# The Philosophy: Learning by Doing

Humans learn most effectively through demonstration. Whether it’s tying a shoe, using a new app, or assembling a product, we mimic behavior by watching and doing. Omniminds applies this same paradigm to machine learning, allowing agents to learn by observing real users complete tasks on a screen. This creates a much richer training signal than traditional supervised learning or static datasets.

Instead of relying on labeled data or hard-coded logic, agents begin with context-rich demonstrations that reflect real user flows, decision points, and interface complexity.


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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://omniminds-ai.gitbook.io/whitepaper/6.-demonstration-based-training-system-the-dojo/the-philosophy-learning-by-doing.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.