# AI Data Agents on Databricks

### *It's like having a highly skilled data engineer who never gets tired, never cuts corners, and understands both your code and your data.* 

## Introduction

Osmos Data Engineer for Databricks is your AI-powered teammate that understands both your **code** and your **data**. Built to work natively in Databricks, it helps you go from **task request to validated changes** quickly, safely, and without the manual overhead of traditional development cycles.

With Osmos Data Engineer, you describe what you want to accomplish — like cleaning up ETL jobs or creating a new table — and it takes care of the rest. It writes and validates the code, prepares scripts for any necessary database changes, and ensures your data model stays in sync with your application logic.

Unlike generic code generators, Osmos Data Engineer is **data-aware**. It works with your data as intelligently as it works with your code, helping you avoid mismatched schemas, broken queries, and surprise production issues.

### Safe by Design

Every task is performed in a dedicated, isolated environment:

* **Code safety**: All work happens in a separate branch before you choose to merge.
* **Data safety**: Osmos creates shallow copies of tables to validate changes without touching production data.
* **Security compliance**: Unity Catalog permissions and workspace access controls are always respected.

This design ensures you maintain complete control over what goes live, while enjoying the speed and consistency of automated execution.

### Why Osmos for Databricks

The rapid growth of AI-assisted coding tools has transformed developer productivity. But data engineers need more than just code generation — they need tools that are fully aware of **data context** and can manage both code and schema evolution seamlessly.

Osmos Data Engineer for Databricks is built for precisely that. It’s the fastest, safest way to transform your ideas into deployed changes, letting you move as quickly as your business demands without sacrificing quality or control.


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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://agenticdocs.osmos.io/ai-data-agents-on-databricks.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.