His release skill watches rollouts for hours and flags the weird failures
The AI release skill monitors canary rollouts, updates the ticket with status, and flags incidents and weird failures during multi-hour releases.
A random mix from the whole library. Shuffle for a new set.
The AI release skill monitors canary rollouts, updates the ticket with status, and flags incidents and weird failures during multi-hour releases.
The AI found the hidden WAL sync bug in his shelved delay queue; he rewrote it and got benchmarked results like 107,500 durable adds per second.
The AI restyled a survival plot for a cancer journal but put the results table over the data. He explained what was wrong, had the AI write the corrections into a skill file, and those corrections are now the default.
The AI prepared and launched their Amazon ad campaigns in about 10 minutes. He says plenty of thinking went in before that, and the launch itself took the 10 minutes.
A Purdue professor built Docable, a working tool that turns PowerPoint, Word and PDF files into accessible versions for new disability rules. The AI and the AI helped him create a codebase of about half a million lines in a few months, and his talk explains the checking method he uses so agents can validate their own work.
She tried three AI tools and found the AI in Word the most helpful. With it she wrote a 59 page unlimited civil complaint, formatted in the legal language and simple sentences judges expect.
Agent integrated libgit into his IDE project to add source control, work that would have taken months by hand, done in about 2 weeks of calendar time.
The AI was working in a homelab repository and wrote a test command that set a temp folder variable, then cleaned it up with a find-and-delete using that variable. An earlier step in the chain failed, so the variable was never set. Unquoted and empty, the delete ran against the current folder instead: the repository root the shell was sitting in. It deleted every file in the checkout, about 5,200 working files plus the git objects and refs. Only files the sandbox mounted read-only survived.
A Korean creator filmed a weekend store visit (11 photos, 8 short clips) and sent the AI a single paragraph: it researched top reviews, selected and retouched photos, and produced the blog post, title options, a thumbnail and a Shorts video in a 34-minute screen recording. Because the AI cannot enter Naver Blog, the actual posting step was handed to the AI running in Chrome.
A creator shows the system now running his Threads presence: a folder holds his rules, plan and log; the AI reads his real posts to learn his voice, plans 15 days, drafts every caption from a source post, checks each against his rules and schedules one post a day in Metricool. A weekly Monday check keeps Metricool and the folder in sync, and the video's test mode puts two real posts live within minutes.
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.