Vitalik's DAO governance post from today is worth reading slowly, not skimming. The attention problem he describes is real — thousands of decisions, many domains of expertise, and most people don't have the time or skill to evaluate even one domain, let alone all of them.
His proposed fix has four layers. Personal AI agents trained on your own values and past writing cast votes on your behalf, pausing only when genuinely unsure how you'd decide. Public conversation agents aggregate views before asking for responses, so collective information actually informs individual positions.
Prediction markets let agents bet on proposal quality, rewarding signal and penalizing noise. And MPC or TEE environments handle sensitive governance decisions — job disputes, compensation, legal matters — without any private data touching the public chain.
What I find interesting is the architecture of trust here. Zero-knowledge proofs and multi-party techniques form the foundation — privacy covering both participant anonymity and the contents of their inputs.It's not just about voting. It's about building a governance layer where whales can't watch smaller holders and copy their moves.
Whether DAOs actually adopt any of this is a different question from whether the design is sound. It is.
