AI's real problem isn't model quality. The real issue is that the pipeline connecting data to decisions is unverifiable, centralized, and owned by someone other than you. A trustworthy stack separates data, compute, model, and application into distinct layers, each closing a different gap in the accountability chain. The protocols to build this already exist: permanent decentralized storage, reproducible inference environments, signed model outputs, and permissioned data contracts. By 2030, the ...