Chainfeeds Summary:
This article breaks down the AI × Crypto investment logic proposed by a16z and explains how Know Your Agent (KYA) and cryptographic trust mechanisms enable AI agents to collaborate. It also explores why micropayments are a key infrastructure for building a sustainable AI economy, and discusses relevant projects and underlying architectures that are currently worth noting.
Article source:
https://x.com/stacy_muur/status/2021860725409358329
Article Author:
Stacy Muur
Opinion:
Stacy Muur: AI is approaching a stage where it can solve problems that only a select few top experts worldwide can solve. Recently, ChatGPT 5.2 successfully solved a mathematical problem that only a few hundred people globally could solve. We used to criticize AI for its hallucinations. But as models improve, these biases may become a source of creativity, helping it combine ideas and build cross-disciplinary connections like human brainstorming. To unleash this creativity at scale, a single model is insufficient; a multi-layered collaborative system is needed: one AI generates an idea, a second critiques it, a third optimizes it, and a fourth verifies it. However, when multiple AIs collaborate, two fundamental issues arise: interoperability and accountability. When one AI proposes an idea, another optimizes it, and a third verifies it, how are contributions defined, rewards paid, and responsibilities assigned? This is where cryptography and blockchain naturally align. Relevant projects include Covalent, Allora Network, Questflow, GaiaNet, and SentientAGI. AI is already operating in the real economy; the question is no longer about intelligence, but about who owns it, what it can do, and who is responsible when problems arise. Therefore, websites block them by default through CAPTCHAs, IP blocking, and bot detection. The solution is Know Your Agent (KYA). AI agents need encrypted identities similar to human KYC: a signing key to prove the creator, specify the entity they represent (individual/company/DAO), the scope of permissions and constraints, and the attribution of responsibility. Related projects include Billions Network, cheqd, and Vouched. AI is reshaping the value cycle of open networks. In the past, it was: search → click on a website → website profits. Now, ask an AI question → AI reads the website → provides an answer → website loses traffic and revenue. This creates a hidden tax. If advertising revenue continues to decline, creators reduce content production, open networks shrink, and AI loses its source of high-quality data, the solution is not slow legislation, but a technological restructuring of incentives. A pay-per-use model, where payment is made in real time each time AI uses content, similar to Spotify's pay-per-view model. Related projects include Catena Labs, x402, and AIsa. [Original text in English]
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