> For the complete documentation index, see [llms.txt](https://faction-os.gitbook.io/faction-os-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://faction-os.gitbook.io/faction-os-docs/public-website/src/content/blog/introducing-factionos.md). # Introducing FactionOS as local-first mission control FactionOS starts from a simple operating rule: agentic coding work should stay observable on the machine where the work is happening. The product is being shaped as a local-first command surface for operators who run AI coding tools across real repositories. Instead of treating each terminal session as an isolated black box, FactionOS gives the work a shared cockpit: active sessions, status signals, task history, and the surrounding context that helps a human decide when to intervene. The product overview explains that direction in more detail on the [product page](https://github.com/AI-with-Apex-VIP/factionos/tree/main/product/README.md), while the [features page](https://github.com/AI-with-Apex-VIP/factionos/tree/main/features/README.md) breaks the cockpit into concrete surfaces: session visibility, review posture, local event flow, and human-readable state. ### What the public site is for This website is the product front door for FactionOS. It is separate from the guided public demo and from the hosted GitBook documentation. That separation is intentional: the website can explain the product, the demo can show a safe example surface, and the docs can stay focused on practical setup and usage. The first publishing surface focuses on the product story. The [how it works page](https://github.com/AI-with-Apex-VIP/factionos/tree/main/how-it-works/README.md) describes the current local-first flow, while the docs own setup and implementation detail. ### Who it is for FactionOS is being shaped for people who need clearer operating context around agent work: solo operators running several AI-assisted sessions, engineering teams reviewing handoffs, AI platform teams evaluating local boundaries, and founders trying to keep product work legible. The [use cases hub](https://github.com/AI-with-Apex-VIP/factionos/tree/main/use-cases/README.md) keeps those role-specific stories easy to compare. The common need is not another invisible automation layer. It is a cockpit that helps a human see what changed, what is waiting, and what still needs review. ### The product boundary FactionOS is not promising that agent work should be sent to a hosted control plane by default. The local runtime remains the baseline. Optional integrations need explicit boundaries, clear data handling, and documentation before they are presented as product behavior. Security and privacy language follows the same rule. The [security page](https://github.com/AI-with-Apex-VIP/factionos/tree/main/security/README.md) names the local-first default, optional transfer surfaces, and sensitive data boundaries. That is the standard this site will use as it grows: show the cockpit, name the limits, and keep public product language tied to current product posture. Readers who want a visual preview can open the separate [guided demo](https://demo.faction-os.com/). Operators who want setup and usage details can read the [public docs](https://faction-os.gitbook.io/faction-os-docs). Both destinations are external destinations. --- # 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://faction-os.gitbook.io/faction-os-docs/public-website/src/content/blog/introducing-factionos.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.