I'm building CortexDB — an agent-native context database for AI agents

I'm building CortexDB — an agent-native context database for AI agents Most modern RAG systems follow the same pattern: Split documents into chunks Compute embeddings Store them in a vector database Retrieve top-k similar chunks Send them to an LLM It works. But as AI agents become more autonomous,