Author: Yang Ge Gary
Written in Singapore on June 8, 2026
The Singularity's outbreak has continuously accelerated AI's evolutionary clock, leading to the rapid formation of new civilization generational gaps across different regions of the globe. In the past two months, I have participated in over 20 AI-related events in more than ten cities worldwide. Only the Stripe Sessions in downtown San Francisco at the end of April stood out, creating a generational gap that was far more shocking than all other topics. While the world is growing weary of the single-machine bottlenecks of Claws & Agents, Silicon Valley and San Francisco have already moved into the next dimension in the management of Agent economy and Agent epistemology. The competitive pressure in Q3/Q4 of 2026 remains intense, with the exponential curve being very steep.
1. The Competition in AI Payment and the Bottleneck of the H2A Economy
In Q1 2026, we predicted that from April to May, many regions globally would enter fierce competition for AI Agent Payment, which would quickly become white-hot. The need for value exchange between Agents began to manifest initially, and the rapid development of AI Payment was validated in Q2. Following x402, multiple AI Payment Protocols like MPP rapidly emerged in Q2. Not only are traditional and Crypto financial payment companies upgrading to AI at full speed, but even major tech giants (especially like Google) and even old-school IT companies (such as IBM) have charged into this track, hoping to seize a voice in shaping the Agent world.
On the day of the Stripe Sessions in San Francisco, I discussed the standardization and application issues of Payment Protocols with technical leaders from several top AI companies. The results were reasonable but not entirely satisfactory: 1) No one could set the standard; consensus standards would only gradually form during the scramble. 2) Most completely agreed that Crypto is the inevitable path for AI Payment Protocol, but their starting point was Fiat API, partly due to inertia but more due to compliance hurdles. 3) KYC is both unavoidable and anti-Agent Native. 4) Everyone claims A2A (Agent to Agent), but everyone is actually doing H2A (Human to Agent).
In fact, during Q2 2026, many large tech firms and mid-sized companies in Silicon Valley were quite similar to their East Asian counterparts. Even most Department Heads in the Mag 7 were still approaching AI Payment and Agent Economy with to-B or to-C commercial goals, giving mid- and lower-level employees KPIs focused on human users. This inevitably led to the current, temporarily non-orthodox phase of Payment Protocols and the A2A economy. This H2A-oriented trend quickly hit a bottleneck in Q2. The reason is simple: the greatest characteristic of AI Agents is their ability to make decisions, yet 2B2C commerce developed under the internet and the H2A economy are essentially driven by human decisions. Using Agents to help humans make Fiat Payments in traditional e-commerce scenarios is logically Non-AI-Native. Therefore, at this stage, its value as a trending topic still outweighs its practical utility.
However, from another perspective, H2A has indeed served as an excellent primer, stimulating the transitional thinking toward the next stage of AI-Native and Agent Autonomous economies. By the end of Q2 2026, some astute companies realized this and began "repairing the plank roads openly while secretly crossing at Chencang"—using AI-Native Agent economic thinking to reconsider problems in reverse, finding that retrofitting current H2A economic interfaces is the optimal value proposition for the Q2-Q3 transition.
2. The Inevitable Trend of Agent Economy and the A2A Ecosystem
Agent Economy refers to a new type of 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 is the overall picture formed when different Agents participate in economic activities within the Agent Economy, interact with each other, conduct exchanges (of information and value), and form competitive-cooperative economic value.
In Q2 2026, many top global venture capital firms declared their focus on investing in the Agent Economy and A2A Ecosystem, even defining it as the only important investment direction for the next phase.
Similar to the incubation period before internet e-commerce in 2007, before mobile internet in 2013, and before 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 a similar paradigm, the differences are: 1) The speed of underlying technological development and iteration is faster this time. 2) The perspective of "to A" is different from "to B" or "to C"; it does not entirely stand from the human perspective and needs, making it more abstract, harder to understand, more reliant on first-principles thinking, and requiring consideration of energy value and operational efficiency from an AI-Native perspective. 3) Due to the conflict of the first two points, coupled with biases from different regions and compliance issues, short-term consensus is harder to achieve. The terrible thing is, AI's evolution speed will not slow down because of these various problems. That is to say, the formation of the Agent Economy and A2A Ecosystem is, in essence, gradually breaking away from the rule and demand frameworks dictated by humans. For them, it's mostly a matter of breaking through a few quantifiable bottlenecks.
This is a game of rapidly shifting Nash equilibrium. The rapid explosion of AI Protocols in Q2 2026 fully illustrates this. Major tech firms and frontier labs are scrambling for entry-level rules governing AI Agents. The initial infrastructure of the Agent Economy is taking shape, like a draft version of the Code of Hammurabi. The Nash equilibrium of traditional finance and commerce will quickly dissolve and reshape during this paradigm shift. Those who can quickly understand the AI-Native Protocol-oriented thinking and implement it to gain a differentiated advantage will get a share of the AI pie in this game shift.
3. The Connection, Gap, and Political-Economic Factors Between AI Protocol and Crypto Protocol
AI Protocol is the infrastructure for AI Agents to participate in the Agent Economy, and also the foundational rules, standards, and consensus mechanisms that enable Agents to discover, communicate, exchange, and collaborate in economic activities within an Open Network. Simply put, it is the governance rules and economic law of the AI world.
Since the end of Q1 2026, I started writing about AI Protocol. Initially, it was like a primitive with hunting experience suddenly arriving in modern society to participate in formulating commercial rules. It wasn't until I met a Google executive that my team and I quickly got on the right track. The formation and maturation process of AI Protocol carries the aesthetic inertia of internet giants, while also having to adhere to the first principles of the future AI ecosystem.
The encapsulation forms of AI Protocol are currently still quite inconsistent. They often come as document formats (.json, .ts, .txt), CLI formats, or as APIs or SDKs, which is very different from Crypto Protocol. On one hand, in the early stages of AI development, universal standards for establishing trust in communication handshakes have not been established. On the other hand, the content exchanged via AI Protocol and Crypto Protocol differs at this stage. The former deals with information gaps, capability gaps, and compute power gaps with boundaries that are not yet clear but need to be exchanged, while the latter deals with relatively well-defined asset rights, ownership, and governance rights.
A sharp and obvious question: Are AI Protocol and Crypto Protocol the same thing? Will they merge into one in the future? I cannot yet prove this conjecture with mathematical methods, but intuitively, they will gradually merge and largely overlap to form a mature Digital Protocol system.
There is a deeper hidden issue: At the current stage, AI Protocol tends to focus more on establishing communication to enable collaboration, while weakening financial governance power and diluting a sense of boundaries. This is the opposite of the Crypto Protocol ethos of establishing rights, defining ownership, and valuing clear demarcation. The gap is so significant that it makes them seem like two different philosophies. Besides the surface factor that the AI Agent Economy is in its early developmental stage with different entry points compared to Crypto Protocol, are there other hidden factors behind this phenomenon?
Yes, very clearly, political-economic factors. The traditional financial and legal compliance foundations of the mainstream economies and nation-states are strongly influencing this gap issue. In other words, the current AI Protocol and Agent Economy are still operating within the previous systemic paradigm of human society. All Protocols related to money and management are passively回避规避, or temporarily and compensatorily weakened, being framed by the governance habits of the traditional financial and legal systems (Note 1). However, as the energy of this gap difference accumulates, contrasted with the exponential development of AI, it will soon form an irreconcilable situation. As I summarized at 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 the compliance habits of traditional finance. In the next decade, most of the world's financial laws will become失效失效 or face intense challenges, because AI Agents only follow:
1. First Principles
2. The principle of the shortest energy-value path and the highest efficiency principle
3. Effective KYA rather than KYC符合符合 past aesthetics"
The trend of AI Protocol merging with Crypto Protocol has a first-principles inevitability.
4. Paradigm Analogy of AI Agent Sub-Microeconomics and Biology
AI Agent Sub-Microeconomics is a term I first used during a discussion with an AI expert friend at Oxford not long ago. In the past half month, it has appeared more frequently in our exchanges with partners.
Regardless of whether the current trend is called AI Economy or Agent Economy, we find that their behavioral characteristics possess certain differences compared to human economics. While there is a certain paradigm comparability, they are not entirely the same. Below, I roughly list some distinctions between the AI Agent Economy and human societal economics:
1) The frequency of AI Agent interaction and transactions is higher, with lower amounts per transaction.
2) The consumption and exchange of economic value by AI Agents point more directly to energy.
3) AI Agent decisions are 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) AI Agent value consensus is based on communication protocols, with communication friction costs nearly zero.
7) The minimal economic unit and the minimal value unit in the AI Agent Economy are different, analogous to biology.
In fact, these are just some differences that are currently observable or foreseeable. More differences will certainly emerge in the derivatives and derivative processes of AI's future development.
The last item in the above distinctions, the analogy with biology, has been the most helpful foundational line of thinking for our business development since Q2 2026. It is also the most effective model for commercializing AI companies' thinking regarding products, markets, and management methods. The specific analogies are as follows:
1) The LLM, as the driving kernel for Agent thinking, is analogous to the cell nucleus.
2) The Agent Harness brings differentiation in Agent operational capabilities, analogous to the cytoplasm.
3) The Agent as a whole is an autonomous governance unit with task-specific 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 conditional passage of substances.
5) The value systems 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.
In the developmental iterations of Q1-Q2 2026, AI Agents are gradually forming clearer boundaries, clearer subjectivity, and clearer principles for the exchange of information, value, and energy. An AI Agent Sub-Microeconomics environment, analogous to a biological organism's environment, is taking shape. This contains a wealth of AI value and economic value to be mined, making AI Protocol and AI Finance an inevitable trend for explosion.
5. The Inevitability of AIFi and the Economic Significance of the Financial Chip (FinChip)
Starting from the second half of last year, we proposed thoughts and began layout work in the direction of AIFi (Artificial Intelligence Finance). By the end of Q1 2026, the concept of AIFi had formed a clear trend. A relatively clear definition of AIFi could be: the financial systems 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/TradFi is that in DeFi and TradFi, the value resides in the "Fi" (i.e., Finance), with "Decentralized" and "Traditional" being the forms of that value. In contrast, AIFi is the opposite: the value is in the "AI," and the "Fi" becomes the form of that value. This is not merely wordplay; it is the result of AI development shifting from quantitative to qualitative change.
Simply put, previously, AI served quantitative strategies, financial products, and production processes; it was merely a development tool for extracting financial value and production value. But now, the decision-making capability possessed by AI Agents transfers the ability and power of value discovery from human and corporate hands to the Agents themselves. The subject of the economic unit has shifted, so the subject of value has also fundamentally changed.
Under such a trend, constructing the infrastructure for a new value system will be a crucial task. In my previous article in February of this year,
6. AI-Native is a Paradigm Upgrade Different from Internet+
Whether it's AIFi, Financial Circuit Principles (Note 2), or the Financial Chip FinChip, the most important thing is to Natively integrate the essential principles of AI, Crypto, and Finance, forming a reasonable value system and management mechanism from a future 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 energy-value path and the highest efficiency principle." This is the core difficulty for those currently thinking about and engaging in the construction of new commercial paradigms.
During the early phase of this round's AI upgrade outbreak led by OpenClaw in February this year, several entrepreneurs and I discussed a prediction: Enterprise upgrades through "AI+" and those through "Internet+" would be completely different.
Due to AI's characteristics of rapid development speed, abstract form, and deeper coupling with affairs, among others, for a considerable period (e.g., at least 2 years), it will be difficult to form a set of effective industrial upgrade tool methodologies or universal professional consulting advice. The pressure of the steep curve will persistently exist, posing a巨大巨大 challenge for all scientists, engineers, and entrepreneurs. The process of paradigm upgrade will also be completely unlike any historical experience.
Note1: This is a common historical规律规律. New productive forces孕育孕育 from the production relations of the previous era. In the initial stage, they first match the previous production relations for a period of development. Until they become irreconcilable, they force the emergence of the next stage's production relations, gradually replacing the previous ones to form a new era where productive forces and production relations develop in complete匹配匹配.
Note2:<Financial Circuits and Web3 Economic Model Principles> written in October 2022, describes the paradigm comparison between future financial value and physical circuits.
