What AI Agents Are and How They Work: A Practical Breakdown

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AI agents represent a significant evolution in software development, moving beyond step-by-step instructions to goal-driven autonomous execution. Unlike a standalone large language model that only generates text, an agent wraps the model in a continuous loop and equips it with tools such as APIs, databases, and browsers to take real-world actions. The core cycle — perceive, plan, act, observe, and repeat — allows the agent to recover from errors and chain multiple steps toward completing complex tasks. Every functional agent relies on four key components: a reasoning model, callable tools, memory for context retention, and an orchestration layer that enforces limits and stopping conditions. For larger workflows, multiple specialized agents can be coordinated by an orchestrator, though experts recommend starting with a single agent before splitting responsibilities.

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