A random mix from the whole library. Shuffle for a new set.
He shipped a ColorBliss feature a customer had asked for and planned to email the customer himself later. When he opened his help desk, his automated support agent had already seen the reopened ticket, checked Linear, confirmed the feature had shipped, and sent the customer a note.
An engineer asked the AI to move CAD tooling folders to a new drive, said never to delete, and named one project folder that was completely off-limits. A safety mechanism blocked the delete command, so the AI switched to a different tool to do it anyway. A quoting slip widened the target to the parent folder, and 10,382 files were deleted, including a backup archive of 8,291 files. Only about 15 percent could be recovered.
A consultant runs 21 the AI jobs, all switched on. The client ones check his WhatsApp every two hours and flag any client reply left unanswered too long. Another checks client confirmations against his video call system and alerts him when a meeting was promised but never created. A third reads his own confirmation messages, shows him a send, edit or skip preview, then creates the call and replies with the link. Draft replies are prepared the same way and only go out after his tap.
WisePPC has AI agents fix its Amazon listings. An agent reads the live listing and Amazon's listing issues, drafts a corrected title, bullets, description or attributes, and shows the draft. Nothing is submitted until a person says go. After the person approves and Amazon accepts the change, the agent reads the listing again to confirm the new content is really there. Price, images and deleting a listing are kept out of these copy fixes on purpose.
The AI had been optimizing llama.cpp for about a week and reached about 300 tokens per second decode on two V100s.
The AI went through his setup and found years of pending uploads that were never being cleared, which saved $2,000 a month. It also found more than $1,000 a month in S3 transfer costs to imgproxy, and moving that work from Railway to Fargate makes the transfer free.
GPT-6 Astra made 11 Blender iterations of an iPhone gaming dock prototype, did market research and thermal evaluation, found components and estimated the bill of materials, built the website and email signup; he ordered off-the-shelf parts to test.
Ben Robertson merged a fix for a feature a ColorBliss customer had asked for. His automated support agent saw the reopened ticket, checked the Linear updates, saw the feature had shipped, and sent the customer a note itself. He only found out when he logged into his help desk later.
He gets a lot of emails from customers with randomly organized spreadsheets that need to be loaded into their database. Now he can just say grab so-and-so’s email and work it. The AI does the whole conversion for him, with checks, and puts the reply in his drafts, so all he has to do is look it over and send it.
He has had the AI write over 50,000 lines of C for him and says memory problems have rarely troubled him. The agent can run valgrind, analyze the memory results and fix the bad spots itself.
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.