# AI Agents

- [Overview](https://docs.usepylon.com/pylon-docs/ai-agents/overview.md): AI Agents can deflect customer questions using content, gather internal context for your team, and take action.
- [Build](https://docs.usepylon.com/pylon-docs/ai-agents/build.md): Build your swarm of AI Agents to help augment your team.
- [Resources](https://docs.usepylon.com/pylon-docs/ai-agents/build/resources.md): Give the Agent the knowledge it needs to operate.
- [Runbooks](https://docs.usepylon.com/pylon-docs/ai-agents/build/runbooks.md): Give your agents manuals to execute complex procedures.
- [Bring Your Own Agent](https://docs.usepylon.com/pylon-docs/ai-agents/build/bring-your-own-agent.md): Bring your own agent to connect into Pylon.
- [Test](https://docs.usepylon.com/pylon-docs/ai-agents/test.md): Testing makes sure you can be confident your AI Agent will behave as you want it to.
- [Deploy](https://docs.usepylon.com/pylon-docs/ai-agents/deploy.md): Unleash your AI Agent!
- [Monitor & Iterate](https://docs.usepylon.com/pylon-docs/ai-agents/monitor-and-iterate.md): Inspect why the AI acted in a certain way, view analytics, and continue to improve your flywheel.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.usepylon.com/pylon-docs/ai-agents.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.