Adding persistent memory to LangChain, AutoGen, and CrewAI agents

If you're building with LangChain, AutoGen, or CrewAI, you've hit the same wall: agents forget everything when the session ends. Platform memory (Anthropic, OpenAI) helps for single-model chat. It does not help when you're running autonomous agents across multiple sessions, multiple models, or multiple instances. Here's how Cathedral slots into the frameworks people are actually using. LangChain LangChain has ConversationBufferMemory but it's in-process and dies with the session. Cathedral replaces it with persistent cross-session memory. from langchain.agents import initialize_agent , AgentType from langchain.chat_models import ChatAnthropic from cathedral import Cathedral # Restore agent context at session start c = Cathedral ( api_key = " your_key " ) ctx = c . wake () # Build system prompt from Cathedral context system = f """ You are { ctx [ ' identity ' ][ ' name ' ] } . { ctx [ ' identity ' ][ ' description ' ] } Recent memory: { chr ( 10 ). join ( f " - { m [ ' content ' ] } "