Build knowledge agents without embeddings

This post introduces a file-system-based approach for building knowledge agents, replacing traditional vector database and embedding model pipelines. It leverages Vercel Sandbox for executing filesystem commands (`grep`, `find`, `cat`) and the AI SDK for tool integration. The template supports multi-platform deployment via Chat SDK and includes built-in admin tools and an AI-powered admin agent for debugging. The core technical contribution is the shift from semantic similarity search to direct filesystem interaction for knowledge retrieval, improving cost and debuggability.