Personal Computing 2.0
Short summary
The author argues that as AI models become powerful enough to run locally, we should build a new era of personal computing centered on user data ownership rather than cloud subscriptions and corporate lock-in. This shift would let people control their own computing environments, move between services freely, and reclaim the creative potential that defined early personal computers before the web became dominated by ads and extraction.
- Open AI models running on personal devices could break the lock-in dynamics that destroyed the early web, forcing AI companies to compete on performance and cost rather than trapping users through platform effects.
- Data ownership as the core principle solves privacy problems and enables new capabilities—like instantly finding anything across your digital life—that centralized cloud services can't provide.
- Personal Computing 2.0 should be cross-platform and multi-vendor, letting users mix different AI tools together, script them, and migrate instantly between providers without losing access to their work and memories.
Full summary
The author traces how personal computing went from user-friendly and ad-free in the 1990s to today's bloated mess of subscriptions, notifications, and algorithmic manipulation. The internet started as a liberation—billions of personal websites and free knowledge—but got progressively worse as Big Tech monetized everything, killed blogs, flooded search results with spam, and scraped the entire web to train closed AI systems while simultaneously preventing others from doing the same. The result is what they call a "dead internet" filled with AI-generated garbage. The parallel here is historical: just as cheap processors and memory made desktop computing possible after the mainframe era, cheap compute could now make open AI models ubiquitous enough to break Big Tech's current stranglehold.
The vision of Personal Computing 2.0 starts with one principle—your data belongs to you, not rented from some company that can lock you out or delete your life's work. This means your computing environment should be truly cross-platform and multi-vendor, letting you use different AI tools together, move between providers instantly, and run everything locally on your laptop if you want. The author notes that open-weight models are already good enough that a model on your laptop could control closed AI systems through your browser, forcing these companies to compete on actual merit instead of lock-in tactics. Since your data stays on your machine, privacy problems largely disappear without needing new regulations.
With data under your control, entirely different kinds of computing become possible. The author invokes Google Desktop—a tool that could instantly find anything because it had access to all your files—as proof that this works. Personal Computing 2.0 lets you finally answer questions like what you actually want to build with your data and what your digital life should look like. The emphasis is on personalization: just as people customize their homes differently, everyone should be free to shape their computing environment to match their specific needs rather than fitting into whatever template Apple or Google designed.