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+# 🤖 Agents
+
+Agent is composed of [🧩 Components](./components.md) and responsible for executing pipelines and some additional logic. The base class for all agents is `BaseAgent`, it has the necessary logic to collect components and execute protocols.
+
+## Important methods
+
+`BaseAgent` provides two abstract methods needed for any agent to work properly:
+1. `propose_action`: This method is responsible for proposing an action based on the current state of the agent, it returns `ThoughtProcessOutput`.
+2. `execute`: This method is responsible for executing the proposed action, returns `ActionResult`.
+
+## AutoGPT Agent
+
+`Agent` is the main agent provided by AutoGPT. It's a subclass of `BaseAgent`. It has all the [Built-in Components](./built-in-components.md). `Agent` implements the essential abstract methods from `BaseAgent`: `propose_action` and `execute`.
+
+## Building your own Agent
+
+The easiest way to build your own agent is to extend the `Agent` class and add additional components. By doing this you can reuse the existing components and the default logic for executing [⚙️ Protocols](./protocols.md).
+
+```py
+class MyComponent(AgentComponent):
+    pass
+
+class MyAgent(Agent):
+    def __init__(
+        self,
+        settings: AgentSettings,
+        llm_provider: ChatModelProvider,
+        file_storage: FileStorage,
+        legacy_config: Config,
+    ):
+        # Call the parent constructor to bring in the default components
+        super().__init__(settings, llm_provider, file_storage, legacy_config)
+        # Add your custom component
+        self.my_component = MyComponent()
+```
+
+For more customization, you can override the `propose_action` and `execute` or even subclass `BaseAgent` directly. This way you can have full control over the agent's components and behavior. Have a look at the [implementation of Agent](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt/autogpt/agents/agent.py) for more details.