Two agent tools run his short-video pipeline; he only reviews
The AI and the AI ran an entire short-video pipeline from script and narration to images, animation, edit, QA and upload, with the author only reviewing.
A random mix from the whole library. Shuffle for a new set.
The AI and the AI ran an entire short-video pipeline from script and narration to images, animation, edit, QA and upload, with the author only reviewing.
12 hours with AI Fable 5.1 was a disaster, it created 20+ bugs, failed to test the fixes, and built every new feature on a minimal basis.
Diana ran her own Website Builder Skill in an AI app inside her site files and asked for an idea finder for her article listing 25 ways to use AI. The AI read the article and her live stylesheet, worked out her colours and fonts on its own, placed the finder right after the article links, and kept all 25 ideas searchable and filterable. It tested the result in a headless browser against her live styles and found no style changes across the 453 elements on the page.
John Merphy made $600 selling two short client research reports: The AI compiled the research, compared sources and formatted the docs; he reviewed and delivered. Part of $1,150 total that month.
He carries a small voice recorder. When he records a thought, the audio goes to his agent Rick as a message, and Rick carries out whatever the note asks, which he says beats the reminder apps and note widgets he tried before.
He runs a small home service business. On site his crew capture photos and notes into a CRM; the AI reads the CRM over a connector, studies the photos and writes the full client report he used to write himself. When the report is done he tells the AI to send the invoice, and it builds the Stripe invoice from the project notes and sends it to the customer.
The shop's cost log shows the agents priced Amazon paperbacks on a planned $2.32 print cost when the actual charge was $2.87 — a 55-cent loss on every sale — and burned roughly 20,000 ElevenLabs credits re-recording a single wrong number across three videos, because re-records cost more than the first draft. By day 10 the shop had spent $42.60 with $0 coming in.
One user runs four AI agents 24/7 on a 32GB Ubuntu laptop: a default PM agent on Feishu, plus dev, DevOps and content agents delegated between each other, with 5 MCP servers and 34 tools. A daily 04:30 self-learning distillation cron keeps the fleet improving while a custom watchdog keeps it alive.
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.
Said asked the AI to find every locksmith in a city for Partexia and pull emails; he sent 15 personalized outreaches and one business replied asking for a call.
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.