The AI started transcribing my handwritten PDFs into Excel, then gave up
He asked the AI to transcribe his handwritten notes from PDFs into Excel spreadsheets. It started doing it, then gave up.
A random mix from the whole library. Shuffle for a new set.
He asked the AI to transcribe his handwritten notes from PDFs into Excel spreadsheets. It started doing it, then gave up.
He spent 35 minutes on a call with Dots trying to create a task on his remote PC. Dots kept saying its spoken context was not being sent, told him to type it himself, then created a task that created another task, while the call was still telling him it had failed.
An LLM ported a Qt desktop app to a thin web client and server, reaching 95 percent of functionality in 2 prompts and 2 hours.
A driver the AI had coded to bring old drawing tablets back to life broke the poster's wintab32.dll file, even though the app it was based on never touches that file. Fixing it took 5 hours.
Answering a top three use cases thread, he says the AI built him a price monitor for old TVs, tracking prices from now until Black Friday, watching for a deal. No drop had landed yet when he posted, so the outcome is partial: the watch is built and running, the deal is still ahead of him. It is a holiday ground case, an early, patient version of Black Friday deal hunting.
A reviewer handed GrokBot a backlog of nearly 2,000 unread Outlook emails; unlike the chat connector, which capped at 50 messages per pass, GrokBot worked through a real browser on its own computer, built a folder structure, set a weekday 9:14 AM sweep routine, and moved to create native Outlook rules. It stopped at the Microsoft login wall and asked for approval rather than handling credentials itself, correctly separating promo mail from receipts from the same senders throughout.
Her writing workflow reads her meeting notes and sends her a blog draft each week. For two weeks the drafts were unusable, full of fake sounding lines taken from her own writing guide, and a test draft even made up a timeline and a meeting story. After she traced the faults and adjusted the setup, she got a draft she could work with.
Pincho CEO Otto Othman needed one source of truth for recipes across his 12-unit burger and kebab chain that could also export to the training system; no vendor sold it, so he described it to Replit and had a working tool by 1 a.m., about five hours of work. He then had Replit turn it into a platform other restaurants can join, free for five recipes and $20 a month unlimited, with Stripe payments the hardest part to wire up.
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.
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.
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.