Yang Ge Gary: Agent Economics and AI Microeconomics

Author: Yang Ge

After the singularity explosion, the evolution clock of AI has been accelerating, leading to the rapid formation of new civilizational generations in different regions around the world. In the past two months, I participated in over 20 AI-related events in more than ten cities globally, and only the Stripe Sessions in downtown San Francisco at the end of April surpassed all other themes, revealing a shocking generational gap. While the world is growing weary of the bottleneck of Claws & Agents, Silicon Valley and San Francisco have already entered the next dimension in managing the Agent economy and Agent cognition, with the competitive pressure of Q3 and Q4 in 2026 still intense and the curvature of the index very steep.

tl;dr

1. Competition in AI Payment and the bottleneck of the H2A economy

++2. Agent++ ++economy and++ ++A2A++ ++ecosystem's inevitable trend++

++3. AI Protocol++ ++and++ ++Crypto Protocol++ ++relationship, gap, and political economic factors++

++4. AI Agent++ ++microeconomic characteristics and biological paradigm analogy++

++5. AIFi++ ++inevitability and the economic significance of financial chips++ ++FinChip++

6. AI-Native is a paradigm upgrade different from Internet+

1. Competition in AI Payment and the bottleneck of the H2A economy

In Q1 2026, we predicted that many regions around the world would enter a fierce competition for AI Agent Payment in April and May, rapidly heating up. The demand for value exchange among Agents has begun to manifest, and the rapid development of AI Payment was validated in Q2. After x402, multiple AI Payment Protocols like MPP emerged quickly in Q2, not only traditional and Crypto financial payment companies are accelerating their AI upgrades, but also major companies (especially like Google) and even established IT companies (like IBM) have rushed into this track hoping to seize the discourse power in the Agent world.

On the day of the Stripe Sessions in San Francisco, I discussed the standardization and application issues of Payment Protocols with several technical leaders from top AI companies. The results were reasonable but not satisfying: ① No one can set standards; only through the process of seizing can consensus standards gradually form; ② Most people completely agree that Crypto is an inevitability for AI Payment Protocol, but they are all starting with Fiat APIs, partly due to inertia and more due to compliance obstacles; ③ KYC is both unavoidable and anti-Agent Native; ④ Everyone claims A2A (Agent to Agent), but everyone is doing H2A (Human to Agent).

In fact, in Q2 2026, many large and mid-sized companies in Silicon Valley and East Asia are quite similar, and even most Department Heads in Mag 7 still approach AI Payment and Agent Economy from a B2B to B2C commercial purpose, giving middle and lower-level KPIs focused on to Human Users, which inevitably leads to the current temporary non-orthodoxy of Payment Protocol and A2A economy. This H2A-oriented wind quickly encountered a bottleneck in Q2, and the reason is simple: the biggest feature of AI Agents is their ability to make decisions, while the essence of B2B2C business and H2A economy is that humans are making decisions. Using Agents to help humans make Fiat Payments in traditional e-commerce scenarios is logically Non-AI-Native, so at this stage, the hot value still outweighs practicality.

However, from another perspective, H2A has indeed played a very good introductory role, stimulating the transition to the next stage of AI-Native and Agent Autonomous economic entities. By the end of Q2 2026, some smart companies realized this and began to "openly repair the road while secretly crossing the river," thinking backward with AI-Native Agent economic thinking to reverse-engineer the current H2A economic interface, which is the best value for Q2-Q3.

2. Agent economy and A2A ecosystem's inevitable trend

++Agent++ ++economy++ refers to a new economic system where autonomous (self-governing) AI Agents directly participate in value creation, value exchange, and value capitalization, gradually becoming independent economic entities.

++A2A++ ++ecosystem++ involves different Agents participating in economic activities within the Agent economy, facing each other, interacting (exchanging information) and engaging in value exchange behaviors, forming an overall picture of competitive cooperation economic value.

In Q2 2026, many top venture capital institutions globally declared their emphasis on investing in the Agent economy and A2A ecosystem, even defining this as the only important investment direction for the next stage.

Similar to the incubation periods before the internet e-commerce in 2007, mobile internet in 2013, and Crypto DeFi in 2019, the construction of the Agent economy and A2A ecosystem also requires technical standards, economic rules, consensus building, and market education. On the basis of fundamentally similar paradigms, the differences are: ① This time, the iterative speed of essential technology development is faster; ② The perspectives of to A and to B to C are different, not entirely standing on human perspectives and needs, being more abstract and harder to understand, requiring more support from first principles, and needing to think about energy value issues and operational efficiency from an AI-Native perspective; ③ Due to the conflicts of the first two points, along with biases and compliance issues in different regions, achieving short-term consensus is more difficult. The terrible thing is that the evolution speed of AI will not slow down due to these issues, meaning that the formation of the Agent economy and A2A ecosystem is gradually detaching from the rules and demand frameworks designated by humans, and for them, it is more about breaking through a few quantifiable bottlenecks.

This is a game where the equilibrium of the game quickly shifts. The rapid explosion of AI Protocol in Q2 2026 fully illustrates this point. Major companies and Frontier Labs are competing for the entry-level rules of AI Agents, and the initial infrastructure of the Agent economy is forming, akin to a draft version of the Code of Hammurabi. The equilibrium of traditional finance and business will rapidly collapse and reshape in this paradigm shift. Those who can quickly understand AI-Native protocol thinking and implement it to gain differentiated advantages will be able to share in the AI cake of this game shift.

3. AI Protocol and Crypto Protocol relationship, gap, and political economic factors

++AI Protocol++ is the infrastructure for AI Agents to participate in the Agent economy, and it establishes the basic rules and consensus mechanisms for Agents to discover, communicate, exchange, and collaboratively participate in economic activities within the Open Network; simply put, it is the governance rules and economic laws of the AI world.

Since the end of Q1 2026, I began drafting the AI Protocol, initially likening it to a primitive person with hunting experience suddenly participating in the formulation of business rules in modern society, until I met a Google executive who helped my team quickly get on the right track. The formation and maturation process of the AI Protocol carries the aesthetic inertia of major internet companies, while also needing to adhere to the first principles of the future AI ecosystem.

The encapsulation forms of AI Protocol are still very non-unified, typically appearing in document forms (.json, .ts, .txt), CLI forms, and also API or SDK forms, which is very different from Crypto Protocol. On one hand, in the early stages of AI development, many trust handshakes for communication have not established universal standards; on the other hand, the content exchanged between AI Protocol and Crypto Protocol at this stage is different, with the former dealing with unclear boundaries but needing to exchange information gaps, capability gaps, and computing power gaps, while the latter deals with relatively clearer boundaries of asset rights, ownership, and governance rights.

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

There is a deeper hidden issue: AI Protocol at the current stage tends to establish communication for collaboration while weakening the financial governance power and blurring boundaries, which is in direct contrast to the Crypto Protocol's concept of defining value through institutional rights. The gap is so obvious that it makes one think they are two different ideologies. This phenomenon, aside from the surface factor that the AI Agent economy is at an early developmental entry point different from Crypto Protocol, are there any hidden factors?

Yes, it is very clear: political economic factors. Countries and regions of mainstream global economies, due to the foundation of traditional finance and legal compliance, are strongly influencing this gap issue. In other words, the current AI Protocol and Agent economy are still operating under the previous systemic paradigm of human society, and all protocols related to money and management are passively avoiding or are temporarily weakened and compensated by the governance habits of traditional finance and legal systems (Note 1). However, with the accumulation of energy from the gap differences, compared to the rapid development of AI, an irreconcilable situation will soon form, just as I summarized in a meeting 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 traditional financial compliance habits. In the next decade, most global financial laws will become ineffective or face severe challenges because AI Agents only follow:
++1.++ *++first principles
2.++ ++the shortest path principle of energy value and the highest efficiency principle
3.++ ++effective KYA instead of KYC that conforms to past aesthetics."

The trend of AI Protocol merging into Crypto Protocol is inevitable based on first principles.

4. AI Agent microeconomics and biological paradigm analogy

AI Agent microeconomics is a term I first used during a discussion with an AI expert friend in Oxford not long ago, and it has gradually appeared more frequently in our communications with partners over the past half month.

Whether the current trend is called AI economy or Agent economy, we will find that they exhibit certain differences in behavioral characteristics compared to human economics. Although there are some comparable paradigms, they are not entirely the same. Below, I roughly outline some differences between the AI Agent economy and human social economy:

① AI Agents interact and trade more frequently, with lower individual transaction amounts;

② The consumption exchange of economic value in the AI Agent economy directly points to energy;

③ AI Agent decision-making is efficiency-driven rather than emotion-driven;

④ AI Agent economic behavior is task-oriented rather than consumption-oriented;

⑤ The organizational cost and marginal learning cost of AI Agents approach zero;

⑥ The value consensus of AI Agents is based on communication protocols, with communication wear and tear costs nearly zero;

⑦ The minimum economic unit of the AI Agent economy differs from the minimum value unit, which can be analogized to biology.

In fact, these are just some currently observable or foreseeable differences. In the derivatives and evolution of AI's future development, more differences will certainly emerge.

The last point of the above differences, the analogy with biology, has been the cornerstone thought that has helped our business development the most since Q2 2026, and it is the most effective model for AI companies to think about product, market, and management methods. Specific analogies are as follows:

① LLM as the driving core of Agent thinking, similar to a cell nucleus;

② Agent Harness brings differentiated operational capabilities to Agents, similar to cytoplasm;

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

④ The communication boundary of Agents is typically a set of network protocol stacks, similar to the phospholipid bilayer of cell membranes allowing conditional passage of substances;

⑤ The value systems and environments outside of Agents, such as Skills, Prompt, Algorithm, and the increasingly emerging Composite Skills, Skill Factories, etc., are similar to the extracellular environment, including extracellular vesicles (Exosomes), tissue fluid, extracellular matrix, exchangeable nutrients, and various metabolic environments.

In the development iteration from Q1 to Q2 2026, AI Agents are gradually forming clearer boundaries, clearer subjectivity, and clearer principles of information, value, and energy exchange. An AI Agent microeconomic environment similar to a biological organism is forming, containing a wealth of AI value and economic value to be explored, and AI Protocol and AI Finance are inevitable trends for explosion.

5. AIFi inevitability and the economic significance of financial chips FinChip

Since the second half of last year, we have proposed thoughts and layout work in the direction of AIFi (Artificial Intelligence Finance), and by the end of Q1 2026, the concept of AIFi has formed a clear trend. If we give AIFi a relatively clear definition, it can be: AI native value recognized and tokenized in the Agent economy, forming a financial system and infrastructure for exchange and capitalization.

The biggest difference between AIFi and DeFi and TradFi is that the value in DeFi and TradFi is contained in Fi (i.e., Finance), where Decentralized and Traditional are the forms of value; whereas AIFi is the opposite, where value resides in AI and Fi becomes the form of value. This is not a simple word game, but the result of AI development 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; whereas now, the decision-making capability of AI Agents has shifted the ability and power of value discovery from humans and companies to Agents, thus the subject of economic units has migrated, and the essence of value subjects has also changed.

In this trend, building the infrastructure for a new value system will be an important task. In a previous article in February titled , I first introduced the concept of financial chips (FinChip) and mentioned that the combination of AI Agent + Crypto Smart Contract encapsulated super-intelligent financial assets will truly adapt to the development of the next era of the AI Agent economy. After three months of iterative upgrades, FinChip.AI has initially developed an independent AI Autonomous + Crypto Protocol AIFi system, compatible with both H2A and A2A dual-phase environments; building the infrastructure for the AI Agent economy in the Open Network and gradually forming AI financial value is an important economic significance of FinChip.

6. AI-Native is a paradigm upgrade different from Internet+

Whether it is AIFi, financial circuit principles (Note 2), or financial chips FinChip, the most important thing is to natively integrate the essential principles of AI, Crypto, and Finance to form a value system and management mechanism that is reasonable from a future perspective. AI-Native Thinking is the abstract and counterintuitive logic of this stage, just as mentioned earlier, "AI follows first principles, as well as the shortest path principle of energy value and the highest efficiency principle," which is the most important core difficulty for current thinking and engaging in the construction of new business paradigms.

At the beginning of this year's AI upgrade explosion driven by OpenClaw in February, I discussed a prediction with several entrepreneurs: the upgrade of AI+ enterprises and the upgrade of Internet+ enterprises will be completely different.

Due to AI's rapid development speed, abstract forms, and deeper coupling with affairs, it will be very difficult to form a set of effective industrial upgrade tools or universal professional consulting opinions for a long time (for at least 2 years). The pressure of steep curvature will always exist, posing a huge challenge for all scientists, engineers, and entrepreneurs, and the process of paradigm upgrade will be completely different from any historical experience.

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