The Fastest Revenue Scalers are in Crypto Crypto revenue velocity has increased as the ecosystem has evolved from protocols to applications that scale trading attention and monetizing market volatility. DeFi Protocol Era – crypto companies have historically been very fast at generating revenue, with even initial DeFi protocols like Maker and Aave hitting $100m in cumulative revenue within years of monetizing. DeFi Terminal Era – trading terminals have compounded the rate at which applications in crypto earn revenue by providing convenience and better discovery experiences for trading. DeFi Attention Scalers – Apps like Pump, Axiom, and Hyperliquid have more efficiently monetized attention by focusing on rapid product iteration to maximize surface area of products including, spot, perps, leverage, yield, new market contracts, hyper-specific discovery tools, and social products. All of this has been in service of the goal – provide the best product that allows people to trade attention and market volatility. This growth of revenue velocity isn't unique to crypto. It's happening more broadly across tech with traditional SaaS having similarly undergone a transition of explosive revenue velocity in shorter periods of time with more efficient workforces. The driver for SaaS has been the transition towards product-led companies that now leverage AI-first products that have seen unprecedented usage. Where do crypto revenue scalers go from here? Crypto has yet to fully capitalize on leveraging AI within trading and market creation. I expect that a new wave of DeFi Attention Scalers will emerge over time as new apps are able to more effectively use AI to provide curated experiences. This may look like better discovery for prediction markets, social-integrated trading, or otherwise embedding AI-discovery tooling to enable new trading interfaces and token issuance platforms. In a world where all assets are moving onchain, the quantity of assets is going to 100x, and the programmability of those assets leads to more derivatives, the question for users quickly becomes "what should a buy?". The application that provides the most compelling answer to users wins.
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