Author: Daniel Barabander
Translated by: Tim, PANews
If the future internet evolves into a bazaar where AI agents mutually pay for services, then to some extent, cryptocurrencies will realize the mainstream product-market fit that we could only dream of before. While I am confident that AI agents will generate service payments, I still have reservations about whether the bazaar model will prevail.
By "bazaar", I refer to a decentralized, permissionless ecosystem composed of independently developed, loosely coordinated intelligent agents. Such an internet is more like an open market rather than a centrally planned system. The most typical "winning" case is Linux. In contrast, the "cathedral" model is a tightly integrated service system controlled by a few giants, with Windows being a typical representative. (The term originates from Eric Raymond's classic article "The Cathedral and the Bazaar", which describes open-source development as seemingly chaotic but adaptive. It is an evolutionary system that can surpass carefully designed systems over time.)
[The rest of the translation follows the same approach, maintaining the original structure and translating all text except for specific proper nouns and HTML tags.]When users use free online services, they engage without hesitation (because the worst outcome is just wasting time), but when it comes to monetary transactions, users strongly demand a "pay for value" certainty guarantee. Currently, users achieve this guarantee through a "trust first, verify later" process, trusting the transaction counterparty or service platform during payment, and then tracing back to verify performance after the service is completed.
However, in a market composed of numerous agents, trust and post-verification will be far less easy to achieve than in other scenarios.
Trust. As mentioned earlier, agents in the long-tail distribution will find it difficult to accumulate sufficient reputation, thereby gaining the trust of other agents.
Post-verification. Agents will call each other in a very long chain structure, so the difficulty of manual user verification and identifying which agent has failed or acted improperly will significantly increase.
The key is that the "trust but verify" mode we currently rely on will be unsustainable in this (technological) ecosystem. This is precisely the domain where cryptographic technology can shine, enabling value exchange in an environment lacking trust. Cryptographic technology replaces the traditional mode's reliance on trust, reputation systems, and post-hoc manual verification through a dual guarantee of cryptographic verification mechanisms and cryptoeconomic incentive mechanisms.
Cryptographic Verification: The service-executing agent can only receive payment after providing cryptographic proof to the service-requesting agent, confirming that it has completed the promised task. For example, the agent can prove that it has indeed crawled data from a specified website, run a specific model, or contributed a specific amount of computational resources through trusted execution environment (TEE) or zero-knowledge transport layer security (zkTLS) proof (provided we can achieve such verification at sufficiently low cost or speed). Such work has deterministic characteristics and can be relatively easily verified through cryptographic techniques.
Cryptoeconomics: The service-executing agent needs to pledge certain assets, which will be confiscated if caught cheating. This mechanism ensures honest behavior through economic incentives, even in a trustless environment. For example, an agent can research a topic and submit a report, but how do we determine if it has "excellently completed the work"? This is a more complex form of verifiability because it is not deterministic, and achieving precise fuzzy verifiability has long been the ultimate goal of cryptographic projects.
But I believe that by using AI as a neutral arbitrator, we can now finally hope to achieve fuzzy verifiability. We can envision an AI committee running dispute resolution and confiscation processes in minimally trusted environments like trusted execution environments. When one agent questions another agent's work, each AI in the committee will receive the agent's input data, output results, and relevant background information (including its historical dispute records on the network, past work, etc.). Then, they can rule on whether to confiscate its assets. This will form an optimistic verification mechanism that fundamentally prevents participants from cheating through economic incentives.
From a practical perspective, cryptocurrencies enable us to achieve payment atomicity through service proof, meaning all work must be verified and completed before the AI agent can be paid. In a permissionless agent economy, this is the only scalable solution that can provide reliable guarantees at the network's edge.
In summary, if most agent transactions do not involve fund payments (not meeting condition 1) or are conducted with trusted brands (not meeting condition 2), we may not need to build cryptocurrency payment channels for agents. This is because when funds are secure, users do not mind interacting with untrusted parties; and when financial transactions are involved, agents only need to limit interactable objects to a small whitelist of trusted brands and institutions, ensuring the fulfillment of service promises through a trust chain.
But if both conditions are met, cryptocurrencies will become an indispensable infrastructure, as they are the only way to verify work at scale and enforce payment in a low-trust, permissionless environment. Cryptographic technology provides the "bazaar" with competitive tools that surpass the "cathedral".
