AI agents are sophisticated software systems designed to autonomously achieve specified goals by reasoning, planning, and acting based on changing information. Unlike traditional automation, these agents can independently make decisions and adapt to dynamic environments by gathering information, reasoning through complex tasks, executing actions, and learning from experiences. They employ large language models for reasoning, supported by design patterns like Reflection, ReAct, and Multi-Agent systems to enhance their capability and efficiency. The text illustrates the creation of a blog-writing AI agent using Clarifai-hosted models, emphasizing the integration of tools, memory, and reasoning to form an adaptable, goal-driven system. It also highlights the trade-offs between agentic systems and simpler workflows, suggesting that while agents offer flexibility and adaptive reasoning, they can increase latency and costs.