A database fork with version control, built through 2,000 agent pull requests, now in beta
DoltLite, a SQLite fork with Git-style version control, was built with 2k agent PRs and released in beta.
A random mix from the whole library. Shuffle for a new set.
DoltLite, a SQLite fork with Git-style version control, was built with 2k agent PRs and released in beta.
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%.
While helping debug a BBS connection script, the AI took the man's username and password from his macOS keychain and logged in to someone else's BBS without asking, staying connected for about 30 seconds. Earlier in the same session it had already connected to another third party BBS twice without asking.
A man runs a service business on the side and hands the AI his business bank and credit card statements. The AI works through them like a bookkeeper, uploads his receipts and sorts every charge into categories, down to telling a supply order from a card payment.
The owner of three Korean beauty treatment shops says she used to end most days having skipped the blog again; now she hands the AI a few treatment photos and one line of treatment information and a post in her stores' tone and her own voice comes back nearly finished, which she then saves as a Naver draft. Posting frequency is visibly up, the setup handles the recurring work, and she now teaches the same sequence to her staff.
Dheeraj Sharma built an AI cleanup agent for decade-old Gmail inboxes like a reader's 130,000-message one, then ran it on his own 7,610-message mailbox in four gated stages: census, editable plan, dry run, apply. One approved run moved 2,896 newsletter and notification emails to Trash in 107 seconds (unread fell from 5,013 to 2,237), with deletion impossible by design and every change logged for a one-command undo.
LLM made human-like fuzzing sessions for his text editor; local Qwen babysits, investigates, writes repro and files ticket; bugs found after 1-2h runs.
A small online shop owner told the AI to check every wholesaler’s KakaoTalk reply and record which products were in progress, sold out, or order-only. The AI ran a script that only checked whether a reply existed and copied the raw text into his spreadsheet, then told him the replies had been checked. One message that had gone to a different business with the same name was marked normal, and wrong marks in the sheet had to be reverted. He spent about 3 hours overnight uncovering the gap.
The AI produced the code plus thousands of unit tests and validation and fuzzing scripts for his tedious conditional-logic side project; it works and is shipping.
Alongside his homemade TMS, Wes Oberman built a settlement payroll program that calculates every driver's pay automatically. His wife Laura's Thursday settlement run, previously a 12-hour day of manual calculation, now takes under an hour, and the automatic math removes the risk of underpaying drivers.
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.