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	9454
title	Implement Push-Based WebSocket Integration in Data Pipeline
state	Closed
labels	enhancementaiarchitecturecore
assignees	tobiu
createdAt	Mar 12, 2026, 9:16 PM
updatedAt	Mar 25, 2026, 11:40 AM
githubUrl	https://github.com/neomjs/neo/issues/9454
author	tobiu
commentsCount	1
parentIssue	9449
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Mar 25, 2026, 11:40 AM

Implement Push-Based WebSocket Integration in Data Pipeline

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

Closed v12.1.0 enhancementaiarchitecturecore

tobiu commented on Mar 12, 2026, 9:16 PM

Goal

Natively support server-pushed data streams and Progressive Hydration via WebSockets within the Data Pipeline architecture.

Context

Modern web apps use WebSockets to push data to clients (e.g., real-time dashboards, live task boards). Often, backends push "Operations" or "Deltas" (e.g., { target: 123, changes: { status: 'done' } }) rather than full state objects. Currently, Neo's WebSocket connection handles request/response mapping via mId (Promises), but lacks a robust mechanism for persistent channel subscriptions and routing unsolicited pushes through the shaping pipeline.

Acceptance Criteria

remotes-api.json Enhancement:
- Differentiate between standard RPC methods (Request/Response) and streams (Persistent Subscriptions).
- Allow streams to define their own parser and normalizer configs.
Persistent Subscriptions (manager.rpc.Message):
- Implement logic to handle persistent subscriptions. Instead of a single-use Promise mId, the manager must register a persistent callbackId for a specific stream signature.
- When a WebSocket message matching that stream arrives, it must trigger the registered callback repeatedly.
Delta-Aware Parsing (Progressive Hydration):
- The Pipeline must be able to process stream pushes.
- When a payload arrives via a stream, it enters the Data Worker Pipeline.
- We need the architectural capacity for specialized Parsers (e.g., an Opcode Parser) that can read proprietary backend deltas and translate them into standardized Neo.mjs data commands (e.g., { action: 'update', recordId: '123', data: { status: 'done' } }).
Worker Boundary Routing:
- The shaped data (or parsed Delta) must be sent via IPC back to the App Worker's Pipeline.
- The App Worker Pipeline fires an event (e.g., push or update) that a Store or ViewController can subscribe to.
- A Store receiving a delta should call record.set() on the existing Neo.data.Record to trigger highly localized, surgical VDOM updates.

tobiu added the enhancement label on Mar 12, 2026, 9:16 PM

tobiu added the ai label on Mar 12, 2026, 9:16 PM

tobiu added the architecture label on Mar 12, 2026, 9:16 PM

tobiu added the core label on Mar 12, 2026, 9:16 PM

tobiu added parent issue #9449 on Mar 12, 2026, 9:18 PM

tobiu cross-referenced by #9449 on Mar 12, 2026, 10:00 PM

tobiu assigned to @tobiu on Mar 12, 2026, 10:04 PM

tobiu referenced in commit 8472a3e - "feat: Implement Push-Based WebSocket Integration in Data Pipeline (#9454)" on Mar 25, 2026, 11:39 AM

tobiu Mar 25, 2026, 11:39 AM

Input from Gemini 3.1 Pro:

✦ I have committed the implementation for the WebSocket integration as discussed.

Actions Taken:

src/data/connection/WebSocket.mjs: Added streamCallbacks, registerStream(), and unregisterStream() to support persistent channel subscriptions alongside single-use promises. Updated onMessage to route incoming pushes (data.stream or data.method) to these callbacks.

src/manager/rpc/Api.mjs: Enhanced registerApi() to recognize and store streams defined in remotes-api.json.

src/manager/rpc/Message.mjs: Added onMessageStream() and onMessageStreamUnsubscribe() to orchestrate persistent stream registrations down to the specific WebSocket connection.

src/worker/App.mjs: Added the rpcStreamCallbacks registry and the onRpcStreamData() handler. When the Data Worker forwards pushed data via IPC, the App Worker invokes the correct subscriber callback, completing the push cycle from server to UI.

The foundation is in place. As you mentioned, we should proceed with dedicated unit and e2e testing sessions to verify the Progressive Hydration flow end-to-end.

tobiu closed this issue on Mar 25, 2026, 11:40 AM