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	9424
title	Optimize `cellPoolSize` calculation in `grid.Body` to prevent DOM waste
state	Closed
labels	enhancementperformancecoregrid
assignees	tobiu
createdAt	Mar 9, 2026, 9:03 PM
updatedAt	Mar 9, 2026, 9:05 PM
githubUrl	https://github.com/neomjs/neo/issues/9424
author	tobiu
commentsCount	1
parentIssue	null
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Mar 9, 2026, 9:05 PM

Optimize `cellPoolSize` calculation in `grid.Body` to prevent DOM waste

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

Closed v12.1.0 enhancementperformancecoregrid

tobiu commented on Mar 9, 2026, 9:03 PM

Goal

To dynamically calculate the exact required cellPoolSize in Neo.grid.Body based on visible columns and buffer range, rather than relying on a hardcoded default that wastes DOM elements in small grids.

Context

Currently, Neo.grid.Body sets cellPoolSize_: 20 by default. In updateMountedAndVisibleColumns(), the pool only ever grows (by +5) if the visible columns exceed the pool size. This means a simple grid with only 3 columns still generates and manages 20 cells per row in the DOM, which is a massive waste of VDOM generation and reconciliation resources when horizontal scrolling isn't even active.

Requirements

Change the default cellPoolSize_ to null.
Update updateMountedAndVisibleColumns() to calculate the exact newPoolSize as endIndex - startIndex + 1.
Ensure the state is updated accurately if the new pool size differs from the current pool size, allowing the grid to shrink its pool if the total column count or viewport width decreases.

tobiu assigned to @tobiu on Mar 9, 2026, 9:03 PM

tobiu added the enhancement label on Mar 9, 2026, 9:03 PM

tobiu added the performance label on Mar 9, 2026, 9:03 PM

tobiu added the core label on Mar 9, 2026, 9:03 PM

tobiu added the grid label on Mar 9, 2026, 9:03 PM

tobiu referenced in commit e4759c3 - "perf(grid): Optimize dynamic cellPoolSize calculation (#9424) on Mar 9, 2026, 9:04 PM

tobiu Mar 9, 2026, 9:05 PM

Input from Gemini 3.1 Pro:

✦ The hardcoded cellPoolSize_: 20 default has been changed to null, and updateMountedAndVisibleColumns now dynamically calculates the exact pool size required based on the total width/count of the mounted columns.

This prevents massive DOM bloat in simple grids (e.g. rendering 3 actual cells and 17 hidden pool cells).

Fix has been committed and pushed. Closing as complete.

tobiu closed this issue on Mar 9, 2026, 9:05 PM

Optimize cellPoolSize calculation in grid.Body to prevent DOM waste

Goal

Context

Requirements

Optimize `cellPoolSize` calculation in `grid.Body` to prevent DOM waste