Agentic AI
AI systems designed to operate with high autonomy — planning, executing, and adapting without constant human oversight. Agentic AI emphasizes independent action-taking to accomplish user goals.
Why It Matters
Agentic AI represents the shift from AI as a tool to AI as a collaborator or delegate. It is the fastest-growing paradigm in enterprise AI adoption.
Example
An agentic coding assistant that receives a bug report, reproduces the issue, identifies the root cause, writes a fix, runs tests, and submits a pull request — all autonomously.
Think of it like...
Like a self-driving car versus cruise control — one just maintains speed, the other navigates, makes decisions, and handles unexpected situations independently.
Related Terms
AI Agent
An AI system that can autonomously plan, reason, and take actions to accomplish goals. Unlike simple chatbots, agents can use tools, make decisions, execute multi-step workflows, and adapt their approach based on results.
Multi-Agent System
An architecture where multiple AI agents collaborate, each with specialized roles or capabilities, to accomplish complex tasks that no single agent could handle alone.
Tool Use
The ability of an AI model to interact with external tools, APIs, and systems to accomplish tasks beyond text generation. Tools extend the model's capabilities to include search, calculation, code execution, and more.
Function Calling
A capability where an LLM can generate structured output to invoke specific functions or APIs. The model decides which function to call and what parameters to pass based on the user's request.
Planning
An AI agent's ability to break down complex goals into a sequence of steps and determine the best order of actions to accomplish a task. Planning involves reasoning about dependencies, priorities, and contingencies.