Ask HN: What are you working on? (October 2025)

The main pitch is you have minimal dependencies and overheads and can run tests natively on pandas/polars/pyspark/dask/duckdb/etc (thanks to the awesome Narwhals project)

It's mostly there for v1 right now, but kean to add a tiny bit more functionality, and well a lot more docs. Working on something that's automated alongside the test suite, which should keep things reliable and fresh (I'll find out soon enough)

[0] https://github.com/benrutter/wimsey / https://codeberg.org/benrutter/wimsey

It’s an instagram style UI but for scrolling through record releases and snippets, worked on making it responsive as possible with low latency audio playback so you can browse a lot of stuff quickly.

Wrote about it on my blog: https://www.polymonster.co.uk/blog/diig

And GitHub repo: https://github.com/polymonster/diig

> I’m curious though, how significant do you think it is for the agent to have semantic access through Tree-sitter?

For this, I'm really not sure, but since the start of building VT Code. I just had this idea to use tree-sitter to assist the agent to have more (or faster/more precise) semantic understanding of the coding, instead of relying them to figure out themself. For me, naively I think this could help agent to have better language-specific and accurately decision about the workspace (context) that they are working. If not having tree-sitter, I think the agent could eventually figure out itself. For this aspect, I should be research more on this topic. In VT Code, I included 6 language: Go, Python, Rust, TypeScript, Swift... ) via rust-binding crates, mostly when you launch the vtcode agent on any workspace, It will show the main languages in the workspace right way.

> Also what model have you had the most success with ?

I'm having mainly limited-budget so I can only use OpenRouter and utilize its vast amount models support. So that I can prototype quickly, for different use-cases. For VT Code agent, I'm using mainly x-ai/grok-code-fast-1, in my experience, it most suit for building VT Code agent it self because of speeds, and versatile in function calling and have good instruction following. I also have good successes with x-ai/grok-4-fast. I have not tried claude-4.5-sonnet and gpt-5/gpt-5-codex though. I really love to run benchmarks for VT Code to see how it perform in real world coding task, I'm aiming for Aider polygot bench, terminal-bench and swe-bench-lite, it is in my plan for now in my GitHub issues.

For VT Code itself, I instruct it to strictly follow system-prompt, in which I take various inspiration from Anthropic, OpenAI and Devin guide/blogs on how to build coding agent. But, for a model-agnostic agent, the capability to support multi providers and multi models is a challenge. For this I think I need help. I'm fortunately to have support from open-source community suggesting me to use zig, I have had good success with it so far, for implement LLM calls and implement the /model picker.

Overall in my experience building VT, the most important aspect of effective coding agent is context engineering, like all big-lab has research. A good system prompt is also very important, but not context is everything. https://github.com/vinhnx/vtcode/blob/main/prompts/system.md

// Sorry, English is not my main language, so pardon the typo and grammar. Thank you!