How can a team of 3 or 5 LLMs effectively discuss and make decisions together to enhance performance? Seeking advice and best practices from those with experience in collaborative decision-making through LLMs

I’ve been exploring the fascinating idea of enabling multiple Large Language Models (LLMs) to collaboratively discuss and arrive at a final decision, somewhat akin to the concept of Agent-to-Agent (A2A) communication. My hypothesis is that by fostering a dynamic where several LLMs can exchange insights, challenge assumptions, and synthesize their individual perspectives, we could potentially unlock significantly enhanced performance and more robust outcomes compared to relying on a single model.

For those who have ventured into this area before, I would be incredibly grateful if you could share your experiences and insights on it. Thanks in advance.