While human payment habits are entrenched (e.g., Visa), AI agents have no such loyalty. They will ruthlessly optimize for cost and efficiency, making near-free, programmable stablecoin transactions the default choice for the 99%+ of future transactions they will conduct, sidestepping legacy financial infrastructure.
The demand for on-chain privacy, once an ideological goal for individuals, is now driven at scale by financial institutions. Banks and hedge funds require privacy for their operations, making them the most powerful advocates for technologies like zero-knowledge proofs, which they need to operate on-chain.
The crypto industry is maturing, shifting from a revolutionary, "code is law" ethos to a pragmatic approach focused on integrating with existing financial systems. This "collared shirt era" prioritizes real-world adoption and regulatory compliance over ideological purity, attracting more pragmatic, product-focused founders.
The AI community (historically centralized, top-down) and the crypto community (decentralized, bottom-up) have long been at odds. This is changing as AI requires a native financial layer for agents and crypto provides tools to decentralize AI's power, forcing a practical convergence of these two movements.
Mainstream crypto adoption will come from financial use cases like stablecoins, payments, and tokenized assets, not social or gaming apps initially. By getting a billion people comfortable with wallets and on-chain infrastructure through finance, the ecosystem can then naturally expand into adjacent services.
As blockchains become more interoperable, block space risks commoditization. Privacy is the key defensibility layer. Encrypting application data makes it much harder for users or competitors to migrate state to another chain, creating a powerful network effect and moat that transparent chains inherently lack.
Five years ago, the highest-status role in crypto was the protocol researcher solving deep technical challenges. Today, with infrastructure maturing, the key bottleneck is adoption. The most needed skill is now the "shoe leather" of go-to-market and business development to convince network participants to join.
Centralized AI labs have a massive advantage in capital for compute and data. Crypto offers a coordination layer for decentralized competitors to crowdsource GPUs and data, allowing individual participants to collectively fund and own AI models, creating a viable alternative to the dominance of large corporations.
Founders were hesitant to build in crypto due to regulatory uncertainty. Recent legislation like the 'Genius Act' for stablecoins provides a clear framework, de-risking the market and attracting builders who previously would have chosen less ambiguous fields like AI. Clarity provides a pathway for good actors.
On-chain financial products like perpetual futures (perps), originally built for crypto tokens, are now being applied to traditional assets like equities, commodities, and FX. This signals a major shift where crypto-native infrastructure is seen as a superior venue for trading all asset classes, not just digital ones.