Multi-AI Debugging Overview multi-ai-debugging provides systematic debugging workflows using multiple AI models as specialized agents. Based on 2024-2025 best practices for AI-assisted debugging with multi-agent architectures. Purpose : Systematic root cause analysis and fix generation using AI ensemble Pattern : Task-based (6 independent debugging operations) Key Principles (validated by tri-AI research): 1. Multi-Agent Council - Specialized agents debate root causes before consensus 2. Evaluator/Critic Loops - Fix agent + critic agent verify solutions 3. Trace-Aware Analysis - Full executio…