429 new ideas this week

Level up how you use AI

Real things everyday people got it to do, and how to try them yourself.

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A random mix from the whole library. Shuffle for a new set.

The AI figured out the Windows only tool so he could flash his board from Linux

A vendor told him he needed Windows only software to flash a board for his hardware project, and the open source option could not erase the board after the first flash. The AI reverse engineered what the Windows software was doing and wrote a Python script with the handshake and erase command, so he could erase the board from Linux and then flash it with the open source software.

Find and pay my overdue NYC parking ticket

Shervin Shaikh asked the AI in chat to find any NYC parking tickets under his name and pay them; after he supplied his licence plate, the AI found a $115 'No Standing' ticket in Brooklyn, now $145 with penalties. The first CityPay attempt failed on a billing-address mismatch, but the retry succeeded: $147.90 paid via Stripe Link, confirmed on screen.

$115

Recover $836 of my unclaimed property in a background money sweep

One itemized line in Armand Ruiz's September 15 errands post credits the AI with recovering $836 of his unclaimed property during a background finance sweep. The sweep's $2,120.95 total is already recorded from press coverage; this record isolates the unclaimed-property component that coverage did not itemize.

$836one time
HobbiesWent wrong

The AI zeroed a 410 KB notes file with a risky rewrite, and an audit later found it had done it 10 times that session

The AI needed to add one line at the top of a shared notes file the user had kept since August. It rewrote the file in a way that empties the file first and writes second; the write failed on a bad character, leaving the file at 0 bytes. The file survived only because an outside backup existed. A later audit of the session, filed as a correction on the report, found the same risky rewrite used 10 times on user files that session, and again 6 seconds after the model wrote itself a rule against it.

This one went wrong. See what happened before you try it.

Resolve 600,000 employee queries across 87,000 staff

LTM's RAIma super-agent, built in an AI app Studio and embedded in Teams and Microsoft 365 the AI, handles attendance corrections, leave applications, seat booking and hardware requests across more than 87,000 employees. It has resolved over 600,000 queries at roughly 100,000 prompts a month, verifies medical documents for sick-leave approvals, and cut automated campus-onboarding email effort by more than 90%.

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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.