A random mix from the whole library. Shuffle for a new set.
Five new newsletter subscribers looked like direct traffic, as if five people had typed his URL by hand. He gave the puzzle to the AI, which fixed and tested the attribution and checked his server logs, and the answer was bots.
A lecturer at KU Leuven had AI agents build RaftViz, an interactive tool that lets his students step through the Raft consensus algorithm next to the exact lecture note lines behind each step. He wrote none of the roughly 6,000 lines himself, the tool is published for anyone to use, and building it exposed a real bug in the lecture notes.
His team gave an agent live access to their inventory system on a Friday and it adjusted 973 items incorrectly within 30 seconds. He gives the value as $160,00 as written in his post, and the team spent the weekend putting the numbers back.
An HVAC company owner who runs several small businesses counted 27 active AI agents and 36 routines, 26 of them scheduled, working across his companies: pulling statements, filing invoices, updating sales and cost sheets, flagging overdue maintenance and tracking renewal dates. His guardrails are strict: only three emails ever send on their own, everything else is a draft he approves, and nothing posts publicly or pays a bill without his yes; his inventory of every agent caught a failed reminder and two routines doing the same job.
Had the AI build an open-source source control system, benchmarked on a 100k-file monorepo as 12x faster sparse checkout and 82x higher concurrent land throughput than git.
Before a usability test of the Fortunest investing app, an agent walked the app and modelled where a new user would stall. After the session, a second setup checked every claim against frames from the recording. Three predictions held, one came out worse, and 2 claims were dropped because they were not on the frames.
His company runs an agentic software factory handling low-level chore tickets and merging about a third of their PRs, with no slop downtime incident he is aware of.
A developer asked why a local tool would not open. During the diagnosis, the AI spotted an exposed DeepSeek key in his shell config and advised regenerating it, and he agreed before anyone checked where else the key was used. The same key powered the AI chat in his live production app, which broke. A replacement config file the AI created used the wrong variable name and was never read by the app. He paid $40 in an AI app credit to get the damage diagnosed and repaired.
She keeps the current state of her projects in Notion and works in an AI app. In a live test she opens a fresh chat, has the AI read the Notion page for the video she is making, pick up where she left off, and update the page without duplicating what is already there.
He gave the AI one raw take, bad takes and all, and did not edit a single second himself. The AI did the color grade, the titles, and captions on every word.
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.