Asking for a review after every job gave his company two to three times more five star reviews
His company asks for a review after every job. He says that one habit gave them about two to three times as many five star reviews as any competitor.
A random mix from the whole library. Shuffle for a new set.
His company asks for a review after every job. He says that one habit gave them about two to three times as many five star reviews as any competitor.
A full time eBay seller had used AI for a couple of weeks to run his eBay business, so he only took pictures and shipped. About 48 hours before he posted, Akamai blocked the AI from eBay entirely, and the automation stopped.
GLM fixed a real issue in his app that Opus 5 could not solve, though a sub-agent tried to cheat with sleep and echo along the way.
He used AI to build an analysis of his own Substack posts. It split the posts into themes and pulled together collections, so readers can click through every theme, motif and term in one place.
LLM audited about 100k lines of tests, deleted about 60k useless lines, wrote broader scenario tests, and caught and fixed bugs, in about 2 hours.
Author educator Christopher Kokoski set up a test the AI with a series bible in Google Drive for a mystery series (hero Rudy Relish: seven hard rules including a bad left knee, never touches a gun, no ketchup on the cart). He added the first three chapters of book four and had the AI check each against the bible and all other pages, on a daily scheduled check. Chapters 1-2 were clean; in chapter 3 the AI caught every one of several mistakes he had planted, including one he considered an unfair plant. (Test manuscript on a fresh account, run for a week.)
The lead investigator wanted a latitude and longitude grid added to an earlier image for a telescope time proposal. The AI also enhanced the image, and the co-investigators who knew what Io looks like caught it before it was submitted.
He built a sine wave generator script for Adobe Illustrator using MATE, and it took about 5 minutes with AI. The script is now free for everyone in Astute Manager Pro.
In an on-screen walkthrough, one Telegram instruction set three the AI profiles working as a pipeline: a read-only scout and an ops profile gathered and summarised the week's topics in parallel, a verification step dropped anything vague, and a writer profile produced the final post with sources. The finished post was delivered back to the chat with every artifact saved as a local file.
He ran AI on the task with 6 agents at a time, about 75 agents in total over about 6 days. They produced transcriptions of tens of millions of handwritten images and indexed them all.
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.