Agentic AI
In plain terms
AI systems that plan and take multi-step actions toward a goal, not just answer.
Going deeper
Agentic AI uses models that can reason, call tools, and chain steps autonomously, deciding what to do next to accomplish a task. It moves from single responses to goal-directed workflows.
Under the hood
Combines an LLM with planning, memory, and tool/function calling in a loop; reliability, error recovery, and guardrails are the hard, unsolved parts.
Examples
AutoGPT-style agents, tool-using assistants, multi-agent workflows, ReAct loops.
Think of it like...
Like the difference between an encyclopedia and an intern: one answers questions, the other figures out the steps and actually gets the task done.