Prism v11.0 enables AI agents to recall information instantly without searching — using a memory technique borrowed from cognitive psychology

Developer dcostenco released Prism v11.0, an open-source tool that gives AI agents (autonomous AI systems that make decisions and take actions) a new memory system based on Holographic Reduced Representations and cognitive science principles. The system retrieves stored information in constant time — meaning lookup speed doesn't slow down as memory grows, unlike traditional search.

Instead of forcing AI agents to search through past conversations or documents each time they need context, Prism stores information in a compressed mathematical structure inspired by how human brains organize memory. This means agents can answer questions about prior interactions instantly, without the delay of sifting through logs or databases.

For teams building AI assistants, chatbots, or workflow automation tools, this eliminates a major bottleneck: agents can now maintain coherent long conversations and remember user preferences without slowing down. Customer service bots stay responsive even after thousands of interactions; personal AI assistants recall context from weeks of prior chats without lag.