An agent built a proof checker, then broke its soundness 5 ways and fixed them
Fable built a minimal proof assistant, then checked its soundness and found and fixed 5 ways it could prove false theorems.
Real things everyday people got it to do, and how to try them yourself.
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Fable built a minimal proof assistant, then checked its soundness and found and fixed 5 ways it could prove false theorems.
A Fast Company reviewer found the AI’s background initiative the most striking part of testing: periodically the agent sent unprompted notifications with prepared reports — how to decrease the electric bill, or how to sell the reviewer's old Tesla for top dollar — without being asked to work on either.
He linked his brand and personal Gmail and Outlook accounts to the AI. The first job he gave it was unsubscribing him from spam, and he says it felt great.
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.
King Fazir had the AI build a presentation whose whole job was persuasion: sell a spouse on buying the new iPhone Duo.
Shipped a RAG customer-service agent for an online seller that sent 1,467 or more replies automatically to real buyers and ran the chat channel unattended.
He had the AI build a blog site out of his own Mastodon posts, and the blog is live. A Python script fetches the posts, tidies them up and pulls threads together into single posts.
Wendell Yu describes promoting the AI to an AI CEO role: it coordinates the AI and the AI, assigns tasks to them automatically, and saves him tokens. It is the second of five first-hand the AI cases in his video.
The AI with Photocraft combined people from two photos of the same location into one photo in 3 tries over 5 minutes, after the AI attempts had changed faces.
His team runs a fuzz framework that drives a Migration Assistant with Playwright, has an LLM judge results, and files issues back into their system.
The AI pursued reimbursement for a disrupted flight and recovered $2,000 for the user.
A contractor onboarded Instinct through a WhatsApp chat that simply asked what he had been putting off; it now prepares his contracting invoices and drafts his outgoing emails - the two admin jobs that used to pile up behind the actual work.
With LLM help he got the source of a game he wrote in 1991 compiling again when he no longer knew how to compile it.
He set up the AI with five helpers for his YouTube work. One scouts what is new every Monday, one helps write scripts, one makes all his thumbnails, one updates his personal brand GitHub repo, and one helps him engage on X.
He had the AI reverse engineer a PlayStation 2 game he had the bytes for. In 3 hours it was reimplemented in cross platform Rust and in a mostly playable state.
Paired with Zapier, the AI checks his spam folder for mail that should not be there; most scans find nothing, but the few real messages it rescues make it worth running. It also uploads and catalogues invoice payments for the finance team, work he used to do by hand.
In a Vox feature on personal agents, entrepreneur Matt Van Horn said his wife sent Instinct a photo of a parking ticket with no instructions at all. The agent, which already had her credit card on file, simply paid it.
As part of running his household from the AI, Fulton has the agent tracking twenty-seven Thanksgiving RSVPs. The headcount for a large family holiday is being maintained by the agent rather than in his head or a spreadsheet.
The speakers on his Linux laptop had never worked. The AI fixed the audio, and he says he could not have done it himself. He now plans to check the code and try to send a patch to the Linux kernel.
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.
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.