> For the complete documentation index, see [llms.txt](https://sniveler-code.gitbook.io/dots/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://sniveler-code.gitbook.io/dots/project-ai-behavior-architect/section-1/welcome-to-ai-behavior-architect.md).

# 👋Welcome to AI Behavior Architect

**AI Behavior Architect** is a visual scripting tool and runtime framework designed from the ground up for Unity's **Data-Oriented Technology Stack (DOTS)** and the **Entity Component System (ECS)**.

> 💡 **The DOTS Challenge**\
> While there are many Behavior Tree solutions available for Unity, most are built around object-oriented `MonoBehaviour` workflows. Attempting to force those object-oriented trees into an ECS environment often results in heavy memory allocations (Garbage Collection), thread-safety issues, and lost performance.

AI Behavior Architect solves this by bridging the gap between designer-friendly visual scripting and hardcore developer performance.

#### 🎯 Who is this for?

* 🎨 **For Designers:** A clean, intuitive node-based editor right inside Unity. Design AI logic, manage sub-trees, configure blackboards, and watch visual debugging in real-time—all without touching code.
* 💻 **For Programmers:** A robust backend that takes that visual graph and uses a custom code-generator to automatically write highly optimized, Burst-compiled `ISystem` and `IJobChunk` C# scripts.

You get the rapid iteration of visual scripting with the extreme runtime performance of pure DOTS code.

#### ✨ Core Features at a Glance

* **100% DOTS Native:** Executes entirely inside Burst-compiled jobs.
* **Zero-GC Allocations:** No runtime garbage collection. Memory is handled strictly via unmanaged buffers and Blob Assets.
* **Auto-Code Generation:** Click "Compile" and watch the framework generate optimized backend systems for you automatically.
* **Advanced Spatial Queries:** Built-in spatial hashing nodes to easily find entities (nearest, random, etc.) without writing complex math.
* **Parallel Execution:** Native support for evaluating multiple nodes simultaneously.


---

# 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 dynamically by asking a question.

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

```
GET https://sniveler-code.gitbook.io/dots/project-ai-behavior-architect/section-1/welcome-to-ai-behavior-architect.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.
