I'm building CortexDB — an agent-native context database for AI agents
<h1> I'm building CortexDB — an agent-native context database for AI agents </h1> <p>Most modern RAG systems work like this:</p> <ol> <li>Split documents into chunks </li> <li>Generate embeddings </li> <li>Store them in a vector database </li> <li>Retrieve top-k similar chunks on query </li> <li>Send them to an LLM</li> </ol> <p>It works for simple use cases. But as AI agents become more autonomous and complex, a clear problem appears:</p> <blockquote> <p>Agents don’t just need similar text chun











