> For the complete documentation index, see [llms.txt](https://docs.jetadmin.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.jetadmin.io/ai-agents/run-agents-in-apps-workflows-and-tasks/agents-1.md).

# Using agents

Learn how to use Jetadmin Agents to automate tasks using natural language and LLMs, no coding or complex logic required.

An agent can:

* Handle or delegate tasks based on reasoning from LLM.
* Be triggered through chat, workflows, or directly from other agents.
* Continuously evaluate and improve its own process (the "agentic loop").

With Agents, you can embed AI-driven decision-making directly into your apps, workflows, and automations.

### Accessing Agents

You can set up and access agents in several ways:

* **From Triggers**: Choose *Agent* as an action when configuring triggers.

{% @arcade/embed flowId="qM5YHy90gQHp6vJewhG5" url="<https://app.arcade.software/share/qM5YHy90gQHp6vJewhG5>" %}

* **Search**: Type “Agent Chat” in the component search box and drag it into your page.

{% @arcade/embed flowId="dzyDUvcYhYQSoDLzku7K" url="<https://app.arcade.software/share/dzyDUvcYhYQSoDLzku7K>" %}

* **Left Menu**: In the left-hand menu, click the Agents icon and then select Add Agent.

{% @arcade/embed flowId="2pdlEYxOU9QEVjbWVItM" url="<https://app.arcade.software/share/2pdlEYxOU9QEVjbWVItM>" %}

{% hint style="info" %}

### When to Use Agents

Agents are useful when you need more than simple automation rules. They are best for:

* **Complex workflows** where steps depend on reasoning or context.
* **Customer-facing chatbots** that can pull data from multiple sources.
* **Task delegation** when actions may involve multiple systems or tools.
* **Dynamic decisions** that go beyond pre-defined logic.

If your task is straightforward and always follows the same pattern, a regular workflow or automation may be enough. If it requires flexibility and decision-making, an agent is the better choice.
{% endhint %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

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

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.jetadmin.io/ai-agents/run-agents-in-apps-workflows-and-tasks/agents-1.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.