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Thank you!

Sorry for the confusion, even though the author's names may not have an active record on Scholar. But I would like to share it here because I read the paper, and I find it interesting.

You read the paper? All 459 pages of it? And you missed e.g. this gem on page 257? "[11:23:54] CLAUDE: OPUS 5 — 606 pages, need 194 more. FINAL PUSH. Write these in first person as Logan. MAXIMUM DENSITY:"

I'm sorry.

Sorry, I saw the post-credit title and I thought this was the Author's intended title. I changed it back now.


I've been building VT Code (https://github.com/vinhnx/vtcode), a Rust-based semantic coding agent. Just landed Codex OAuth with PKCE exchange, credentials go into the system keyring.

I build VT Code with Tree-sitter for semantic understanding and OS-native sandboxing. It's still early but I confident it usable. I hope you'll give it a try.


What excites me about the OpenAI + Astral acquisition: Codex CLI, uv, and ruff are all written in Rust. Fast by design, and fully open source.


I think my submission about this post was selected to "second-chance" pool by HN Moderators. Hence it's being shown again. Thanks for the heads up!


I think Cognition DeepWiki's or Google CodeWiki's code map does generated a architecture map (Mermaid style). Eg: https://deepwiki.com/openai/codex#project-purpose-and-archit...


Thanks for recommending these tools; very helpful!

https://codewiki.google/github.com/openai/codex


You're welcome!


This month, I'm working on VT Code, a terminal-native coding agent I've been building in Rust (https://github.com/vinhnx/vtcode).

This month I'm focusing on long-pending TODO items: self-benchmarking with Terminal bench (https://www.tbench.ai/), fuzzing the security parsers (it executes shell commands, so the threat model is real), normalizing extended thinking traces across providers, and improving the agent UI/UX and TUI components and harness.


I listen to a lots of podcast.

Currently here is my pinned favorites ones:

Practical AI

Grit

Wenbin Fang's Podcast Playlist (Founder of https://www.listennotes.com/)

The Gradient: Perspectives on AI

Latent Space: The AI Engineer Podcast

The Empty Bow

Hacker News Recap

Dwarkesh Podcast

Machine Learning Street Talk (MLST)

Interconnects

Talk Python To Me

Training Data

---

My podcast collection (opml file format). Exported from Overcast.

Feel free to import to your podcast app of choice. https://github.com/vinhnx/podcasts


This research paper "Mercury: Ultra-Fast Language Models Based on Diffusion" from last year (2025)

https://arxiv.org/pdf/2506.17298


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