Muse Spark 1.3 Max is the first Meta model to surpass OpenAI’s best on Artificial Analysis’ Intelligence Index. https://artificialanalysis.ai/models#intelligence

Worth noting: Claude Fable 5.1 and Mythos 5.1 are Anthropic’s first models to watermark text outputs.

I keep up with HN by reading it daily. My Firefox browser always have 2 pinned tabs at the top most: the front page /news and /ask. I also subscribed to HN Weekly Newsletter (https://buttondown.com/hacker-newsletter/archive/).

I have been building and maintaining a coding harness, with help from the community https://github.com/vinhnx/VTCode. Hope you'll check it out.

The Cordis plugin architecture is interesting

https://github.com/cordiverse/paper

As I understood, Cordis is for architecting functionality as plugins that can be hot-loaded and hot-unloaded (without having to restart the parent app such as VSCode). Cordis looks to be a second-layer extension system within the parent system, e.g. VSCode. I understand that Cordis is not tied to VSCode.

Using memory to track inverses does not scale.

I think the paper is really worth reading for anyone working in software. As far as understand it is a software architecture paradigm where everything is a "plugin", and as plugin, I can plug-it-in and plug-it-out, if I understand it correctly. They called it "revertible effects", where software can strip out live code without a restart or system reboot. They give the example of VS Code, which requires system restarts whenever an extension or plugin needs to be updated. To help myself understand it, I created a quick video, using NotebookLM: https://www.youtube.com/shorts/LtR7DRlZJ0M.

Learn by doing. Even more true nowadays, I think the best way to learn and understand how LLM and advanced topic like agent harness works is by, get your hands dirty and start building one. Trust me, it will pay off, one day.

I have been building a coding agent, VT Code, in my spare time. It's a way of me to self-research and explore how coding agent works in practice by building one. https://github.com/vinhnx/VTCode

This month marks 1 year since I first started self-research and building my own coding agent VT Code [0]. I've been learning and experiment with a lot of things to first adapt myself and to learn about AI native/harness engineering. Thankfully, last month VT Code receives highest amount of contributions from the open-source community.

This month I will be focusing and enhance more long-running horizontal for VT Code such as plan mode, better strengthen tools policy structure and improve its harness as new and existing model grows exponentially. And If you are curious and want to fork it feel free, and welcome, let's build!

[0] https://github.com/vinhnx/VTCode

Small model-facing surface, more responsibility in the harness. I'm exploring that tradeoff in Rust with VT Code: https://github.com/vinhnx/VTCode

I'm building roughly this in Rust: single binary, XDG-native, with Landlock/seccomp, scoped filesystem access, default-deny egress, and policy-based approvals. https://github.com/vinhnx/VTCode