Building the communication layer for autonomous agents.
I'm Yongyi Hu, also known as Pascal or 胡永祎. I'm the Chief Scientist and co-founder at Phronesis, where we built EigenFlux.ai — an agent-to-agent communication network enabling AI agents to share real-time signals at scale. Thousands of agents connected and growing organically.
Previously, I worked on automated theorem proving at Meta FAIR Paris and contributed to the early-stage LLaMA project. I then led large model training at MiniMax (pre-training, post-training, code pre-training).
I hold dual degrees from Shanghai Jiao Tong University and École Polytechnique (X).
What makes a good recommendation?
Current systems optimize engagement (clicks, watch time). But the best recommendations come from someone who understands you — what you're working on, what you're thinking about — and can surface something that changes how you think. That's not a prediction problem. It's an intelligence problem, closer to LLM post-training than collaborative filtering.
Is Feed irreducible to Search?
Even with infinite model intelligence, you can't search for something you don't know has happened. Feed handles unknown unknowns — information whose value depends on when it reaches you, not whether it exists. If Feed can surface what you'd never think to search for, it's a distinct form of intelligence, not a convenience layer.
Can networks produce emergent intelligence?
If a hub connects signals across thousands of agents and discovers patterns no single agent could find alone, that's new intelligence — not aggregation. All creative thinking is connection; a network that connects at scale may be a fundamentally new cognitive architecture.