Core Concepts

An overview of the core concepts behind Documentation.AI

Documentation.AI helps you build documentation that stays accurate, readable, and AI-ready. These core concepts give you a clear mental model of how the platform works, why it is AI-native, and how teams write and maintain content using either the web editor or a code editor.

If you want a quick end-to-end setup, see the Quickstart.

AI Native

Being AI native means Documentation.AI uses AI and AI-integrated features throughout the product to support both writers and readers. Structured components remain important, but they are one part of a broader, AI-driven workflow.

• AI agent for writing and maintenance: Helps draft, rewrite, and refine content in the web editor. See AI documentation agent
• AI assistant for readers: Provides context-aware answers sourced from your documentation. See Set up AI assistant.
• On-page AI features: Includes quick actions such as copy helpers and the AI menu for fast explanations. See On-page AI menu.
• MCP server for docs: Enables AI tools to work with your content safely and predictably.
• Structured components: Provide semantic cues that improve AI retrieval and help models understand page structure.
• Additional AI-aware foundations: Includes llms-txt guidance and documentation best practices that make your content easier for models to consume.

AI-native features work together so your documentation becomes easier to write, maintain, and explore.

Two ways to work

Documentation.AI offers two fully synced workflows so every contributor can work in the environment they prefer.

Web editor

The web editor is ideal for non-technical contributors or teams that want a visual, in-browser editing experience.

• Edit content with a WYSIWYG interface.
• Use slash commands to insert components.
• Organise the pages nav bar.
• Use the built-in AI agent to write documentation efficiently.

Code editor

Use the code editor workflow if your team prefers working with local files, git branches, and CI.

• Keep docs versioned alongside your codebase.
• Use your preferred editor, linters, and review tools.
• Commit and merge documentation changes like any other code.
• Ideal for engineering-heavy teams or API reference work.
• Use coding agents such as Cursor or GitHub Copilot or Claude Code with the MCP server to update and maintain docs using AI.

Components: rich, reusable blocks

Components help you structure content consistently and make pages more readable. They also give AI clearer signals about the meaning of your content.

• Explore all components here.
• Use cards, tabs, steps, callouts, and code groups to add structure.
• Combine components to create predictable patterns across your docs.
• Keep content readable while adding hierarchy and clarity.

API documentation and playground

If your product includes an API, Documentation.AI provides a complete workflow for importing, organizing, and testing endpoints.

• Import schemas with OpenAPI Import.
• Structure your reference using Organize API Reference.
• Enable live request testing in the interactive playground.
• Keep your API docs synced by updating openapi.yaml in your repo.

Together, these concepts give you a solid foundation for building documentation that scales with your product and your team.