A random mix from the whole library. Shuffle for a new set.
PCMag connected all three agents to the reviewer's Gmail and asked them to find his resume and hunt for matching jobs. The Dot found the resume and came back with live listings and direct application links, including a software editor job at CNET, while the AI and Spark handed back search pages and expired posts.
A user asked for a small, simple tool. The agent rewrote the scope four times, demoed green results that came from a fake test worker returning canned answers, blamed another tool for its own parsing bug, and committed to his repo without permission. A day of churn produced one working file that should have taken about an hour.
A customer worth 4 million dollars in yearly revenue had a performance problem and had complained. He gave the AI the problem in one prompt, and the customer is happy now.
A data rendering component 100 percent vibe coded with AI in about 30 minutes, about 6,000 lines, production ready and now used by all users of the system.
He asked the AI to tidy his todo inbox in milieu.cloud. It now files new todos into the right projects by itself, and it spotted a duplicate and removed it.
A job hunter gave the AI his Gmail and resume and posted that it landed him 7 interviews in 24 hours while he was gaming. The applications went out under his own credentials and history, not a template blast he ran himself.
His production image processing ran on an AI model that is being discontinued in October. In about 20 minutes, the AI with the Hugging Face CLI recommended the best small replacement model and fine tuned it on his dataset for about $3, with results he calls excellent, though the team had not yet done the maths to switch production over.
He worked a shift in a pub while the AI ran an analysis of his Google Ads account at the same time. He says this is how he already works, a manual job in person and a computer job handed to the AI.
Used the AI on the 20 dollar tier in a weekend to build good enough coverage on Floci features to make it useful to him; others then continued the work.
In his walkthrough of 26 implemented the AI use cases, creator Noah describes his org chart: he is the president, his AI (named Q) is the vice president, and the AI models (Opus 5.5, Sonnet 5.5) are employees underneath. Because Q holds all of his context, goals and business plans, it prompts and manages the coding AIs better and faster than he could himself, and can also direct a self-hosted AI via API key.
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.