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.

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.