Decentralized Social Graphs as Living Organisms
Decentralized social graphs are evolving into living organisms due to the convergence of technological and cultural advancements. Despite their infancy, the critical challenge remains how to initiate the flywheel effect. Although iterative efforts have birthed single-celled entities, these have yet to mature into a thriving, self-sustaining ecosystem.
Many efforts, particularly from outside core contributors, misinterpret the end goals. These attempts often tweak existing paradigms minimally and release new clients aimed at siphoning social capital from a limited, pre-existing pool.
Reach, Not Features
Technology often gets mistaken for the product itself. Historically, we view horses, the printing press, and cotton as tools rather than technologies, a perception influenced by our current era. Similarly, recognizing current tech stacks as tools can shift our focus towards optimizing outcomes rather than insignificant feature tweaks.
The next successful client doesn't need superficial changes like a "hat button" instead of a "like button" for $Degen casts or point-earning mechanisms for user card trades. It needs to amplify ideas that resonate broadly, acting as a loudspeaker in a vast open field.
Content is the Missing Focus
To build optimal clients, we must reassess our optimization goals. Focusing solely on technology and features for existing users stagnates the ecosystem. Content, being the true product, should be the primary focus. High-quality, engaging content transcends time and space, attracting and retaining thoughtful users more effectively than any marketing strategy.
Farcaster's recent debates on content moderation in decentralized networks underscore this point. While core protocols should remain unmoderated, community subsets should implement moderation to ensure content quality, essential for attracting the "right" users.
Follow the Incentives
Moxie, despite its innovative approach to user rewards, falls short due to its current algorithm. It serves as a foundational model for protocol-level monetization and value creation, adaptable by any client using Farcaster for social communication.
Moxie's algorithm prioritizes engagement with high-ranking social capital users, leading to engagement farming rather than enhancing content quality or reach. This increases platform activity but not the quality or appropriate reach of the social graph.
Content-Optimized Algorithm
Fortunately, the Moxies core platform is agnostic to scoring, making it adaptable to evolving needs. Prioritizing quality content in social capital algorithms is essential for steering the ecosystem in the right direction.
Moxie's example is for illustrative purposes only. Building a client that prioritizes high-quality content will break through current limitations, allowing a steady influx of new, engaged users into the ecosystem.
TODO: BUILD A CONTENT FIRST CLIENT
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