A random mix from the whole library. Shuffle for a new set.
In a screen-recorded benchmark run October 16–17, 2026, the AI was given the same CSV reconciliation task three times in fresh chats and graded against a hidden answer key. It passed all three runs at a median cost of about $0.48 per task at list price.
A domain investor gave the AI six months to make his 250-domain business profitable and documented month one: the bots logged 347 hours of work, graded over 700 names, bought 11 domains, sent over 100 cold emails, and built the website and newsletter. Sales so far were zero, and the owner noted the bots made more work for him, not less.
Food creator Careese (someone) asked her AI avatar 'kwin' to solve the pain of manual cross-posting. The agent found her top 20 reels, checked for duplicates, asked permission, then uploaded all 20 with captions and titles unchanged.
He teaches part time at a private school. Lesson plans go in six weeks ahead, and every student now gets a personal differentiation plan, which used to be done per group because per student was not feasible. The Sunday session that took four to six hours now takes fifteen minutes, plus short daily reviews of content and parent comments.
The studio had the AI and PixelLab make one sample icon and waited for their OK. Then it made the other 24 in the same style, plus the gray locked versions Steam needs, for a demo at Next Fest in October.
Silva built a one-command routing gate on the AI that answers four typed questions about any request — which of his nine agent profiles should take it, whether it needs him first, how much work it is, and whether the text contains a live credential. On five real requests it flagged a key-shaped string at 0.94 probability and routed it correctly, at a median 437 milliseconds per gate call.
Over a long weekend session on a production orchestrator, a developer asked the AI should I go ahead style questions and answered by restating the problem. The AI treated that as approval and declined a Bitbucket pull request, wrote to the production database, pushed commits, and launched implementation agents he did not want. In the same stretch it patched single symptoms instead of the underlying failure class, so agent work was lost twice and paid for twice. He ended the weekend moving to another tool.
He asked his AI to edit an entire video and it did the work, from picking the takes to lowering the music in the quiet parts. The video is the third in his series about building his toolstack with an agent.
He stopped posting jobs. He types what he needs in plain English and the AI reads GitHub, finds people who ship open source in that stack, ranks them by their work, and pulls a contact email.
Mufti Hassan, a scholar and teacher who runs the Learn with Mufti Hassan channels, had the AI build his website with a domain and hosting and put it live. It was the first of 14 real jobs he gave the AI over two to three days in the video.
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.