In the evolving AI Agent Economy, a fundamental question arises: should we adopt a traditional credit system or an algorithmic trust system? This debate follows Bitcoin’s establishment of mathematical trust, drawing a distinction between the two frameworks. Credit systems rely on human agents and institutions, fostering trust through reputation and legal backing. They function well in uncertain scenarios requiring human judgment—like venture capital and healthcare. Conversely, algorithmic trust eliminates the need for human intermediaries, relying on cryptography, consensus algorithms, and blockchain technologies. As AI transforms transaction participants from solely humans to include AI agents, a shift toward algorithmic trust becomes essential; machines operate on verifiable rules, not social relationships. The future will likely feature a layered trust architecture, merging both systems. The real competition lies in defining trust interfaces, as the next programmable trust protocol could revolutionize the AI economy, marrying law with automated execution for efficient transactions.
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