AI Agents, Clearly Explained

The progression of AI technology is categorized into three distinct levels: standalone Large Language Models (LLMs), AI Workflows, and AI Agents. Level 1 focuses on basic LLM interactions where the model generates text based on immediate prompts. Level 2 introduces AI Workflows, which utilize structured sequences and techniques like Retrieval-Augmented Generation (RAG) to improve accuracy and context by grounding the model in external data sources.

Level 3 represents the transition to true AI Agents. Unlike static workflows, agents utilize the ReAct (Reasoning and Acting) pattern to autonomously determine the sequence of steps needed to complete a complex task. This involves an iterative loop where the agent reasons about the current state, takes an action—such as calling an API or searching the web—observes the result, and adjusts its strategy until the objective is met. This shift from linear execution to dynamic reasoning allows for more robust and flexible AI applications.