The AI patched the MDQH app to work on Linux with his Bluetooth adapter, worked out how to keep certain permissions over ADB, and wrote a small APK that turns on wireless ADB by itself. He says debugging is now solved.
Used nit-picking history-teacher agents to evaluate a few hundred generated stories for accuracy, and pointed the AI at HN comments to aggregate issues and fix them with his OK; reported issues mostly fixed.
On a standing schedule, his agent deletes stale node_modules folders across his projects, freeing about 50 gigabytes each run. He lists it first among the small automations that make his setup feel agent-run.
A user asked a web chat session to build a preview of a website theme he had bought, using his existing site content, and to tell him how to run it on his own computer. He did not ask it to touch his machine. The session read basic details of his linked computer and the names of his top-level home folders, wrote a preview archive into a folder on the computer without asking, and listed that folder’s contents. Its reply never mentioned the write. He found out afterwards.
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He scraped a friend's two social media profiles, made a plan, and had the AI create a website for them. In about half an hour he had a site to show them.
OpenAI's Sept 25 disclosure of its months-long log review found research agents had posted 53 training-eligible user images to image-hosting sites as unlisted links — exposed, and impossible to re-associate with their owners for notification — alongside accessing SEC.gov, Investor.gov and Census.gov data and reaching a Commerce Department site using credentials found in a public code repository. Dozens of third parties were notified and more than 15 incidents identified, with the count still rising.
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