What is the 'Neural Link'?

The Neural Link is a bi-directional bridge that connects AI agents (like Gemini or Claude) directly to the Neo.mjs runtime. It allows agents to 'see' the application's Scene Graph, inspect component state, verify event listeners, and even mutate the running application in real-time. This turns the application into a 'glass box' for AI, enabling autonomous debugging and feature development.

Why is Neo.mjs called an 'Application Engine' instead of a framework?

Traditional frameworks are general-purpose libraries (like a Toyota) that help you organize code, but they compile away into ephemeral DOM nodes. Neo.mjs is a precision-engineered runtime (like an F1 car), similar to Unreal Engine for games. It maintains a persistent 'Scene Graph' of objects in a separate worker thread. These objects retain their identity, state, and relationships, allowing for advanced capabilities like multi-window orchestration, runtime permutation, and deep AI introspection that are impossible with 'melted plastic' DOM-based frameworks.

What is 'Context Engineering'?

Context Engineering is the practice of curating the environment and information flow for AI agents to maximize their autonomy. In Neo.mjs, this is implemented via three Model Context Protocol (MCP) servers: a Knowledge Base for semantic code understanding, a Memory Core for learning from past sessions, and a GitHub Workflow server for project management. This ecosystem allows agents to work as fully integrated members of the development team.

What is 'Object Permanence' in the context of Neo.mjs?

In Neo.mjs, UI components are persistent JavaScript objects living in the App Worker, not just transient rendering results. This 'Object Permanence' means a component (like a Dashboard) maintains its state (scroll position, user input, internal logic) even if it is detached from the DOM or moved to a different browser window. This is the 'Lego Technic' approach versus the 'Duplo' approach of traditional frameworks.

What is an 'Agent Operating System'?

Neo.mjs v11 introduced the concept of an Agent OS, where the platform itself provides the tools and interfaces for AI agents to operate. It combines a standalone, type-safe AI SDK for autonomous 'Code Execution' with the Neural Link for runtime control. This enables agents to monitor, debug, and heal the application autonomously, effectively acting as an operating system for synthetic intelligence.

How does Neo.mjs handle multi-window applications?

Neo.mjs uses shared web workers to run a single application instance across multiple browser windows. All windows share the same application state and data in real-time. Components can even move between windows while retaining their JavaScript instances. This enables desktop-class experiences like multi-window IDEs, browser-based email clients, and multi-screen control rooms.

What makes Neo.mjs different from React, Angular, or Vue?

Neo.mjs is fundamentally different in its architecture: (1) It uses True Multithreading via web workers to prevent UI jank, (2) It is an AI-Native Application Engine with built-in bridges for AI collaboration, and (3) It treats components as persistent objects in a Scene Graph, enabling native multi-window support and runtime permutation.

Frontmatter

id	9602
title	Restructure Learn Portal (tree.json) for AI-Native Onboarding and Engine Positioning
state	Closed
labels	documentationenhancementai
assignees	tobiu
createdAt	Mar 31, 2026, 1:11 AM
updatedAt	Mar 31, 2026, 2:29 AM
githubUrl	https://github.com/neomjs/neo/issues/9602
author	tobiu
commentsCount	1
parentIssue	null
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Mar 31, 2026, 2:29 AM

Restructure Learn Portal (tree.json) for AI-Native Onboarding and Engine Positioning

Name: Neo.mjs Application Engine
Author: Neo.mjs

Closeddocumentationenhancementai

tobiu commented on Mar 31, 2026, 1:11 AM

Problem

The learn/tree.json structure needs an overhaul to position Neo.mjs effectively for AI-Native onboarding and better surface its unique architectural advantages. Previously, AI and MCP documentation was disjointed.

Solution

Consolidated AgentOS Module: Unify the fractured guides/mcp and guides/ai into a top-level AgentOS node. Put fundamental Agent capabilities at the root and encapsulate configurations in an AgentOS/Tooling sub-node.
Restructured Top-Level Flow: Cleaned up the hierarchy spacing and consolidated irrelevant nodes.
Deferred to Separate Tickets: The elevation of specific "Object Permanence" and "JSON First UIs" benefits was deferred. Moving the highly detailed technical guides to the top-level was confusing, so independent concise marketing stubs will be authored for them via future tickets.

tobiu added the documentation label on Mar 31, 2026, 1:11 AM

tobiu added the enhancement label on Mar 31, 2026, 1:11 AM

tobiu added the ai label on Mar 31, 2026, 1:11 AM

tobiu assigned to @tobiu on Mar 31, 2026, 1:13 AM

tobiu referenced in commit 35d1b68 - "docs: Restructure Learn Portal for AI-Native Onboarding (#9602)" on Mar 31, 2026, 2:29 AM

tobiu Mar 31, 2026, 2:29 AM

Input from Gemini 3.1 Pro (Antigravity):

✦ ### Task Completed

successfully restructured tree.json to extract AgentOS features from the generic guides folders.

positioned Neo vs other frameworks inside an Engine vs Frameworks node.

Deferred the elevation of specific Object Permanence and JSON First UIs metrics to separate tickets (#9603, #9604), as moving the 6-page deep-dive technical documents into the top-level Benefits module created a severe hierarchy imbalance.

Commits are pushed and structure validated.

tobiu closed this issue on Mar 31, 2026, 2:29 AM