On February 7, Chris Dixon, a partner at a16z and leader of a16z crypto, shared insights on social media regarding the long-term prospects of cryptocurrency. According to BlockBeats, Dixon addressed the prevailing notion that non-financial applications of cryptocurrency are obsolete and the 'read-write-own' model has failed. He argued that these conclusions misunderstand the core principles and misjudge the current stage of development.
Dixon emphasized that the blockchain era is currently focused on finance, but the fundamental idea is not that all crypto applications will emerge simultaneously or that finance won't lead the way. The core concept is that blockchain introduces a new primitive capable of coordinating human and capital resources at internet scale, embedding ownership directly into systems.
Finance naturally demonstrates the value of this primitive, which is why it is often cited as a primary example of productive token use cases. It is not separate from the broader vision but rather a foundational part of it, serving as the basis and testing ground for other applications.
At a16z and a16z crypto, the focus is on the long term, with fund structures designed for cycles exceeding ten years, acknowledging that building new industries takes time and sequence is crucial.
Infrastructure and distribution networks typically precede new application categories. The internet did not begin with social media, streaming, or online communities; it started with packet switching, TCP/IP, and basic connectivity. Only after hundreds of millions of people went online did new cultural and economic categories emerge. Cryptocurrency is likely to follow a similar path, requiring financial applications like payments, stablecoins, savings, and DeFi to bring millions on-chain before meaningful adoption in media, gaming, AI, or other areas can occur. Many applications depend on ready wallets, identity, liquidity, and trust mechanisms.
This is why a16z has spent over five years advocating for clear token regulatory frameworks. Great endeavors require time. The breakthroughs seen in AI today are the result of decades of hard work by talented individuals. Building new technological systems is a marathon, characterized by long periods of groundwork followed by sharp turning points. It is these tumultuous years that pave the way for future achievements.
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