Understanding AI agents: Construction, behavior, and boundary setting
F5, Thursday, August 21st, 2025
Some folks seem to be conflating LLMs with AI agents. Let's just put that to bed, shall we? While certainly some are 'extending' chatbots to execute tools and call them AI agents, that's an immature approach if you want to harness agents for advanced automation.
Which of course you do, because you recognize that that's one of the most valuable use cases to address the growing operational fatigue caused by hybrid, multicloud complexity.
An AI agent should be a software unit (an application) bounded system that interprets goals, maintains context, and performs actions by invoking tools. It may use a large language model (LLM) to reason about what needs to happen, but the LLM is just one piece of the machinery. The agent is the system.
In practical terms, an AI agent receives a task (explicit or inferred), evaluates it within a contextual boundary, and decides how to act. Such actions can include calling tools, querying systems, or triggering workflows.