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	7885
title	[Docs] Refine Agent OS Technical Report (Section 2.1 & 4.1)
state	Closed
labels	documentationBlog Postai
assignees	tobiu
createdAt	Nov 23, 2025, 8:21 PM
updatedAt	Nov 23, 2025, 8:22 PM
githubUrl	https://github.com/neomjs/neo/issues/7885
author	tobiu
commentsCount	0
parentIssue	null
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Nov 23, 2025, 8:22 PM

[Docs] Refine Agent OS Technical Report (Section 2.1 & 4.1)

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

Closed v11.10.0 documentationBlog Postai

tobiu commented on Nov 23, 2025, 8:21 PM

Description

Updates the agent-os-technical-report.md blog post draft to correct architectural inaccuracies and update code examples based on recent API changes.

Changes

Section 2.1 (Architecture Diagram):
- Corrected the diagram to show the Agent OS SDK and MCP Server Layer as parallel entry points to the Service Layer.
- Explicitly labeled the underlying data realms:
  - Knowledge Base: ChromaDB (1 Collection)
  - Memory Core: ChromaDB (2 Collections)
  - GitHub Workflow: API & Filesystem
Section 4.1 (Code Example):
- Updated the KB_QueryService example to use the new limit parameter.
- Removed inaccurate claims about token usage for query results.
- Refined comments to focus on "Broad Search & Filtering" as the primary benefit of Code Execution for this use case.

Acceptance Criteria

The architecture diagram correctly reflects the "Service vs. Server" decoupling.
The code example in Section 4.1 is technically accurate and aligns with the current OpenAPI spec.
Misleading claims about token costs for metadata-only queries are removed.

tobiu added the documentation label on Nov 23, 2025, 8:21 PM

tobiu added the Blog Post label on Nov 23, 2025, 8:21 PM

tobiu added the ai label on Nov 23, 2025, 8:21 PM

tobiu assigned to @tobiu on Nov 23, 2025, 8:22 PM

tobiu referenced in commit 57469ef - "[Docs] Refine Agent OS Technical Report (Section 2.1 & 4.1) #7885" on Nov 23, 2025, 8:22 PM

tobiu closed this issue on Nov 23, 2025, 8:22 PM