What does agentic mean?

As of 2025, agentic has become the most popular buzzword in tech. People are talking about agentic UIs, agentic workflows, agentic coding assistants. An agentic AI can break down a task, figure out the steps needed, and execute them autonomously. For example, if you ask an agentic coding assistant to “add user authentication,” it might research your codebase, plan the implementation, write the code, run tests, and fix any issues it finds. All without asking you what to do at each step.

This is different from the previous generation of AI assistants that wait for you to give them each instruction. You tell a non-agentic AI “write this function,” and it writes the function. You tell an agentic AI “build this feature,” and it figures out all the functions it needs to write.

You’ll see this term a lot with Claude Code, which can autonomously explore codebases, plan implementations, write code, run tests, and iterate on solutions. That’s agentic behavior. In fact, the first time I really experienced an agentic system was Claude Code. Previously I was using Copilot in my code editor just for simple auto-complete or function writing tasks. But with Claude, since it can perform all kinds of tasks across the code base, it really could complete large complex tasks by itself.

The flip side is that agentic systems need good judgment about when to act and when to ask for help. The best agentic AIs know their limitations and check in with you when they’re unsure, rather than just powering ahead and potentially making mistakes.

I’ve found that agentic tools are great for tedious tasks where the path is clear but the work is time-consuming. They save me hours on things like refactoring, setting up boilerplate, or fixing linting errors across a codebase.