Intermediate · Generative AI

AI Agent

Visual diagram · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. An AI system that autonomously plans, uses tools, and takes actions to accomplish goals through iterative reasoning.

Technical Definition

An AI system that autonomously plans, uses tools, and takes actions to accomplish goals through iterative reasoning.

How it works

Agents extend LLMs from passive generators to active problem-solvers. They receive goals, break them into sub-tasks, select and use tools, observe results, and iterate. ReAct combines reasoning with action. Challenges include planning reliability and error recovery.

Visual Explanation (cycle)

User Goal → Plan Sub-tasks → Select Tool → Execute Action → Observe Result → Reflect & Adjust → Complete or Loop

Related Concepts

• Large Language Model (LLM) — A massive neural network trained on vast text corpora to understand and generate human language with remarkable fluency.
• Retrieval-Augmented Generation (RAG) — A technique that enhances LLM responses by retrieving relevant documents from an external knowledge base before generating an answer.
• Prompt Engineering — The art of crafting effective input instructions to guide LLM behavior without changing model weights.