When relying on human feedback for GenAI prompt optimization, several potential biases and limitations may arise. One common bias is the subjectivity of human evaluations, as individuals may have different preferences, perspectives, and levels of expertise that can influence their assessments of AI-generated responses. This subjectivity can lead to inconsistencies in feedback and hinder the effectiveness of prompt optimization efforts. Additionally, there is a risk of cognitive biases, such as confirmation bias or anchoring bias, influencing how humans perceive and evaluate the AI outputs, potentially leading to skewed feedback. Moreover, the limited sample size of human evaluators in studies like the one described can introduce sampling bias and affect the generalizability of the findings. Furthermore, there may be challenges in effectively capturing and interpreting qualitative feedback from humans, as it can be complex and nuanced, requiring careful analysis to extract actionable insights for prompt optimization.