I replaced my agents markdown memory with a semantic graph

Why flat files are a dead end for agent memory and what happens when you use a DAG instead I have been building with AI agents since mid-2025. First with LangChain, then briefly with AutoGen, and for the last couple months with OpenClaw. And the whole time there was something bugging me that I could not quite articulate until I saw it break in production. The memory problem. The thing nobody talks about Every agent framework I have used stores memory the same way: text files. Markdown, YAML, JSON, whatever. It is all the same idea -- dump what the agent "knows" into a flat file and hope for the best. OpenClaw does this with SOUL.md (the agent personality), HEARTBEAT.md (its task loop), and a bunch of markdown files for conversation history and long-term memory. And honestly? It works fine for personal use. I ran my OpenClaw agent for weeks managing my email and calendar through Telegram. No complaints. Then I tried to build something for a client. The client is a small fintech in Spain