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	9318
title	Optimize VDom Helper hot paths to reduce GC pressure
state	Closed
labels	enhancementai
assignees	tobiu
createdAt	Feb 26, 2026, 11:03 PM
updatedAt	Feb 26, 2026, 11:06 PM
githubUrl	https://github.com/neomjs/neo/issues/9318
author	tobiu
commentsCount	1
parentIssue	null
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Feb 26, 2026, 11:06 PM

Optimize VDom Helper hot paths to reduce GC pressure

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

Closed v12.0.0 enhancementai

tobiu commented on Feb 26, 2026, 11:03 PM

This ticket continues the GC pressure reduction effort, focusing on the VDOM worker's hot paths (src/vdom/Helper.mjs and src/vdom/VNode.mjs).

The VDom Worker can generate thousands of delta updates. Array allocations and closures inside looping constructs create significant GC pressure.

Changes:

Replaced Object.keys().forEach() and Object.entries().forEach() with for...in loops in Helper.compareAttributes and Helper.createVnode.
Refactored .forEach loops on child arrays to use standard for loops in Helper.createVnodeMap, Helper.findMovedNodes, and Helper.getFragmentPhysicalCount.
Optimized normalizeClassName in VNode.mjs to avoid .filter(Boolean) and .forEach closures.
Converted Object.entries().forEach() to for...in in Helper.updateBatch.

These optimizations will make the VDOM generation and diffing process much lighter on memory allocations.

tobiu added the enhancement label on Feb 26, 2026, 11:03 PM

tobiu added the ai label on Feb 26, 2026, 11:03 PM

tobiu referenced in commit dc13a71 - "perf: Optimize VDom Helper hot paths to reduce GC pressure (#9318)" on Feb 26, 2026, 11:06 PM

tobiu assigned to @tobiu on Feb 26, 2026, 11:06 PM

tobiu Feb 26, 2026, 11:06 PM

Input from Gemini 3.1 Pro:

✦ The optimizations for the VDOM worker hot paths have been implemented and pushed to dev.

Key changes:

Helper.mjs: Replaced Object.keys().forEach and Object.entries().forEach with for...in loops in compareAttributes and createVnode to avoid array allocations and closure overhead.

Helper.mjs: Refactored .forEach on childNodes arrays into for loops in createVnodeMap, findMovedNodes, and getFragmentPhysicalCount.

Helper.mjs: Changed Object.entries().forEach to for...in in updateBatch.

VNode.mjs: Optimized normalizeClassName to use plain for loops instead of .forEach and .filter(Boolean).

Closing this ticket.

tobiu closed this issue on Feb 26, 2026, 11:06 PM