# Key Concepts

Before diving deeper into Pletor, let's clarify the foundational concepts that power everything you'll build.

### Agents

**Agents are reusable creative systems**. They are designed to handle specific marketing tasks. 

You can use Agents to ideate and experiment freely with AI or as a scalable recipe. Once you've perfected the formula (the right models, brand context, etc.), it becomes a repeatable system that removes all production constraints.

<figure><img src="/files/tk0tyE1F7Fkp1l8PA6Io" alt="" width="563"><figcaption><p>A few agents built by the Pletor team</p></figcaption></figure>

### Studio

**The Studio is where the magic happens and Agents get built.**

Here you can experiment with different nodes, test various AI models, and refine your workflow until it consistently delivers the results you want.

<figure><img src="/files/t4UJlJhi1FDdTVIaw4Sf" alt="" width="563"><figcaption><p>A (very) simple agent in the Studio</p></figcaption></figure>

### Nodes

**Nodes are LEGO blocks for Agents.** Each node performs one specific function: collecting user input or brand context, generating an image or a video, etc.

Connect nodes together, and you've built an agent. No coding required. Just drag, drop, and connect.

<figure><img src="/files/ACA4TJUA5UCVqTQwZxmH" alt="" width="563"><figcaption><p>Common nodes and models</p></figcaption></figure>

### Models

**Models are the AI engines under the hood.** When a node needs to generate an image, write copy, or create a video, it uses an AI model to do the heavy lifting.

Different models excel at different things, see AI model library section.

<figure><img src="/files/6FoSS4RJCCSqk9lRjNOd" alt="" width="375"><figcaption><p>A few model providers available on Pletor</p></figcaption></figure>

**Ready to see these concepts in action?** Head to the [AI Studio](/studio/canvas.md) to start building your first custom agent, or explore our [template agents](/agents/templates.md) to see what's possible.


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# 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.pletor.ai/getting-started/key-concepts.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.