> For the complete documentation index, see [llms.txt](https://whitepaper.cortexs.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.cortexs.ai/introduction.md).
# Introduction
In the digital age, the exponential growth of information is both a blessing and a curse. We are surrounded by a constant influx of data from diverse sources like markdown files, PDFs, videos, web pages, and more. This digital content can enrich our knowledge, spark creativity, and fuel productivity—if only we could access and organize it efficiently.
However, the reality is often different. Many professionals, students, researchers, and creatives find themselves drowning in information, struggling to locate the insights they need amidst a sea of unstructured content. Manual indexing and searching through files are not only time-consuming but also inefficient.
Introducing **Cortex AI Agent**—a groundbreaking solution created by Lithosphere founder and Chief Scientist, [King Kasr](https://kasr.me) and developed by [KaJ Labs](https://kajlabs.org). This next-generation AI agent draws inspiration from Tiago Forte’s revolutionary concept commonly known as the "Second Brain". **Cortex AI** redefines how individuals gather, organize, and engage with their personal knowledge, empowering users to enhance learning, boost productivity, and unlock new levels of creativity.
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# 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://whitepaper.cortexs.ai/introduction.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.