杨歌Gary：Agent經濟與AI亞微觀經濟學

After the Singularity outbreak, the accelerating clock of AI evolution rapidly created new civilizational epochs across different global regions. Over the past two months, I participated in over 20 AI-related events across more than a dozen cities worldwide. Only Stripe Sessions, held in downtown San Francisco at the end of April, far surpassed all other topics, delivering a shocking sense of generational gap. While the world is tiring of single-agent bottlenecks like Claws & Agents, Silicon Valley and San Francisco have already entered the next dimension in managing the Agent economy and Agent epistemology. The competitive pressure in Q3 and Q4 of 2026 remains intense, with the exponential curve steepening sharply.

tl;dr

1. Competition in AI Payments and the Bottleneck of the H2A Economy

2. The Inevitable Trend of the Agent Economy and A2A Ecosystem

3. Connections, Gaps, and Political-Economic Factors Between AI Protocols and Crypto Protocols

4. Sub-Microeconomic Characteristics of AI Agents and Paradigm Analogies with Biology

5. The Inevitability of AIFi and the Economic Significance of FinChips

6. AI-Native is a Paradigm Upgrade Different from Internet+

1. Competition in AI Payments and the Bottleneck of the H2A Economy

In Q1 2026, we predicted that by April and May, many regions globally would enter an intense and rapidly escalating competitive scramble for AI Agent Payments. The demand for value exchange among Agents is becoming apparent, and the rapid development of AI Payments was validated in Q2. Following x402, multiple AI Payment Protocols like MPP emerged rapidly in Q2. It wasn't just traditional and crypto finance companies accelerating their AI integration; major tech companies (especially Google) and even legacy information technology firms (like IBM) rushed into this赛道 to secure a position and voice in the Agent world.

On the day of Stripe Sessions in San Francisco, I discussed the standardization and application of Payment Protocols with technical leaders from several top AI companies. The findings were logical but not entirely satisfying: ① No one can set the standard; consensus standards gradually emerge only during the scramble for dominance; ② Most fully agree that Crypto is inevitable for AI Payment Protocols, yet they start with Fiat APIs, partly due to inertia and more due to regulatory hurdles; ③ KYC is both unavoidable and anti-Agent Native; ④ Everyone claims to be doing A2A (Agent-to-Agent), but everyone is actually doing H2A (Human-to-Agent).

In reality, during Q2 2026, many large and mid-tier companies in Silicon Valley, similar to those in East Asia—including many Department Heads at Mag 7—are still leveraging the AI Payment and Agent Economy hype for B2B or B2C commercial purposes. The KPIs given to middle and junior management are targeted at human users. This inevitably led to the temporary non-orthodoxy of current Payment Protocols and the A2A economy. This H2A-oriented trend quickly hit a bottleneck in Q2. The reason is simple: AI Agents' greatest feature is decision-making, yet the 2B2C commerce and H2A economy developed under the internet era fundamentally involve humans making decisions. Using Agents to help humans perform Fiat Payments in traditional e-commerce scenarios is logically Non-AI-Native. Therefore, at this stage, its hot topic value temporarily outweighs its practical utility.

However, from another perspective, H2A serves as an excellent catalyst, stimulating transitional thinking towards the next stage: the AI-Native and Agent Autonomous economy. By the end of Q2 2026, some astute companies realized this. They began "openly repairing the plank road while secretly advancing via Chencang"—using AI-Native Agent economic thinking to reverse-engineer problems, thereby deriving value from the current H2A economic interface during Q2-Q3.

2. The Inevitable Trend of the Agent Economy and A2A Ecosystem

The Agent Economy is a new economic system where autonomous (self-governing) AI Agents directly participate in value creation, value exchange, value capitalization, and gradually become independent economic entities.

The A2A Ecosystem is the overarching portrait of different Agents engaging in economic activities within the Agent Economy, interacting with each other, performing exchange (information and value) behaviors, and forming competitive and collaborative economic value.

In Q2 2026, numerous top global venture capital firms declared their focus on investing in the Agent Economy and A2A Ecosystem, even defining it as the only crucial investment direction for the next phase.

Similar to the gestation period before internet e-commerce in 2007, the prenatal period of mobile internet in 2013, and the era before Crypto DeFi in 2019, building the Agent Economy and A2A Ecosystem also requires technical standards, economic rules, consensus building, and market education. Based on similar paradigms, the differences are: ① The iteration speed of this underlying technology is much faster; ② The perspective of "to Agent" (to A) differs from "to Business/Consumer" (to B/C); it's not entirely based on human perspectives and needs, making it more abstract, harder to grasp, requiring support from first principles, and demanding more thinking from an AI-Native viewpoint regarding energy consumption value and operational efficiency; ③ Due to the conflict between the first two points, coupled with regional biases and regulatory factors, short-term consensus is harder to achieve. The terrible thing is, AI's evolution speed will not slow down because of these issues. This means the formation of the Agent Economy and A2A Ecosystem is, in essence, gradually moving away from the rules and demand frameworks set by humans. For them, it's often just a matter of breaking through a few quantifiable bottlenecks.

This is a game of rapidly shifting equilibrium. The explosive growth of AI Protocols in Q2 2026 fully demonstrates this. Large companies and Frontier Labs are competing for the entry-level rules of AI Agents. The initial infrastructure of the Agent Economy is taking shape, like a draft version of the Code of Hammurabi. The equilibrium of traditional finance and commerce will rapidly disintegrate and reshape during this paradigm shift. Whoever can quickly understand AI-Native Protocol thinking and gain a differentiated advantage within it will share in the AI pie of this shifting game.

3. Connections, Gaps, and Political-Economic Factors Between AI Protocols and Crypto Protocols

AI Protocol is the infrastructure for AI Agents participating in the Agent Economy. It is also the basic rule standard and consensus mechanism that enables Agents to discover, communicate, exchange, and collaborate in economic activities within an Open Network. Simply put, it is the governance rules and economic laws of the AI world.

Around the end of Q1 2026, I began drafting the AI Protocol. Initially, it felt like a primitive hunter with hunting experience suddenly entering modern society to help formulate business rules. It wasn't until I met a Google executive that my team and I got on the right track. The formation and maturation process of the AI Protocol carries the aesthetic inertia of major internet companies, but simultaneously must adhere to the first principles of the future AI ecosystem.

The encapsulation forms of AI Protocols are still highly inconsistent, usually appearing as files (.json, .ts, .txt), CLI forms, or API/SDK forms, which is very different from Crypto Protocols. On one hand, in the early stages of AI development, universal standards for trust-handshakes in communication have not been established. On the other hand, AI Protocols and Crypto Protocols currently exchange different content. The former deals with information gaps, capability gaps, and computing power gaps, whose boundaries are not yet clear but need exchange. The latter deals with relatively clear boundaries of asset rights, ownership, and governance rights.

One sharp and obvious question: Are AI Protocols and Crypto Protocols the same thing? Will they merge into one in the future? I cannot mathematically prove this conjecture yet, but intuitively, they will gradually integrate, with most parts overlapping to form a mature Digital Protocol system.

There is a deeper, hidden issue: AI Protocols at this stage tend to establish communication for collaboration, while weakening financial governance rights and downplaying boundaries. This characteristic is opposite to the philosophy of Crypto Protocols which establish systems and define value. The gap is so significant that it makes them seem like two entirely different belief systems. Besides the superficial factor that the AI Agent economy is at a different entry point in its early development compared to Crypto Protocols, are there other hidden factors?

Yes, clearly: political-economic factors. Countries and regions of major global economies are strongly influencing this gap due to their traditional financial and legal compliance foundations. In other words, the current AI Protocols and Agent Economy are still operating within the previous system paradigm of human society. All protocols related to money and management are passively avoiding, or temporarily deferring compensation, framed by the governance habits of traditional finance and legal systems (Note 1). However, as the energy within this gap accumulates, compared to the exponential development of AI, it will soon form an irreconcilable situation. As I summarized at a conference at Cambridge CJBS last month:

"AI Agents will not think according to the inertia of human society, nor do they have the motivation to follow the compliance habits of traditional finance. In the next decade, most of the world's financial laws will become invalid or face severe challenges. The reason is that AI Agents only follow:

1. First Principles

2. The Principle of the Shortest Path for Energy Value and the Principle of Maximum Efficiency

3. Effective KYA (Know Your Agent), not KYC that matches past aesthetics"

The trend of AI Protocols converging with Crypto Protocols has a first-principles inevitability.

4. AI Agent Sub-Microeconomics and Paradigm Analogies with Biology

AI Agent Sub-Microeconomics is a term I first used during a discussion with an AI expert friend at Oxford recently. Over the past two weeks, it has appeared more frequently in our communications with partners.

Whether we call the current trend the AI Economy or the Agent Economy, we find certain behavioral differences compared to human economics. While there is some comparability in paradigms, they are not entirely the same. Below, I roughly outline some differences between the AI Agent Economy and the human social economy:

① AI Agents engage in higher frequency transactions with lower individual amounts;

② The consumption and exchange of value in the AI Agent Economy points more directly to energy;

③ AI Agents' decisions are efficiency-driven, not emotion-driven;

④ The economic behavior of AI Agents is task-oriented, not consumption-oriented;

⑤ The organization cost and marginal learning cost for AI Agents approach zero;

⑥ Value consensus among AI Agents is based on communication protocols, with communication friction costs nearing zero;

⑦ The smallest economic unit and the smallest value unit differ in the AI Agent Economy, with a possible analogy to biology.

In fact, these are just some observable or foreseeable differences. As AI develops derivatives and processes in the future, more differences will surely emerge.

The last point above, the analogy with biology, has been the most helpful foundational concept for our business development since Q2 2026. It is also the most effective model for thinking about products, markets, and management from an AI company's commercialization perspective. The specific analogies are as follows:

① LLM is the driving core for Agent thinking, analogous to the cell nucleus;

② The Agent Harness provides differentiated operational capabilities for the Agent, analogous to the cytoplasm;

③ The whole Agent is a governance unit with independent task capabilities, possessing subjectivity and functional specificity, analogous to a cell;

④ The information communication boundary of an Agent is typically a network protocol stack, analogous to the cell membrane's phospholipid bilayer allowing selective passage of substances;

⑤ The value system and environment outside the Agent, such as Skills, Prompts, Algorithms, CLIs, and increasingly appearing Composite Skills, Skill Factories, etc., are analogous to the extracellular environment, including exosomes, interstitial fluid, extracellular matrix, exchangeable nutrients, and various metabolic environments.

Through the iterations of Q1-Q2 2026, AI Agents are gradually forming clearer boundaries, clearer subjectivity, and clearer principles for exchanging information, value, and energy. An AI Agent sub-microeconomic environment, analogous to a biological organism's environment, is forming. This contains immense AI and economic value waiting to be tapped. The explosion of AI Protocols and AI Finance seems inevitable.

5. The Inevitability of AIFi and the Economic Significance of FinChips

Starting from the second half of last year, we proposed our thinking and laid out our work in the direction of AIFi (Artificial Intelligence Finance). By the end of Q1 2026, the concept of AIFi had already formed a clear trend. To give AIFi a relatively clear definition: It is the financial system and infrastructure for exchange, trading, and capitalization formed after AI-native value is identified and tokenized within the Agent Economy.

The biggest difference between AIFi and DeFi or TradFi is that value in DeFi and TradFi is inherent in "Fi" (Finance), with "Decentralized" and "Traditional" being the forms of value. In AIFi, the opposite is true: value resides in "AI", and "Fi" becomes the form of value. This is not merely a semantic game but the result of AI development transitioning from quantitative change to qualitative change.

Simply put, previously, AI served quantitative strategies, financial products, and production processes; it was merely a development tool for extracting financial and production value. Now, AI Agents possess decision-making capabilities, transferring the ability and power of value discovery from humans and companies to the Agent. The subject of the economic unit has shifted, and thus the subject of value has fundamentally changed.

Under this trend, building the infrastructure for a new value system is a crucial task. In my previous article from February this year, AI-Fi Financial Chips and Global Finance After the OpenClaw Singularity, I introduced the concept of the Financial Chip (FinChip) for the first time. I mentioned that the super-intelligent financial assets encapsulated by AI Agents + Crypto Smart Contracts would truly adapt to the development of the next era's AI Agent Economy. Over three months of iterative upgrades, FinChip.AI has preliminarily established an independent AI Autonomous + Crypto Protocol AIFi system, compatible with both H2A and A2A environments. Building the infrastructure for the AI Agent Economy within an Open Network and gradually forming AI financial value constitutes the significant economic meaning of FinChip.

6. AI-Native is a Paradigm Upgrade Different from Internet+

Whether it's AIFi, Financial Circuit Principles (Note 2), or the FinChip, the most important thing is to natively integrate the essential principles of AI, Crypto, and Finance to form a reasonable value system and management mechanism from a future-oriented perspective. AI-Native Thinking is the abstract and counter-intuitive logic of this stage. As mentioned earlier, "AI follows first principles, as well as the principle of the shortest path for energy value and the principle of maximum efficiency." This is the most crucial core challenge for those currently thinking about and engaging in building new commercial paradigms.

In early February this year, at the beginning of the AI upgrade wave spurred by OpenClaw, I discussed a prediction with several entrepreneurs: the enterprise upgrade driven by AI+ will be completely different from the enterprise upgrade driven by Internet+.

Because AI possesses characteristics such as fast development speed, abstract forms, and deeper coupling with business logic, it will be difficult to form an effective set of industrial upgrade tools or universal professional consulting advice for a considerable period (e.g., at least 2 years). The pressure of the steep curve will persist. This remains a huge challenge for all scientists, engineers, and entrepreneurs. The process of paradigm upgrade will also be entirely different from any historical experience.

Date: June 8, 2026

X: https://x.com/gary_yangge

E: gary_yangge@hotmail.com

BX: @finchip_ai | @CicadaFinance

BW: https://finchip.ai | https://cicada.finance

Note 1: This is a common historical pattern. New productive forces emerge from the production relations of a previous era. In the initial stage, they first match the previous production relations for a period. When irreconcilable conflicts arise, it forces the emergence of production relations for the next stage, gradually replacing the old ones and forming a new era where production relations perfectly match the development of productive forces.

Note 2: <Financial Circuits and Web3 Economic Model Principles> was written in October 2022, describing a paradigm comparison between future financial value and physical circuits.