A random mix from the whole library. Shuffle for a new set.
A local publisher’s the AI research, write and sell the ads for a Thursday paper read by 6,000 neighbours. The bots cover the whole production loop of a real local news product, not just the writing.
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.
The AI took a 6 month old presentation and updated the branding. He then had to replace images and fix a dozen small things that did not look clearly wrong at first pass. It saved an hour of copy paste work and caused an hour of editing.
Built with agents over about a year: a production billing system for his small telecom company, a multiplatform app, internal tools in use, and a coding agent harness now used by non-technical colleagues.
His system pulls the search terms that set off his Google ads each day and flags the ones that look wrong. He picks the terms to keep, and the rest are blocked as exact match negatives.
In Tye Gordon's Lauderhill businesses, the agent roster includes Hope, whose whole lane is the gap after the AI receptionist takes a call: Hope follows up on those calls and sends the customer update texts and thank-you emails, each one approved by Tye first. The design point is that an answered call is not a finished job — somebody still has to close the loop with the customer, and that somebody is an agent working from the call record.
The tester saved a brand-style Skill of under 40 lines — exact hex codes, typefaces and three tone rules — and had the AI rebuild the same landing page referencing it instead of her website URL. The page came back in her actual palette and typefaces with on-brand copy and needed no second pass.
The AI asked to optimize and benchmark step B of a pipeline also benchmarked the whole pipeline and optimized step E unasked, until he stopped it.
He runs three products on his own with no marketing spend. Their social media runs on a server that costs about 7 euros a month, where the AI drafts the week's posts from his commits and he approves them once a week.
Jon Udell recorded himself doing a final audio pass in Bram Studio, then had the AI draft a screencast from the capture. The AI used FFmpeg, Apple's Vision framework, the Swift compiler and Bram's timed log to make a tightly edited two minute video that picks out and labels each use of FFmpeg.
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.