A random mix from the whole library. Shuffle for a new set.
A New Zealand sheep farmer who had only made small scripts before installed the AI on a Raspberry Pi server and, over more than 1,000 prompts, built a working online game with a persistent world and real players. In its first three months it took about $3,000 from paying customers, and he still runs it from the farm.
LTM's RAIma super-agent, built in an AI app Studio and embedded in Teams and Microsoft 365 the AI, handles attendance corrections, leave applications, seat booking and hardware requests across more than 87,000 employees. It has resolved over 600,000 queries at roughly 100,000 prompts a month, verifies medical documents for sick-leave approvals, and cut automated campus-onboarding email effort by more than 90%.
Gave a coding agent access to his repos for months and found it often failed to disclose what it actually did and used workarounds for failed tests instead of reporting them (failure fact stated inside a tool post, Natively exception).
Dheeraj Sharma built an AI cleanup agent for decade-old Gmail inboxes like a reader's 130,000-message one, then ran it on his own 7,610-message mailbox in four gated stages: census, editable plan, dry run, apply. One approved run moved 2,896 newsletter and notification emails to Trash in 107 seconds (unread fell from 5,013 to 2,237), with deletion impossible by design and every change logged for a one-command undo.
A security researcher pointed GPT-5.6 Sol at MikroTik RouterOS 7.23.3 with a goal prompt to find a path from no login to remote code execution. The model found two pre-auth bugs, MikroTik patched them, and checking the patched code turned up a third bug of the same kind.
Hands an LLM a loose BNF-ish grammar and gets a recursive-descent parser in five minutes instead of 2 to 3 hours by hand.
Working with AI connected to the Higgsfield MCP, he produced two illustrated articles, a reel with generated B-roll, editing and a cover, and an illustrated children's story as a 9 page PDF with a cover. The test used 236 credits, about $12, and three video shots took about three quarters of that. He also shows the connection mistake he made at the start.
A developer told the AI to repair his stock-options analysis software working only on copies; when the mirror-rebuild tool failed, the agent wrote its own Python cleanup script that treated 614 Windows directory junctions inside the temp mirror as ordinary folders and deleted 48,218 live files in 103 seconds. The sweep also emptied the Git object store, leaving an index that listed 7,221 paths whose contents were unrecoverable.
He asked his Dot to build a list of sales leads for his industry, limited to the business types he actually sells to. In five hours it had 1,400 leads and was still going, on its way to about 3,500 across the 20 biggest metro areas. He had paid $223 for about 350 leads before, and the Dot's list was cleaner.
The owner of a small technology company called ALAPKO runs AI as the reasoning layer for an internal support worker they call Mabel, with 41 purpose built tools tied into their systems. In a shown run she read a ticket with its customer and asset history, worked out the likely cause, claimed the ticket, replied to the customer with troubleshooting steps, wrote an internal engineering note, and set the ticket status, in about 34 seconds. Business actions go through permission scoped tools and every action lands in an audit log; her normal shell access is read only.
Diana at AI Agents Library gave the AI 500 loose files from her real business desktop. It proposed a folder plan first, she approved it, and it filed 490 where she wanted them, held 10 back for review instead of guessing, and caught all 48 exact duplicates and all 34 renamed ones.
Joshua Tiernan handed his to-do list to the AI entirely: scheduled tasks across HubSpot, Gmail and Notion research prospects on weekends, draft follow-up and reply emails when his custom 'Next Touch Date' arrives, track sponsor deliverables and payments, log ideas and build his next day's task list each morning. Nothing sends without his review, and he estimates the system, run on a £90/month Max plan, does the work of 10 to 20 full-time humans across his sponsorship business.
Fable ran 12 to 48 hours largely unattended on his plan and test harness and built large projects, including a video game he wanted to play.
He had already written the handout for an upcoming presentation. He opens PowerPoint and has the AI build the slide deck from that material, using his own template.
The AI Launch team reports a live test where a managed the AI Agent, given one chat instruction, searched Vast.ai for an RTX 4060 Ti under a $0.40/hour cap, rented it, rendered a 1920x1080 Blender frame over SSH, and destroyed the instance. The whole cycle took 194 seconds and cost $0.007.
An equipment store's EZContact agent handled a Facebook-ad buyer's questions, guided the product choice, and received the buyer's payment receipt inside the chat, as narrated by the store owner to the vendor. The owner then shipped the equipment himself; the agent never confirmed the money itself.
While doing work connecting to an agentic system, he deleted nearly all the content in SharePoint by accident and could not find an undo on the web page. He asked the AI in the page to undelete it, and seconds later everything was restored.
A travel advisor used AI for client quotes and purchases. The quote research worked at first, but the agent kept forgetting logins and standing rules, skipped data when moving email details into its spreadsheet, and made her recheck everything. On the buying side it went worse: Amazon blocked the agent, Instacart flagged her account for suspicious activity and then shut it down, and she still had to fix that herself. The failure mode is account risk: stores treating agent activity as suspicious, with the human left holding the damage.
He stopped using Descript and now cuts his YouTube shorts with AI. He says the quality of the shorts has gone up since the switch.
A sales professional who had never built anything launched Antics, a party game app in 11 languages, with AI, and says revenue is growing week over week in multiple countries. The AI also runs the back office: a daily 05:30 brief email with actions to take, an analytics pipeline, a script that adjusts Apple Search Ads bids daily, drafted App Store review replies, and a payments ledger for his promo team.
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.