Agentic AI represents a shift from chat-based AI to autonomous agents that accomplish goals. Key characteristics include: planning (breaking goals into subtasks), tool use (calling APIs, running code, browsing web), memory (maintaining context across interactions), and reflection (evaluating and correcting own work). Architectures like ReAct, AutoGPT, and agent frameworks (LangGraph, CrewAI) enable building agents. Agentic workflows combine multiple AI calls with human oversight checkpoints. Applications include: coding assistants that write and test code, research agents that gather and synthesize information, and automation agents that handle business processes. Safety and control remain active research areas.
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Agentic AI
AI systems that can autonomously plan, execute multi-step tasks, and interact with external tools and environments.
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