Stop Asking One AI. Build an LLM Council for Complex Decision-Making 🚀 Standard LLM workflows usually follow a single path: you input a prompt, and a single model provides a single response. For simple tasks, this is efficient. However, for nuanced strategic planning, risk analysis, or complex architectural choices, relying on a single AI perspective introduces bias and blind spots. To solve this, I built LLM Council—an open-source multi-agent debate framework that orchestrates specialized AI personas to stress-test ideas before synthesizing a finalized, objective strategy. Here is a breakdown of the architecture, the technology stack, and how this agentic workflow can be utilized for advanced problem-solving. 🏗️ The Architecture: Multi-Agent Debate & Synthesis Instead of routing a query to a standard chatbot, this project implements a specialized mixture-of-agents (MoA) orchestration pattern.…