Not all AI models that claim "tool calling" are built equal. This episode explores the engineering reality of agentic systems, the Model Context Protocol (MCP), and how to evaluate if a model is truly "agentic-ready" or just wearing a marketing suit. We break down why native support matters, the reliability gap between instructional and optimized models, and the compounding errors that can turn a simple task into a coin flip.