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	9236
title	Implement "Quick Star" Opt-In Pipeline
state	Closed
labels	enhancementai
assignees	tobiu
createdAt	Feb 22, 2026, 12:21 AM
updatedAt	Feb 22, 2026, 12:25 AM
githubUrl	https://github.com/neomjs/neo/issues/9236
author	tobiu
commentsCount	1
parentIssue	null
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Feb 22, 2026, 12:25 AM

Implement "Quick Star" Opt-In Pipeline

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

Closed v12.0.0 enhancementai

tobiu commented on Feb 22, 2026, 12:21 AM

Description

Implement the automated pipeline to process "Quick Star" opt-ins from the neomjs/devindex-opt-in repository.

Requirements

Fetch Stargazers: Query the GitHub GraphQL API to fetch the stargazers of the neomjs/devindex-opt-in repository.
Verify Identity: The GitHub API response itself serves as verification that the user starred the repository while logged in.
Handle Blocklist Reversals: If a newly discovered stargazer is currently on the blocklist.json (meaning they previously opted out), remove them from the blocklist.
Update Tracker: Add the newly discovered (and unblocked) usernames to the tracker.json file so the DevIndex updater pipeline can process them.
Deduplication: Ensure users already in tracker.json or users.jsonl are not added again.

Testing

Verify that users who star the repository are successfully added to tracker.json.
Verify that a user on the blocklist is removed from it upon starring the opt-in repo.
Test deduplication logic.

tobiu added the enhancement label on Feb 22, 2026, 12:21 AM

tobiu added the ai label on Feb 22, 2026, 12:21 AM

tobiu assigned to @tobiu on Feb 22, 2026, 12:21 AM

tobiu referenced in commit 798a60a - "feat: Implement Quick Star Opt-In Pipeline (#9236)" on Feb 22, 2026, 12:25 AM

tobiu Feb 22, 2026, 12:25 AM

Input from Gemini 3 Pro:

✦ The "Quick Star" opt-in pipeline has been successfully implemented and tested.

It correctly queries the GitHub API for stargazers of the devindex-opt-in repository.

Users who star the repository are validated implicitly by GitHub.

Users who were previously on the blocklist (from opting out) are seamlessly removed from it upon starring the opt-in repo.

Unblocked and new users are correctly added to the tracker.json file for the updater pipeline to process.

The system correctly deduplicates and ignores users already in the tracker or the active database.

Closing this ticket as completed.

tobiu closed this issue on Feb 22, 2026, 12:25 AM