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neomjs
neo
JavaScript2019–2026
neomjs / neo

neo

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.

3Distinct people
38Mentions
0Explicit recommenders
3.3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 5:05:26 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year38 dated mentions

Observed mentions: 2019-12-13 23:15:24 UTC to 2026-09-03 10:23:26 UTC.

01020302019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 30 mentions; 17 submissions, 13 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC514
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC301713
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC110
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC211

What Hacker News says

2 sources
tobiu·Feb 28, 2026Submission

Show HN: DevIndex – Ranking 50k GitHub developers using a static JSON file

Hey HN, I’ve always been frustrated by the lack of an accurate ranking for top open-source contributors on GitHub. The available lists either cap out early or are highly localized, completely missing developers with tens or hundreds of thousands of contributions. So, I built DevIndex to rank the top 50,000 most active developers globally based on their lifetime contributions. From an engineering perspective, the constraint I imposed was: *No backend API.* I wanted to host this entirely on GitHub Pages for free, meaning the browser had to handle all 50,000 data-rich records directly. Here is how we made it work: 1. *The Autonomous Data Factory (Backend):* Because GitHub's API has no "Lifetime Contributions" endpoint, we built a Node.js pipeline running on GitHub Actions. It uses a "Network Walker" spider to traverse the social graph
Read the rest
(to break out of algorithmic filter bubbles) and an Updater that chunks GraphQL queries to prevent 502 timeouts. The pipeline continuously updates a single `users.jsonl` file. *Privacy Note:* We use a "Stealth Star" architecture for opt-outs. If a dev stars our opt-out repo, the pipeline cryptographically verifies them, instantly purges their data, and blocklists them. No emails required. 2. *Engine-Level Streaming (O(1) Memory Parsing):* You can't `JSON.parse()` a 23MB JSONL file without freezing the UI. We built a Stream Proxy using `ReadableStream` and `TextDecoderStream` to parse the NDJSON incrementally, rendering the first 500 users instantly while the rest load in the background. 3. *Turbo Mode & Virtual Fields:* Instantiating 50k JS objects crushes memory. The store holds raw POJOs exactly as parsed. Complex calculated fields (like "Total Commits 2024") use prototype-based getters dynamically generated by a RecordFactory. Adding 60 new data columns adds 0 bytes of memory overhead per record. 4. *The "Fixed-DOM-Order" Grid:* We had to rewrite our underlying UI engine (Neo.mjs). Traditional VDOMs die on massive lists because scrolling triggers thousands of `insertBefore`/`removeChild` mutations. We implemented a strict DOM pool. The VDOM array length never changes. Rows leaving the viewport are recycled in place via hardware-accelerated CSS `translate3d`. A 60fps vertical scroll across 50,000 records generates 0 structural DOM mutations. 5. *Quintuple-Threaded Architecture:* To keep sorting fast and render "Living Sparklines" in the cells, we aggressively split the workload across workers. The Main Thread only applies DOM updates. The App Worker handles the 50k dataset, streaming, and VDOM generation. A dedicated Canvas Worker renders the sparklines independently at 60fps using `OffscreenCanvas`. The entire backend pipeline, streaming UI, and core engine rewrite were completed in one month by myself and my AI agent. Live App (see where you rank): https://neomjs.com/apps/devindex/ Code / 26 Architectural Guides: https://github.com/neomjs/neo/tree/dev/apps/devindex Would love to hear feedback on the architecture, especially from anyone who has tackled "Fat Client" scaling issues or massive GraphQL aggregation!
1 points · Open discussion

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