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	9394
title	E2E: Validate GridRowScrollPinning against DevIndex Canvas Worker Latency
state	Closed
labels	aitestinggrid
assignees	tobiu
createdAt	Mar 8, 2026, 5:25 PM
updatedAt	Mar 8, 2026, 5:44 PM
githubUrl	https://github.com/neomjs/neo/issues/9394
author	tobiu
commentsCount	1
parentIssue	9380
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Mar 8, 2026, 5:44 PM

E2E: Validate GridRowScrollPinning against DevIndex Canvas Worker Latency

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

Closed v12.1.0 aitestinggrid

tobiu commented on Mar 8, 2026, 5:25 PM

This ticket tracks the E2E validation of the CSS Variable based GridRowScrollPinning architecture against the devindex application.

The Challenge: The devindex app represents the extreme edge of framework latency. Its grid rows contain <canvas> elements managed by an OffscreenCanvas worker, which adds significant processing overhead to the VDOM pipeline compared to the bigData test grid. We need to prove that the 500px optical pinning threshold successfully prevents the "white flash" during massive thumb drags despite this increased latency.

Testing Strategy:

Environment: apps/devindex/index.html
Streaming Wait: The test must explicitly wait for the initial GitHub API data streaming to complete before initiating scroll maneuvers to ensure a stable testing baseline.
Measurement: We will reuse the requestAnimationFrame + getBoundingClientRect visual blanking detector developed in #9392.
Assertion: The grid must record 0 blank frames during a simulated massive scrollbar thumb drag.

tobiu added the ai label on Mar 8, 2026, 5:25 PM

tobiu added the testing label on Mar 8, 2026, 5:25 PM

tobiu added the grid label on Mar 8, 2026, 5:25 PM

tobiu added parent issue #9380 on Mar 8, 2026, 5:25 PM

tobiu referenced in commit 97a2fa2 - "Test: Add DevIndex E2E Validation for GridRowScrollPinning (#9394) on Mar 8, 2026, 5:43 PM

tobiu Mar 8, 2026, 5:44 PM

Input from Gemini 3.1 Pro:

✦ The test/playwright/e2e/GridThumbDragDevIndex.spec.mjs test file has been committed and pushed.

Findings from the DevIndex Playwright Test:

White Flashes: 0 frames. The GridRowScrollPinning addon's CSS Variable strategy (--grid-row-pin-offset) successfully intercepts massive scrollbar thumb drags and mathematically locks the stale rows onto the viewport, preventing the user from staring at a blank screen while the Canvas Worker computes the heavy data load.

Jitter Bounces: 5 frames. As expected, when the 500px "freeze" threshold is engaged, it stops the native scroll. Once the worker catches up and the transform is cleared, the grid snaps the rows to their true locations. This mathematically registers as a "bounce" or "jitter" in the test because the tracking row teleports.

Conclusion on Current State: The optical pinning mechanism works flawlessly to prevent the white flash. The remaining visual artifact (the snap/jitter when healing) is an inherent consequence of choosing to freeze the scroll rather than showing empty space.

Closing this ticket to finalize the baseline. We will now investigate further architectural refinements to address the root latency or healing mechanisms.

tobiu assigned to @tobiu on Mar 8, 2026, 5:44 PM

tobiu closed this issue on Mar 8, 2026, 5:44 PM

tobiu referenced in commit 5fc7737 - "Test: Optimize Playwright E2E Config for Native GPU Acceleration (#9394) on Mar 8, 2026, 6:34 PM