Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
A researcher updating his own old question says he now asks his agent to download the papers his reference manager could not get. The agent works in the browser while he is signed in with his school login, and he clicks through the human checks himself.
Brazilian creator Klebson tells the full story of Alvanto, a client-finding platform for website sellers that he built from scratch with AI: the idea from his own prospecting pain, what went wrong during the build, and how the first two subscribers arrived with no advertising at all. He gave the project a four-month deadline to prove itself and stresses the numbers are small and real — two people paying monthly.
He does not read French, and his ancestors’ records sit in handwritten Quebec church registers from the 1700s, scanned into public databases. Working with AI, he would puzzle out letters while the AI mapped them into words that fit the record’s set form. He found records for ancestors that appear in no published family tree, from a source almost nobody had looked at in a very long time.
He needed to attach a photo from his PC to a text message. After several rounds with AI he had a script that picks a photo on his PC and sends it straight to his phone, which he likes better than going through Google Photos.
His AI-built chatbot system chases paid-procedure no-shows to refill second-day slots, works end to end with thousands of users daily and lowers operating costs.
He spent about 5 minutes picking the mods he wanted for GTA4. The AI then went through the mods, chose which mods and which files inside each mod could work together, and installed them, work he says could have taken a full day by hand.
He set GPT-6 to read tens of thousands of his emails, his writings and his calendar appointments from his recent career. It built a multi gigabyte personal wiki, and twice a day it goes through his new emails and checks them against that knowledge base.
His claim was too small for a lawyer and the insurer had frozen it at $4,430, so he worked it himself with AI holding every letter in order. The agent surfaced six dated contradictions in the adjuster's own letters, including a legal basis for denial that changed three times, and reviewed each of his drafts as opposing counsel before anything was sent. After his letter quoting their own paper back at them, the offers climbed: $6,500, then $8,000, then $8,750, and the insurer accepted his split of the last gap the same morning, at $10,250.
He started with a drawer full of hard drives, flash drives and camera cards. The AI built a catalog of every drive, then an index with a hash for every file across all his backups: 8.1 million files, 3.6 million of them unique, going back about 20 years.
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.