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.

Shuffle again

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

Port 430,000 lines of TypeScript to Rust with coding agents

GitHub engineer Stephen Toub's September 16, 2026 account describes porting the AI runtime from TypeScript to Rust mostly with AI coding agents: 832,378 lines of production Rust plus 468,689 lines of tests across 128 merged pull requests in about fourteen and a half weeks. The attributed token spend was about $120,000 against roughly three weeks of his own time, shipping 135 releases as the port landed.

WorkNew

My news site now uses Jev to pick stories and the bill stayed flat

He runs Qood News. When the AI 2.5 was retired, moving to the AI 3.1 would have tripled his AI bill, so a decision model called Jev now decides what counts as good news and costs stay about the same. In testing Jev approved 39 of 110 stories while the AI approved 53, mostly dropping filler.

Check all 124 scheduled jobs in my church's database and tell me what broke

Jay Kranda, the Innovative Tech Pastor at Saddleback Church, has the AI check the church's Rock RMS people-management database every Monday and Thursday at 5am. It reviews all 124 scheduled jobs in the system and reports back in plain English which ones are erroring, so problems surface before Sunday instead of during it.

Ship one secret feature at 4am while I sleep

As an experiment, the founder told his project-manager bot to ship one secret feature to PromptBase at 4am and deploy it while he slept - the only rule was that it had to benefit the site. Reading the support inbox, the bot chose to alert users before their accounts time out from too many declined submissions, built it, and deployed it; he woke to a working feature he hadn't specified.

WorkWent wrong

I let Astra run a software factory for 35 hours. It built nothing of value.

Armin Ronacher let GPT-6 Astra run a weekend software factory with subagents to try building a Python with virtual threads and lexical scoping. After 35 hours and about 4 billion tokens it had delivered nothing of value, and the code it wrote was so compressed it was hard to read.

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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.