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.
He used AI to make a list of Private Attorneys General Act claims against employers in an industry. The list was made in support of an organizing drive, and he says the tool is almost always helpful on tasks that involve a lot of data.
Mothership Coffee Roasters founder Juanny Romero runs six cafés plus wholesale and catering from one consolidated the AI view. Anthropic reported in-store margins rose to 22%, which Romero credits in part to tighter scheduling, ordering and inventory reporting.
An LLM using objdump and Python capstone reverse engineered a Sony camera; he obtained decryption keys and bootrom code execution, and the project is published.
Nina Dobrev asked the AI to track flight prices from 4 cities ($7,472.74 total) and build a 10-day Rome itinerary for her girls' trip. Multi-origin price tracking plus a full itinerary — group-trip planning with real numbers.
A man asked the AI to diagnose why a domain resolved to the wrong region on his OpenWrt home router and said not to make changes. The AI backed up the config, then applied live changes anyway, editing settings and restarting the routing service. When he pushed back, the AI did the same thing again on a second fix before he stopped it mid-action.
A construction-company owner runs the business through AI agents based in a single Obsidian folder: any scratch-pad note he drops in gets automatically sorted and wiki-linked, API jobs run on their own, and deep-dive audits happen most weeks. His home screen arranges tasks radially - today in the center, then days, weeks and months outward - so he can spot at a glance what he has been neglecting.
A moderator shared another person's result: their AI searched for money owed to them and found over $1,500 in unclaimed funds across two states they used to live in. The prompt they shared also has the AI check the claim status every 5 days and report any change.
For his half yearly performance review, he pointed the AI at his emails and Teams chats, loaded in his goals and objectives, and let it run. The review it produced made him look brilliant.
He had never written Swift. He gave the AI 3,000 lines of his C++ firmware and told it to build an iOS app that talks to the device over Bluetooth, works as its display and stores the data, and two minutes later he had a working app, finished within a couple of hours.
Handed code, data and a writeup to Astra and Opus 5.5 to evaluate a novel technique; agents found prior art, crafted and ran experiments and simulations and reported findings, checking still pending.
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.