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The recent crypto market has been stirred by a wave— the concept of "AI Agent Economy" has surged against the trend, and related tokens have responded accordingly. The surface story is very appealing: AI agents evolve from passive chart analysis to actively managing wallets and executing DeFi strategies. But when this wave of enthusiasm subsides, a hidden, colder technological reality comes into view: these increasingly autonomous and "valuable" AI agents generate massive interaction records daily, accumulate learning experiences, and rely on various "means of production" to execute tasks. Where should all this data go?
This is not a small problem. Can traditional centralized servers suffice? Clearly not— the autonomy of these agents is constrained by the architecture itself. So what about decentralized storage? How can we break the deadlock between cost, security, and availability?
The answer determines not just the superficial question of "Can AI trade cryptocurrencies," but also how large the entire agent economy can grow and whether it can be truly sustainable.
Conversely, an AI agent that conducts autonomous on-chain transactions embodies both value and fragility— two sides of the same coin. It continuously learns optimal strategies through trial and error— every successful arbitrage, every failed interaction is valuable experience data. But where this data is stored and who protects it directly determines the "lifecycle" of the agent. Data loss, tampering, or hijacking by centralized platforms would strip the agent of its core competitiveness. This is the Achilles' heel of the agent economy.