Ask HN: Rust and AI builders interested in local-first, multi-agent systems?

[cajazzer]

I’m a founder exploring a local-first personal AI system built around multi-agent architecture and on-device intelligence.

This is not a cloud chatbot or a hosted-LLM wrapper. The focus is on building an assistant that lives with the user — understands personal context, reasons over local data, and can act autonomously without exporting private information off the device.

I’m interested in connecting with senior engineers who enjoy building AI systems in Rust, think in terms of orchestration and state, and care deeply about correctness, performance, and privacy.

San Francisco Bay Area preferred, as I believe early in-person collaboration matters.

Posting anonymously for privacy reasons — happy to share more in 1:1 conversations.

— Founder, SF Bay Area Contact: [e-mail]

[colbyn]

As old a rust dev. Any interest in the client side of things? I’ve been experimenting with a few ideas in this regard. Especially, true native markdown rendering and a branching conversational data model. (This complicated the UI and required better layout handling.)

[cajazzer]

Yes — definitely interested in the client side, especially where it intersects with core system design rather than just presentation.

Both native markdown rendering and non-linear / branching conversation models are areas I’ve been thinking about as well, particularly as systems move beyond linear chat and into more exploratory or agent-driven workflows.

Would be curious to hear more about what you experimented with and what tradeoffs you ran into, especially on the data model and UI side.

[repelsteeltje]

> I’m interested in connecting with senior engineers who enjoy building AI systems in Rust, think in terms of orchestration and state, and care deeply about correctness, performance, and privacy.

So something like triton server backends, but using rust rather that python or c++?

[cajazzer]

Thanks. That’s a fair comparison, but I’m thinking a bit broader than model serving alone.

I’m less interested in building a generic inference backend and more focused on how the system behaves over time — things like agent lifecycles, state, memory, and coordination. Inference is part of it, but not the whole thing.

Correctness, performance, and privacy matter because the system is long-lived and stateful, not just because it’s pushing tokens around.