Using LLM as a judge architecture to optimize multi-agent system prompts and configurations. For now it's achieved through LLM based consensus system that evaluates another LLM output, and based on its performance for a specific task, it's tune the architecture and the prompt e.g. refine the prompt, change the base model to a smaller or cheaper model, etc