Liquid biopsy results represent probabilistic inferences rather than direct evidence of tumor presence. Ultra-sensitive detection environments inherently increase the risks of false negatives and false positives. Clonal hematopoiesis (CHIP) is a major biological confounder, particularly in ctDNA-based analyses. CTC and EV analyses are also affected by platform-dependent definitions and isolation biases. Threshold setting and cut-off determination have direct clinical consequences and must be carefully justified. AI-based interpretation improves performance but introduces challenges related to transparency and explainability. Therefore, reliability in liquid biopsy depends as much on error control as on detection capability. This chapter focuses on common interpretive pitfalls and strategies to mitigate them. It provides a critical framework for responsible clinical interpretation of liquid biopsy data.