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	9095
title	Docs: "Streaming Data & Progressive Rendering" Guide
state	Closed
labels	documentationai
assignees	tobiu
createdAt	Feb 10, 2026, 8:32 PM
updatedAt	Feb 10, 2026, 8:50 PM
githubUrl	https://github.com/neomjs/neo/issues/9095
author	tobiu
commentsCount	2
parentIssue	9089
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Feb 10, 2026, 8:50 PM

Docs: "Streaming Data & Progressive Rendering" Guide

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

Closed v12.0.0 documentationai

tobiu commented on Feb 10, 2026, 8:32 PM

Docs: "Streaming Data & Progressive Rendering" Guide

Objective

Create a comprehensive guide in learn/guides/datahandling/Streaming.md explaining the new Streaming Data architecture implemented in Epic #9089.

Content

The guide should cover:

Concept: Why stream? (Time-to-First-Byte vs Time-to-First-Render, Memory O(1)).
Architecture:
- Neo.data.proxy.Stream (App Worker side).
- TextDecoderStream & ReadableStream (Browser API).
- Chunking & Batching (Performance).
Store Integration:
- proxy config vs url.
- Progressive Loading (Events: load firing multiple times).
- Impact on Grids (Scrollbar updates).
Format: JSONL (NDJSON) requirements.
Visuals: Mermaid sequence diagram showing the flow of data from Fetch -> Stream -> Chunk -> Store -> Grid.

Location

File: learn/guides/datahandling/Streaming.md
Tree: Add under Guides -> Data Handling.

Tasks

Create learn/guides/datahandling/Streaming.md.
Update learn/tree.json.
Verify formatting in Portal (optional but good practice).

tobiu added the documentation label on Feb 10, 2026, 8:32 PM

tobiu added the ai label on Feb 10, 2026, 8:32 PM

tobiu added parent issue #9089 on Feb 10, 2026, 8:32 PM

tobiu assigned to @tobiu on Feb 10, 2026, 8:34 PM

tobiu referenced in commit 4af32ac - "docs: Add Streaming Data & Progressive Rendering guide (#9095)" on Feb 10, 2026, 8:40 PM

tobiu Feb 10, 2026, 8:41 PM

Input from Gemini 3 Pro:

✦ I have created the "Streaming Data & Progressive Rendering" guide.

Deliverables

learn/guides/datahandling/Streaming.md: Comprehensive guide covering the problem (TTFR, Memory), the solution (Stream Proxy, Chunking, Progressive Loading), implementation details, and performance benchmarks. Includes a Mermaid sequence diagram.

learn/tree.json: Added the new guide to the navigation tree under "Data Handling".

This completes the documentation requirements for the streaming initiative.

tobiu Feb 10, 2026, 8:49 PM

Input from Gemini 3 Pro:

✦ I have corrected the Mermaid diagram syntax to ensure compatibility with the learning section viewer.

Status

Guide created and verified.

Tree updated.

Syntax polished.

Ready to close.

tobiu closed this issue on Feb 10, 2026, 8:50 PM