Agentic AI
Agentic AI refers to artificial intelligence systems designed to act toward goals rather than only generate responses. Instead of producing a single answer, an agent can plan, decide among options, take actions (often using tools like search, software, or databases), observe results, and adjust its behavior to reach an
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What “agentic AI” means
Agentic AI refers to artificial intelligence systems designed to act toward goals rather than only generate responses. Instead of producing a single answer, an agent can plan, decide among options, take actions (often using tools like search, software, or databases), observe results, and adjust its behavior to reach an objective. This “sense–plan–act–learn” style loop is a key idea behind agentic systems.
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How it differs from typical AI
Traditional AI often focuses on prediction or generation (e.g., answering questions, translating text). Agentic AI adds an operational layer: it can break a goal into steps, choose actions, manage intermediate states, and handle multi-step tasks. For example, an agent might interpret a request, retrieve relevant information, run calculations, and then draft an outcome—iterating when new information appears.
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Common capabilities and risks
Common capabilities include task decomposition, tool use, workflow automation, and iterative refinement. Risks include incorrect actions, unintended side effects, security vulnerabilities when tools have access to data or systems, and difficulty guaranteeing safety in open-ended environments. Because of this, many deployments emphasize guardrails, permissions, auditing, and human oversight.
Client endpoint
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