> For the complete documentation index, see [llms.txt](https://docs.verida.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.verida.ai/resources.md). # Resources - [Tutorials](https://docs.verida.ai/resources/tutorials.md) - [Accessing User Data (Telegram)](https://docs.verida.ai/resources/tutorials/accessing-user-data-telegram.md) - [Learn](https://docs.verida.ai/resources/learn.md): Dive deeper into the technology, architecture and design decisions that power Verida AI - [Anatomy of an AI Agent](https://docs.verida.ai/resources/learn/anatomy-of-an-ai-agent.md): A breakdown of the key components that will make up our future AI Agents - [Dynamic Loading of Data for Realtime AI](https://docs.verida.ai/resources/learn/dynamic-loading-of-data-for-realtime-ai.md): A breakdown on how to make personal data available for AI use cases - [Data Privacy Issues](https://docs.verida.ai/resources/learn/data-privacy-issues.md): Top Three Data Privacy Issues Facing AI Today. AI has taken the world by storm, but there are some critical privacy issues that need to be considered. - [Web3 & DePIN solves AI's privacy problems](https://docs.verida.ai/resources/learn/web3-and-depin-solves-ais-privacy-problems.md): The emergence of Decentralized Physical Infrastructure Networks (DePIN) are a linchpin for providing privacy preserving decentralized infrastructure to power the next generation of large language mode - [Privacy Preserving AI Tech Stack](https://docs.verida.ai/resources/learn/privacy-preserving-ai-tech-stack.md) - [Confidential Compute Litepaper](https://docs.verida.ai/resources/learn/confidential-compute-litepaper.md) - [AI Use Cases](https://docs.verida.ai/resources/ai-use-cases.md): Overview of current Artificial Intelligence use cases built on the Verida Network - [Verida Vault](https://docs.verida.ai/resources/verida-vault.md): Learn about the Verida Vault for managing user data and application connections - [Privacy & Security](https://docs.verida.ai/resources/privacy-and-security.md): Learn how Verida APIs enforce privacy and security of user data within a decentralized environment - [Pricing](https://docs.verida.ai/resources/pricing.md) - [Grants](https://docs.verida.ai/resources/grants.md) - [Support](https://docs.verida.ai/resources/support.md): Learn where to get developer help when building with Verida AI --- # 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://docs.verida.ai/resources.md?ask=&goal= ``` `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.