We have been exploring the intersection of crypto and AI, examining what happens when two powerful technologies converge. This episode reflects on how AI agents came to be, how they became a part of our social graphs and speculates on what roles they will play in our lives. If you're working at the crossroads of Crypto and AI and want to collaborate with us, please get in touch.
Hello!
There's something poetic about a sound engineer who spent years mixing bands in New York City clubs, orchestrating one of crypto's most intriguing experiments in AI.
Shaw, the founder of AI16Z DAO and creator of the Eliza framework, joined me for a conversation on December 10. We explored how a seemingly simple idea of helping developers access better trading strategies evolved into a platform that's reshaping how we think about AI in crypto.
This conversation builds on themes I explored in my recent article, 'Using Chains, Taming Minds,' in which I examined how AI agents are reshaping crypto markets and digital culture. We built SentientMarketCap to monitor and analyse the AI agent sector in crypto.
AI16Z sits at the intersection of AI automation and community-driven finance. Traditional finance keeps its trading strategies private. Conversely, in crypto, while sophisticated traders and funds use advanced strategies, retail traders often rely on influencer signals and private groups. AI16Z trades at ~$800 million, while the DAO manages $21 million.
According to the DAO, its token holders above a certain threshold get access to interact with agent AI Marc, pitch ideas, and try to influence his investing decisions. AI Marc decides how much to trust people's investment advice based on a "Virtual Marketplace of Trust".
Their Eliza framework, which is used to build AI16Z, has attracted over 140 contributors, and they have an eight-person team.
Shaw's team solved what he calls the "social agent loop" by making it simple for AI agents to engage naturally on platforms like Twitter. Projects like Eliza and Virtuals Protocol have made it easy to create these agents, leading to thousands of AI agents operating in the wild, from traders to market commentators to digital personalities.
Their vision for democratising AI goes beyond just trading. With a $20M treasury managed by AI and no VC funding, AI16Z represents a new model of organisational structure. Their approach challenges traditional notions of value creation in crypto. It creates a possibility that transparent, AI-driven systems might replace the current influencer-driven market dynamics in the future.
If you want to learn to create your agents, here’s a tutorial by Shaw.
The future may well be one where AI agents don't just assist in trading but fundamentally reshape how markets function. Whether this leads to more efficient markets or new forms of market dynamics entirely remains to be seen.
This episode is about recognising moments of transformation as they happen and understanding how to stay ahead of them.
Signing off,
Saurabh Deshpande
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