Give your AI agent a real memory in 50 lines of Python

Your AI agent is brilliant for exactly one conversation. Then it forgets everything. It doesn't remember that the user prefers dark mode. It can't recall that it already solved this exact problem last Tuesday. It has no idea which approach worked and which one failed. Most developers fix this by duct-taping a vector store, a Redis cache, and a conversation log together. That's three services to maintain for something that should be built into the engine. I wanted a single pip install that gives an AI agent the same three types of memory that cognitive science describes for humans: what it knows (semantic), what it experienced (episodic), and what it knows how to do (procedural). This distinction comes from Endel Tulving's foundational work (1972) and Larry Squire's taxonomy of memory systems (2004), and it has been successfully implemented in cognitive architectures like SOAR and ACT-R for decades. So I built it into VelesDB. The problem with "memory" in AI agents today Most agent fram