The Secret to Scalable AI Agents: Virtual Filesystems with Deep Agents

Description

Your AI agent sees one filesystem. Under the hood? S3, SQLite, and local disk, all working together. In this video, I show how Deep Agents uses virtual filesystems to give your agent a unified interface while routing to completely different storage backends. The agent doesn't know (or care) where data actually lives. 🔥 What you'll see: • CompositeBackend routing paths to different storage systems • SQLite backend that synthesizes files from database tables (not stored files!) • S3 backend for cloud documentation • Local filesystem for agent output • A working AI sales assistant that reads customer data and generates proposals 📂 The Architecture: /docs/ → S3 (company documentation) /memories/ → SQLite → Virtual files (user profiles + conversation history) /workspace/ → Local disk (generated proposals) The agent uses standard filesystem operations (ls, read_file, write_file) but each path routes to a different backend. The SQLite backend is especially interesting—it stores data in proper relational tables and generates JSON/Markdown files on-the-fly from SQL queries. 📚 Resources: • Code: https://github.com/christian-bromann/deepagents-filesystem-example • Deep Agents docs: https://docs.langchain.com/oss/javascript/deepagents/overview • Backends documentation: https://docs.langchain.com/oss/javascript/deepagents/backends 👉 npm install deepagents 📦 https://www.npmjs.com/package/deepagents