AI agents benefit from three components:

1. Planning: This core function of an agent, allows it to break a goal into smaller steps and work on them one by one. Another aspect of their planning is to **self-reflect** on their actions and learn from them. 

The way an agent pulls off self-reflection very much depends on the implementation, but a general outline could be thought of as shown in the image below.

2. Memory: To learn from past mistakes, you must remember them. Memory is the component of storing, and later retrieving information by the agent, to refine its actions.

3. Tool Use: A key differentiating factor between a simple LLM and an AI agent, is their ability to use tools. Using tools can be as simple as calling an API, or using a Python function to read or write some files.