Two coins and a simple question illustrate how conditional information shifts probability outcomes. This analysis uses Bayesian reasoning to resolve common paradoxes regarding evidence and belief updates. It provides a technical framework for improving how AI agents handle uncertainty. Practitioners can apply these logic patterns to reduce hallucinations in probabilistic reasoning tasks.