Agentic AI
Agents & AutomationAI systems designed to operate with autonomy — planning, reasoning, and executing multi-step tasks with minimal human guidance.
Agentic AI is the design philosophy behind AI agents. Rather than a single prompt-response interaction, agentic systems maintain context across multiple steps, use tools, and make independent decisions to achieve a goal.
The 'agentic' qualifier distinguishes these systems from traditional chatbots. A chatbot answers your question. An agentic system might research your question across 10 sources, synthesize the findings, create a report, and email it to your team — all from a single instruction.
Key components of agentic AI include: planning (breaking goals into subtasks), tool use (calling APIs, browsing the web), memory (retaining context across steps), and reflection (evaluating its own output and correcting course).
Real-World Example
An agent differs from a chatbot in one respect: it takes actions between the prompt and the answer — reading a file, running a command, calling an API — rather than only producing text.
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What is Agentic AI?
AI systems designed to operate with autonomy — planning, reasoning, and executing multi-step tasks with minimal human guidance.
How is Agentic AI used in practice?
An agent differs from a chatbot in one respect: it takes actions between the prompt and the answer — reading a file, running a command, calling an API — rather than only producing text.
What concepts are related to Agentic AI?
Key related concepts include AI Agent, Tool Use (Function Calling), Autonomous Agent, Multi-Agent System. Understanding these together gives a more complete picture of how Agentic AI fits into the AI landscape.