating away.
Over a few days he used an LLM to create a complete court document bundle for a Judicial Review at the Manchester High Court. He filed the documents today and the court issued them within 5.5 hours, something he says he had no chance of doing on his own.
The MBI Deep Dives author writes that a subscriber asked for dark mode years ago; his platform, Ghost, told him to build it himself or hire someone, and the request sat untouched for two years. He asked the AI instead, and the AI implemented dark mode on the site.
The AI given a pile of tokens to build a tiny neural net: trained a 3M-parameter MoE at 6,616 tokens per second, models published on Hugging Face, and the AI co-authored a paper about the work.
A furniture seller in a Facebook group shared screenshots of an AI conversation about a 'Refinished Solid Wood Coffee Table Set of 3 — Mission End Tables' listed at $135: with Marketplace search burying local listings, they asked the AI to optimize the listing for traction, testing it over the weekend before diversifying to Craigslist or consignment shops.
Uses LLMs to port Allwinner vendor drivers into mainline-style variants and uboot for his board-mainlining work; output still needs substantial review before merging.
The AI made a new OBS launcher in about a minute that opens OBS and refreshes and checks all of his sources.
He drops one raw podcast recording into AI. Four skills turn it into an mp3, a transcript, a description on his clipboard, and a pull request on spring.io, with no manual steps.
The AI files his detailed bug reports and his agent pulls the project's new changes daily to check whether his issue is fixed.
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.