AI agent architecture is built on components like environment interaction, memory, decision-making, and feedback loops. Agents learn from continuous input, refine actions, and adapt to changing conditions. The frameworks include reactive, deliberative, and hybrid models, each applied in robotics, chatbots, and enterprise automation to improve task execution.