Recent discussions in the field of artificial intelligence highlight advancements in the use of large language models (LLMs) for expert prior elicitation and multi-agent consensus. A study showcased an expert-elicitation method for non-parametric joint priors utilizing normalizing flows, emphasizing its significance in predictive modeling. Additionally, research indicates that integrating multiple LLMs can enhance accuracy, achieving a notable 95.6% accuracy rate. This ensemble validation approach aims to improve the reliability of AI systems, particularly for critical applications in sectors such as healthcare and finance, where autonomous deployment has been a challenge due to reliability concerns.