In this thread from September 29, 2026, Ryan Sarver argues that what is today called personal AI is not, in fact, personal. He starts from an incident: Amazon blocked Muse, Meta's assistant, from its shopping site, displaying a message describing the access as an unauthorized agent. Users, customers of both companies, lost a core agent use case, shopping, because of a dispute they had no part in. He sees this as the start of platform wars in which the consumer will be caught in the crossfire.
His central argument concerns the dual-principal problem. An agent hosted by a platform works for the user and for the company that built it, and it is clear which one wins out. He cites Muse's terms, where training on conversations is enabled by default, and Instinct's, which grant a perpetual and irrevocable license covering screenshots and keystrokes. He does not claim these companies are cheating: they disclose what they do. But a personal AI is informationally "maximalist," and it is precisely the one that should least be entrusted to a third party.
He sets out five requirements: owning the agent (open source, data under control, portability), having only a single principal, knowing the contract and being able to inspect its trade-offs, choosing where the agent runs, and having a pleasant product. Silent steering strikes him as more serious here than in search: with an agent, the user delegates and simply wants the outcome, so the steering happens silently through an opaque algorithm. He reports that assistants reportedly cost $3,000 to $7,000 per user per year, against the $20 a month charged, and questions how an advertising-funded company would recoup that subsidy.
His paradox is that ownership can produce the better product: the user hands everything to what they own, memory accumulates, and the most complete access is what drives quality. But OpenClaw feels like Linux; what's needed is an Apple-like experience.
He lays out the five-layer stack: polished clients; a harness with connectors, approvals, and a log; memory readable in markdown, in the vein of Karpathy's LLM wiki or GBrain; two tiers of models, an open-weights default (about $2 a month versus $46) and a frontier model invoked on demand; and a personal or rented machine (about $10 a month).
He calls for building a productized version of OpenClaw, whose revenue comes solely from the user, who can leave with everything.