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	9417
title	Optimize `TreeStore` Hot Paths (Performance)
state	Closed
labels	enhancementaiperformancecore
assignees	tobiu
createdAt	Mar 9, 2026, 4:00 PM
updatedAt	Mar 9, 2026, 4:11 PM
githubUrl	https://github.com/neomjs/neo/issues/9417
author	tobiu
commentsCount	1
parentIssue	9404
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Mar 9, 2026, 4:08 PM

Optimize `TreeStore` Hot Paths (Performance)

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

Closed v12.1.0 enhancementaiperformancecore

tobiu commented on Mar 9, 2026, 4:00 PM

Goal

Maximize the performance of recursive and iteration-heavy operations inside Neo.data.TreeStore by replacing high-overhead functional iterators (Array.prototype.forEach) with optimized for loops.

Context

Tree structures naturally require recursive algorithms to collect descendants (e.g., collectVisibleDescendants). When a user expands a node with thousands of descendants, the overhead of creating a new function execution context for every single forEach callback becomes a measurable bottleneck. While this cannot cause UI stutters (due to the multi-threaded architecture keeping the Main thread free), it can cause a noticeable delay before the VDOM diff is generated and dispatched to the UI.

Acceptance Criteria

Refactor add(): Replace forEach on items and newRoots with for loops.
Refactor collectVisibleDescendants(): Replace forEach on children with a for loop. This is the most critical recursive hot path.
Refactor expand() and collapse(): Replace forEach on children and siblings with for loops.

Dependencies

Depends on the core TreeStore implementation.

tobiu added the enhancement label on Mar 9, 2026, 4:00 PM

tobiu added the ai label on Mar 9, 2026, 4:00 PM

tobiu added the performance label on Mar 9, 2026, 4:00 PM

tobiu added the core label on Mar 9, 2026, 4:00 PM

tobiu added parent issue #9404 on Mar 9, 2026, 4:00 PM

tobiu assigned to @tobiu on Mar 9, 2026, 4:02 PM

tobiu referenced in commit b04627c - "perf: Optimize TreeStore recursive hot paths (#9417) on Mar 9, 2026, 4:07 PM

tobiu Mar 9, 2026, 4:07 PM

Input from Gemini 3.1 Pro:

✦ Replaced all Array.prototype.forEach iterator calls with optimized standard for loops inside TreeStore.mjs.

This eliminates function creation and execution context overhead during recursive tree traversals (collectVisibleDescendants), ensuring O(1) mathematical injection algorithms remain hyper-fast even when expanding folders with thousands of descendants.

Changes pushed to dev.

tobiu closed this issue on Mar 9, 2026, 4:08 PM