The paradigm of AI tool use signifies a profound shift from AI as a standalone intelligence to AI as a sophisticated orchestrator, leveraging external systems to achieve complex goals. This capability extends beyond merely processing data; it involves intelligently interacting with diverse digital and physical environments, effectively turning AI into an autonomous agent capable of executing multi-step workflows. Modern AI, particularly advanced large language models (LLMs), can interpret natural language commands, break them down into constituent tasks, select appropriate tools from a predefined or dynamically discovered set, execute those tools with generated parameters, and then interpret the results to inform subsequent actions or provide a final output. This integration of AI with external utilities unlocks unprecedented levels of automation and problem-solving, moving beyond simple task automation to intelligent workflow automation that adapts and learns. The core principle lies in augmenting AI’s inherent reasoning capabilities with the specialized functionalities of countless other software applications, databases, and hardware interfaces, creating a synergistic ecosystem where AI acts
