What is the real competition in the AI ​​Agent economy?

Author: Han Qin , CEO of Jarsy

A friend asked what the real competition is in the AI ​​Agent Economy?

Many friends have actually shared their thoughts and have offered excellent insights into whether AI agents really need crypto.

But the real issue to discuss isn't whether AI agents need Visa or Crypto, but whether they need a "traditional credit system" or an "algorithmic trust system."

This question touches upon the most fundamental fork in the future financial structure: should human society rely on credit backed by humans or on trust guaranteed by mathematics?

This topic only became meaningful after Bitcoin provided a mathematical proof of trust.

Let's first define two systems. The essence of a credit system is the belief that an entity will not default. This trust originates from legal reputation, regulatory status, and intermediaries. Its core structure connects people to institutions, rules, and trust. Typical examples include the banking system, Visa and Mastercard, the securities market, and loan contracts.

However, algorithmic trust systems differ. Their essence lies in not needing to trust anyone; trust originates from mathematical proofs, cryptography, signatures, consensus, and an immutable ledger. The core structure is from code to mathematics, to automatic execution, and finally to trust. Typical examples include blockchain, smart contracts, ZooKeepers, and MPC.

The most fundamental difference between the two lies at the philosophical level. Trust in a credit system originates from human institutions, fails due to human default, is corrected by the courts, and is confined to the state. Trust in an algorithmic system originates from mathematical theorems, fails due to code vulnerabilities, is corrected by forking, and is confined to the network. Therefore, essentially, a credit system equals trust in human agents, while an algorithmic system equals trust in code rules.

So why did human societies initially rely solely on credit systems? Because historically, the technology for algorithmic trust was lacking. Achieving algorithmic trust requires public-key cryptography, distributed networks, consensus algorithms, and verifiable computation—all of which have only emerged in recent decades. Therefore, for millennia, the only feasible solution was to find someone everyone trusted—either an elder, a king, or, in modern times, a central bank.

Why is the AI ​​era approaching algorithmic trust? Because AI has changed the structure of transaction participants. In the past, transaction participants were equal to humans; now, they are equal to AI agents plus humans. The problem then arises: machines cannot understand legal reputation and social relationships; they can only understand verifiable rules.

Therefore, the AI ​​native economy must lean towards an algorithm-based trust system; otherwise, machines cannot participate smoothly.

Of course, the advantages of a credit system will not disappear. Many people mistakenly believe that crypto will replace the credit system, which is impossible. This is because a credit system is naturally suited to a world of high uncertainty, such as venture capital, healthcare, war, and entrepreneurship. These scenarios cannot be predefined with code and require judgment and flexible consensus, which these algorithms cannot handle.

Secondly, real society requires human intervention to correct errors. Fraud, mistakes, and gray areas are inevitable in the real world, and only humans can adjudicate these. Furthermore, long-term trust relationships still require traditional credit systems, such as family trusts, political alliances, and strategic partnerships. These rely on relational capital, not algorithms.

However, the advantages of algorithmic trust systems are growing explosively. We don't see it today because that tipping point hasn't arrived yet. In high-frequency trading environments, because machine speed far surpasses the speed of human trust, crypto will have an overwhelming advantage. Furthermore, cross-border transactions are a natural strength of crypto, as algorithms are borderless. Of course, the permissionless scenarios we've discussed are crypto's primary battleground.

In the future, the real world will not present a binary choice; the true endgame structure will undoubtedly be a layered trust architecture. The upper layer is the credit governance layer, responsible for rule-making, dispute resolution, and risk-bearing; the national courts will remain the primary agents. The middle layer is the protocol execution layer, responsible for automatic execution, asset transfer, and liquidation; blockchain and smart contracts will be the primary agents. The bottom layer is the computational verification layer, responsible for cryptographic proofs, data integrity, and consensus algorithms.

The biggest competition of the future won't be between cryptocurrencies and banks, but rather who defines the trust interface standard. Whoever defines the standard controls the ecosystem. History has shown that TCP/IP defined the internet, SWIFT defined financial communication, and Visa defined consumer payments. The next standard may well be a programmable trust protocol to define the AI ​​agent economy.

If a credit system is like a country governed by law, then algorithmic trust is like a society of automated machines. The relationship between the two is not one of substitution, but rather that the law stipulates the rules, and the machines execute those rules.

Credit systems solve the problem of who is trustworthy, while algorithmic trust solves the problem of not needing to trust anyone.