Agentic Prompting represents a paradigm shift in how developers interact with and leverage Large Language Models (LLMs). Moving far beyond single-turn queries or simple Chain-of-Thought (CoT) prompting, agentic approaches empower LLMs to exhibit more autonomous, goal-oriented behavior. Instead of merely generating a response, an agentic LLM is designed to plan, act, observe, reflect, and
