Building personal AI systems

I've been deeply focused on how to bridge the gap between general-purpose LLMs and personal context. The goal is an AI that doesn't just answer questions, but understands active projects, a calendar, and a codebase — without sending that private material to a hosted service.

Currently exploring local inference models connected through a unified memory architecture using retrieval-augmented generation (RAG).

The biggest challenge isn't intelligence. It's context delivery latency — retrieving the right chunk of the right file fast enough that the system feels like it's keeping up with you, not making you wait for it to catch up.