Agentic AI
An AI system that loops over a perceive-plan-act-reflect cycle, calls external tools, and adapts its next step based on prior outputs.
Full definition
Agentic AI refers to LLM-based systems that go beyond a single prompt-response interaction. An agentic system observes its environment (perceive), reasons about what to do (plan), takes an action by calling a tool or API (act), and evaluates the result before deciding the next step (reflect). This loop lets the system handle multi-step tasks, recover from errors, and operate semi-autonomously. Most production agents in 2026 are single-agent systems with a small number of tools and a human-in-the-loop checkpoint. True multi-agent systems remain rare in production because they amplify both cost and failure modes.
Frequently asked
What is agentic AI?
Agentic AI is an LLM that loops, calls tools, and adapts based on prior outputs — as opposed to a single-shot prompt.
Is agentic AI the same as AGI?
No. Agentic AI is a system architecture pattern. AGI is a capability claim. Today's agents are narrow.