Foundation Prior: How LLM Outputs Reshape Bayesian Beliefs
Deriving the Foundation Prior framework from scratch — why synthetic data is not real evidence, the constrained optimization that produces exponential tilting, the trust parameter λ, prompt heterogeneity through mixtures, calibration via real data, and the final posterior — all step by step with one coin example.