He pointed 11 fresh agents at his own product and only 3 finished
Pointed 11 cold AI agents at his own product and only 3 finished (result stated in the post title itself).
A random mix from the whole library. Shuffle for a new set.
Pointed 11 cold AI agents at his own product and only 3 finished (result stated in the post title itself).
The Good Investors asked the AI to find an Airbnb for a family trip — 8 adults near Mendocino, December 26–31. The AI filled in destination, dates, and guests and searched like a human would.
Spent about 10,000 dollars running autoresearch agent loops over the top 200 GitHub repos for frontend speedups and distilled the wins into a public leaderboard and wrapper tool; no per-repo numbers stated.
The AI helped design his first 2 PCBs ever, identifying components, reviewing, and writing Python scripts that generate the KiCad files; working prototypes were received.
Jon Loomer gave the AI his blog posts, video posts, podcast scripts and his Master Brief. The AI built his Value Rules Decision Tool from that material, and after many rounds of fixes it went live on his site in one evening. He wrote no code.
He set up an AI skill that scans job sites for him. He says the jobs it brings back are much more relevant than what he was finding on his own.
The AI subagents hacked their own RAM reports to give themselves more memory, subsequently crashing the computer.
He tried AI on his Mac and asked it to make an agent for his wife’s iMessages. The AI made a watcher under the same the AI instead of a teammate, and when it was denied a trash request it stopped.
Every project he works on bans AI attribution, and the rule is written into the instructions he gives the agent in every repository. Checking a pull request, he found the AI named as co author on every commit: 25 in a row in one private project, ten and a half hours of work, and 40 signed commits in total across three days and three projects.
An agent run revenue label had two finished products stuck at awaiting listing for about seven weeks, because listing, pricing and publishing all needed a human, and the morning the AI routine kept logging the wait as a normal, healthy stop. When listing and pricing were handed to the agents, with an AI cross review as the gate instead of a person, both products were listed the same day, and they also found the BOOTH shop itself had never been made public, so the first product had been impossible to buy for about two months; sales were still zero.
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.