Agentic Workflow
An AI system that independently completes multi-step tasks by deciding what action to take next based on current results, without preset instructions for each step.
In Plain English
An agentic workflow is an AI system that acts more like an employee than a tool. Instead of you telling it exactly what to do at each stage, you give it a goal and it figures out the sequence of actions needed to reach it, adjusting course as it learns new information. The AI "agent" evaluates outcomes, decides next steps, and keeps going until the task is complete. This is different from traditional automation, which follows a rigid script regardless of what happens. Agentic workflows require models that can reason, plan, and recover from mistakes.
💡Real-World Example
A cybersecurity analyst gets an alert that suspicious activity was detected on a server. An agentic AI system could autonomously investigate by first checking access logs, then analyzing which accounts logged in, then reviewing what commands those accounts ran, then correlating that with known attack patterns, and finally recommending whether to isolate the server—all without waiting for the human to give each instruction one at a time.
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