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
Coda One's Agent Skills directory catalogs agentic capabilities across platforms like Claude Code and Cursor.
Related Terms
More in Agents & Automation
FAQ
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?
Coda One's Agent Skills directory catalogs agentic capabilities across platforms like Claude Code and Cursor.
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.