> For the complete documentation index, see [llms.txt](https://hugs-solutions.gitbook.io/hugs-platform/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap.md).

# The Hugs Roadmap

- [Overview](https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap/overview.md): The six development tracks
- [Curator engine](https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap/curator-engine.md): The base layer, enabling the Curator ToolKit and apps built on top of it
- [Curator ToolKit](https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap/curator-toolkit.md): SaaS platform, allowing users to deploy their own tools on the Curator engine
- [Dashboards](https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap/dashboards.md): Personal dashboards for the various stakeholders in the Curator ecosystem
- [Perpetual Test Apps](https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap/perpetual-test-apps.md): Internally built apps to test the Hugs infrastructure layer
- [Elastic Rewards](https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap/elastic-rewards.md): The automated rewards pool based on smart contracts
- [Advanced Tooling](https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap/advanced-tooling.md): Tools for developers and more complex integrations


---

# 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:

```
GET https://hugs-solutions.gitbook.io/hugs-platform/the-hugs-roadmap.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.