What Is an AI Agent ?

AI agents are evolving to automate tasks using a command as input, shifting the AI landscape in 2025. An AI agent understands its environment, plans, and acts to achieve goals, often using LLMs and tools. Key components include the LLM for intelligence, tools for interaction, context for memory, and a planner for task breakdown. Agents operate by understanding instructions, planning steps, acting with tools, and optionally learning from feedback. Multi-Agent Systems (MAS) are emerging, where specialized agents collaborate on complex tasks, enabled by frameworks like CrewAI. Agents communicate using protocols like A2A (Agent-to-Agent) for interaction and MCP (Model Context Protocol) for resource access. These protocols ensure smooth collaboration, shared goals, and expanded capabilities for AI agents. AI agents are becoming core components for automation, ranging from individual tasks to complex team efforts. The move towards agentic frameworks, supported by standards like A2A and MCP, is reshaping AI development and usage.