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	9384
title	Implement generic Neo.util.Performance tracker
state	Closed
labels	aiperformancecore
assignees	tobiu
createdAt	Mar 7, 2026, 10:28 PM
updatedAt	Mar 7, 2026, 10:30 PM
githubUrl	https://github.com/neomjs/neo/issues/9384
author	tobiu
commentsCount	1
parentIssue	9380
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Mar 7, 2026, 10:30 PM

Implement generic Neo.util.Performance tracker

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

Closed v12.1.0 aiperformancecore

tobiu commented on Mar 7, 2026, 10:28 PM

This ticket tracks the creation of a generic, lightweight performance tracking utility (Neo.util.Performance).

Goal: Create a Singleton capable of tracking the duration of specific operations across the framework and calculating a rolling average (e.g., Simple Moving Average or Exponential Moving Average) without the overhead of Neo.manager.Base (which extends Collection).

Requirements:

Implement src/util/Performance.mjs.
Methods: markStart(key), markEnd(key), getAverage(key).
Must be zero-allocation on the hot path (e.g., using a fixed-size ring buffer array inside an internal Map).
Ensure methods are sorted alphabetically per project guidelines.

This is a prerequisite sub-task for implementing Dynamic RTT Measurement in the Grid.

tobiu added the ai label on Mar 7, 2026, 10:28 PM

tobiu added the performance label on Mar 7, 2026, 10:28 PM

tobiu added the core label on Mar 7, 2026, 10:28 PM

tobiu added parent issue #9380 on Mar 7, 2026, 10:29 PM

tobiu referenced in commit bb0b2d7 - "feat: Implement Neo.util.Performance tracker (#9384)" on Mar 7, 2026, 10:29 PM

tobiu assigned to @tobiu on Mar 7, 2026, 10:30 PM

tobiu Mar 7, 2026, 10:30 PM

Input from Gemini 3.1 Pro:

✦ I have created the lightweight Neo.util.Performance singleton.

It uses a fast internal Map with fixed-size arrays for zero-allocation moving average tracking, bypassing the overhead of Neo.manager.Base and Collection. The methods have been sorted alphabetically as requested.

Closing this sub-task. We can now proceed with wiring this tracker into VdomLifecycle and ScrollManager in #9382.

tobiu closed this issue on Mar 7, 2026, 10:30 PM