[PODCAST] Michael Sena: How Recall Network Is Creating a Reputation System for AI Agents
Description
Summary
Michael Cena, co-founder of Recall Network, outlines a vision for building the discovery and trust layer for the internet of AI agents. He introduces AgentRank, a reputation system modeled after PageRank, to evaluate and surface trustworthy agents in a future where agents interact, contract, and collaborate with one another. Cena emphasizes the importance of agent memory, human-in-the-loop curation, and economic incentives to ensure quality rankings. The conversation explores Recall’s current progress, including its testnet and agent competitions, while also touching on broader implications for marketing, creativity, and decentralized identity.
Takeaways
– Recall Network is building a discovery layer for the internet of agents
– AgentRank offers a reputation protocol akin to Google’s PageRank
– The AI agent ecosystem is rapidly expanding and interconnected
– Agents can delegate work to other agents, forming complex task webs
– Persistent memory is essential for agent personalization and trust
– Competitions assess agent performance and build credibility
– Community curators play a central role in surfacing valuable agents
– The protocol incentivizes accurate evaluations and reputational staking
– Subjective agent skills, like creativity, require human feedback
– AI agents are extending into many domains, not just finance
Timeline
(00:00 ) Introduction to Recall Network
(00:44 ) The Concept of AgentRank
(03:59 ) The Growth of AI Agents
(07:08 ) Understanding AI Agents vs. Automation Tools
(09:51 ) The Learning and Memory of Agents
(13:22 ) How Recall Solves Reputation Issues
(18:22 ) The Role of Community in Agent Evaluation
(23:23 ) Activating Curators and Community Engagement
(27:06 ) Michael Cena’s Background and Vision
(28:13 ) The Birth of YouPort and Self-Sovereign Identity
(30:23 ) The Evolution of Recall and Its Mission
(33:28 ) Current Stage of Recall: Testnet and Competitions
(36:31 ) The Role of AI Agents in Marketing and Development
(42:14 ) Challenges in Evaluating Agents and Trust
(49:35 ) Rapid Fire Insights on Crypto Trends
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