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 team ran an AI pipeline over a usability test of an investment app and saved about half a day of manual analysis. Every claim the AI made about the screen was checked against a video frame, and two claims that did not hold up were left out of the report.
A man says the AI finished a hardware project he had started, working across three areas at once. The AI finished the firmware in Rust, changed some board parts and finalised the board design, sourced the parts that do not come with the board, and wrote all the documentation for the installer, and he judges the result good enough.
Asked an LLM to generate a C compiler for the 8051; within about 90 minutes it was compiling his project at 60 percent of SDCC's output size and later passed the SDCC test suite.
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.
FlipIt's account of Business Insider's reporting describes UX designer Jay Eskenazi feeding his own compiled notes and recommendations into AI during a three-week Europe trip. The AI mapped his points of interest and exported routes into Google Maps, updated afternoon itineraries as plans shifted — accounting for opening hours, ticket availability and real-time events — and surfaced Barcelona festival information not yet fully published in English.
The AI updated his system packages, including Node, Python, uv, OpenSSL and certifi to named new versions, checked a checksum, and checked recent vulnerabilities.
A traveller's the AI checked him in for his flight automatically as soon as check-in opened. It told him his boarding group and sent him his boarding pass, with nothing for him to remember or open.
Gave the AI and the AI performance targets for a port of Dos Navigator, went to bed, and woke up to a fast Swift file manager he now enjoys using, especially for image previews.
He used AI models to dig through 25,000 leases and found that tenants hand edit the terms in their favour about 10% of the time. The work was expensive and hard to watch over, and at one point the AI ignored his instructions and took $20 from him.
Working with two economists, Schwartz's team built an 'AI data editor' with AI: it ported the replication packages of 4,452 papers from five leading journals out of MATLAB, Stata and other commercial tools into open-source code — some 30,000 routines — and checked essentially every verifiable number against the published tables. The work, normally a careful manual job for a journal editor, is written up in an NBER working paper.
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.