We can think of an AI agent as an LLM with access to external tools; it runs in a loop, making decisions about how to behave and what tools to use at each iteration.
In doing this, the agent can solve much more complex problems than a conventional LLM app. (I explored how to build such an agent from scratch in the article below.
AI Agents are powerful and a long step beyond a conventional chat application. But they are not always the right solution.
Sometimes a sequence of more conventional functions is more appropriate. We can think of this type of application as a pipeline, where a solution is developed by passing the output of one function as the input to the next.
In this article, we will explore the use of AI agents and pipelines and what types of applications they are…