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	9058
title	Feat: DevRank Location Normalizer & Data Enrichment
state	Closed
labels	enhancementaifeature
assignees	tobiu
createdAt	Feb 8, 2026, 10:02 PM
updatedAt	Feb 8, 2026, 10:11 PM
githubUrl	https://github.com/neomjs/neo/issues/9058
author	tobiu
commentsCount	1
parentIssue	8930
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Feb 8, 2026, 10:11 PM

Feat: DevRank Location Normalizer & Data Enrichment

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

Closed v12.0.0 enhancementaifeature

tobiu commented on Feb 8, 2026, 10:02 PM

To improve the filtering capabilities of the DevRank grid, we need to normalize the location data from GitHub. GitHub's location field is free-text and inconsistent (e.g., "Munich", "München", "Bavaria, DE").

This task involves:

Creating DevRank.services.LocationNormalizer: A new singleton service that maps raw location strings to ISO 3166-1 Alpha-2 country codes (e.g., "DE", "US") using Intl.DisplayNames, a regex dictionary for common variations, and a city mapping. It should also provide a flag emoji lookup.
** integrating into DevRank.services.Updater**: Update the fetchUserData method to use the LocationNormalizer. The user data object should now include:
- country_code: The normalized ISO code (for filtering).
- country_flag: The emoji flag (for UI display).
- location: The original raw text (preserved for display).

This enables robust "Sovereign Tech" filtering (e.g., "Top Developers in Germany").

tobiu added the enhancement label on Feb 8, 2026, 10:02 PM

tobiu added the ai label on Feb 8, 2026, 10:02 PM

tobiu added the feature label on Feb 8, 2026, 10:02 PM

tobiu assigned to @tobiu on Feb 8, 2026, 10:02 PM

tobiu added parent issue #8930 on Feb 8, 2026, 10:03 PM

tobiu referenced in commit 0ffa638 - "feat: DevRank Location Normalizer & Data Enrichment (#9058)" on Feb 8, 2026, 10:10 PM

tobiu Feb 8, 2026, 10:11 PM

Input from Gemini 3 Pro:

✦ Implementation Note: Flag Data Strategy

We have explicitly decided NOT to store a country_flag field (neither emoji nor URL) in the backend users.json dataset.

Reasoning:

Payload Optimization: The users.json file is fetched by the client. Minimizing its size is critical. Storing a 2-character ISO country_code is significantly more efficient than storing full URLs or base64 strings for every user.

Client-Side Rendering: The frontend component Neo.component.CountryFlag is already capable of resolving the correct flag asset based purely on the country_code / location value.

Data Hygiene: Separating data (ISO code) from presentation (Flag asset) adheres to better architectural principles.

tobiu closed this issue on Feb 8, 2026, 10:11 PM