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	8908
title	Regression: Big Data Grid filters regenerate data and reset row count
state	Closed
labels	bugairegression
assignees	tobiu
createdAt	Jan 30, 2026, 10:42 AM
updatedAt	Jan 30, 2026, 10:45 AM
githubUrl	https://github.com/neomjs/neo/issues/8908
author	tobiu
commentsCount	1
parentIssue	null
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Jan 30, 2026, 10:45 AM

Regression: Big Data Grid filters regenerate data and reset row count

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

Closed v11.24.0 bugairegression

tobiu commented on Jan 30, 2026, 10:42 AM

Description

In the Big Data Grid example (examples/grid/bigData), filtering causes the entire dataset to be regenerated and reset to the default row count (1000), even if the user had previously loaded a different amount (e.g., 100k).

Root Cause

The MainStore class has reactive configs (amountRows_, amountColumns_) that trigger data generation in their afterSet hooks.

When Collection.filter() runs for the first time, it creates a shadow collection allItems to preserve the unfiltered state. It uses me.constructor (i.e., MainStore) to create this instance.

allItems is instantiated as a MainStore.
The current items (e.g., 100k records) are passed to the constructor.
The amountRows config (defaulting to 1000 in originalConfig) is applied, triggering afterSetAmountRows.
afterSetAmountRows blindly calls this.clear() and this.generateData().
This wipes the 100k preserved items and replaces them with 1000 newly generated random records.
The filter then operates on this incorrect dataset.

Fix

Modify examples/grid/bigData/MainStore.mjs to check for this.sourceId in the data generation hooks. If sourceId is present, it indicates the store is operating as a shadow/linked collection (like allItems), and it should NOT generate its own data or clear existing items.

Impact

examples/grid/bigData/MainStore.mjs

Proposed Changes

Add if (this.sourceId) return; to:

afterSetAmountColumns
afterSetAmountRows

tobiu added the bug label on Jan 30, 2026, 10:42 AM

tobiu added the ai label on Jan 30, 2026, 10:42 AM

tobiu added the regression label on Jan 30, 2026, 10:42 AM

tobiu assigned to @tobiu on Jan 30, 2026, 10:45 AM

tobiu Jan 30, 2026, 10:45 AM

Input from Gemini 3 Pro:

✦ I have applied the fix to examples/grid/bigData/MainStore.mjs. The afterSetAmountRows and afterSetAmountColumns hooks now check for this.sourceId and return early if present. This prevents the shadow collection (allItems) used by the filtering logic from incorrectly regenerating data and resetting the store state.

Changes committed in 2e26baa9f.

tobiu referenced in commit 2e26baa - "fix: Big Data Grid filters regenerate data and reset row count (#8908)" on Jan 30, 2026, 10:45 AM

tobiu closed this issue on Jan 30, 2026, 10:45 AM