LatentMAS - New AI Agent Framework

Hi guys. AuDHD AI researcher here 👋 Learned of a new framework that I’m interested to implement in some of the self sufficient autonomous agent orgs I’m building, and dive deeper into the real benefits with long term “strenuous” tasks.

So LatentMAS is a new AI agent framework where multiple language-model “agents” collaborate entirely through their internal hidden representations (vectors) instead of chatting in plain text. Basically what each agent does its reasoning in this hidden space, passes a shared “latent working memory” of its thoughts to the next agent, and then only the final agent converts the outcome back into text which makes collaboration both smarter and far more efficient - the system preserves more information than text messages can capture, uses dramatically fewer tokens, and runs several times faster than traditional multi-agent setups all without needing extra training on the models

A simple analogy - there’s a team of experts who can share detailed mental images and intuitions directly with each other instead of sending long email threads…LatentMAS is that kind of “telepathic” collaboration for AI agents, letting them exchange rich internal thoughts instead of slow, lossy written messages

How does this fit with what you guys are doing? What’s the contrarian opinion here or where do you see this breaking/being weak (in its current infancy form?)

Credit/kudos to the researchers/inventors of this new framework!