Author: Gary Yang, founder of Xinghan Capital

Written on June 8, 2026 in Singapore

After the Singularity, the evolution clock of AI is accelerating continuously, rapidly forming new generations of civilization across different regions of the world. In the past two months, I participated in more than 20 AI-related events in over ten cities globally, with only the Stripe Sessions in downtown San Francisco at the end of April surpassing all other themes, revealing a shocking intergenerational gap. While the world is growing tired of the bottleneck of Claws & Agents, both Silicon Valley and San Francisco have already entered a new dimension in managing the Agent economy and Agent epistemology. The competition pressure in the third and fourth quarters of 2026 remains intense, with very steep index curvature.

1. The competition of AI Payment and the bottleneck of H2A economy

In Q1 of 2026, we predicted that numerous locations worldwide would enter a fierce competition for AI Agent Payment between April and May, rapidly heating up. The demand for value exchange among Agents gradually emerged, and the rapid development of AI Payment was confirmed in Q2. After x402, several AI Payment Protocols, including MPP, rapidly emerged in Q2, not only traditional and Crypto financial payment companies are accelerating their AI transformation, but also large corporations (especially like Google) and even established IT companies (like IBM) have rushed into this track 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 Protocol with several technical leaders from top AI companies; the results were reasonable but not entirely satisfactory:

• ① No one can establish standards; only through the process of seizing will a consensus standard gradually form;
• ② Most people completely agree that Crypto is inevitable as an AI Payment Protocol, but what they actually engage with are Fiat APIs, partly due to inertia but more so due to compliance obstacles;
• ③ KYC is both unavoidable yet opposed to being Agent Native;
• ④ Everyone claims A2A (Agent to Agent), while everyone is practicing H2A (Human to Agent).

In fact, in Q2 of 2026, many of the big companies in Silicon Valley and mid-tier companies are quite similar to those in East Asia, with most Department Heads of Mag 7 still pursuing AI Payment and Agent Economy's hot issues for B2B and B2C commercial purposes, giving mid-level performance indicators based on to Human Users, which inevitably leads to the current temporary non-orthodoxy of the Payment Protocol and A2A economy. This H2A-driven trend soon encountered a bottleneck in Q2, for a simple reason: the greatest feature of AI Agents is the ability to make decisions, whereas the essence of both B2B2C commercial and H2A economy is that decisions are still made by humans. Using Agents to help humans make Fiat Payments in traditional e-commerce scenarios is, by its very logic chain, Non-AI-Native, hence for now, it is still a matter of the hot value outweighing practicality.

However, from another perspective, H2A indeed serves as a good introductory role, inspiring thoughts on the next stage of AI-Native and Agent Autonomous economic transition. By the end of Q2 of 2026, some clever enterprises realized this and began to "repair the bridge while secretly crossing the river," using AI-Native thinking in the Agent economy to rethink the issues and backtrack to find that the best value of H2A economic interfaces is in Q2-Q3.

2. The inevitable trend of Agent economy and A2A ecosystem

Agent economy refers to a new type of economic system in which 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, interacting and exchanging information (value) with each other, forming a general image of cooperative economic value.

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

Similar to the prelude periods of 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 technological standards, economic rules, consensus building, and market education. On a fundamentally similar paradigm, the differences are: ① This time, the iterative speed of essential technological development is faster; ② The perspectives of to A and to B to C are different and do not entirely stand on human viewpoints and needs, being more abstract and harder to understand, requiring more support from first principles, especially emphasizing energy consumption value and operational efficiency from an AI-Native perspective; ③ Due to the conflicts caused by the above two points, coupled with biases and compliance issues across different regions, achieving short-term consensus is more challenging. The terrible thing is, the evolutionary speed of AI will not slow down due to these various issues, which means the formation of the Agent economy and A2A ecosystem is essentially gradually detaching from the rules and demand framework designated by humans; for them, it is often just a matter of breaking through several quantifiable bottlenecks.

This is a game of rapidly shifting equilibrium. The rapid explosion of AI Protocol in Q2 of 2026 fully illustrates this point. Large companies and frontier labs are scrambling for the entry-level rules of AI Agents, and the initial infrastructure of the Agent economy is beginning to take shape, much like a draft version of Hammurabi's Code. The equilibrium of traditional finance and business will quickly collapse and be reshaped during this paradigm shift. Whoever can quickly understand AI-Native protocol thinking and implement it to gain a differentiated advantage will seize their share of the AI cake in this shift of equilibrium.

3. The relation, gap, and political economic factors between AI Protocol and Crypto Protocol

AI Protocol is the infrastructure for AI Agents participating in the Agent economy; it is also the foundational rule standards and consensus mechanisms enabling Agents to discover, communicate, exchange, and collaborate in economic activities on the Open Network; simply put, it comprises the governance rules and economic laws of the AI world.

Since the end of Q1 of 2026, I have started working on the AI Protocol, which initially felt akin to a primitive person with hunting experience suddenly entering modern society to participate in commercial rule-making, until encountering a Google executive who helped me and my team get back on track quickly. The formation and maturation process of the AI Protocol carries the aesthetic inertia of large internet companies but must also adhere to the first principles of the future AI ecosystem.

Currently, the encapsulation forms of AI Protocol are still quite diverse, typically consisting of file forms (.json, .ts, .txt), CLI forms, and API or SDK forms, which are 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, AI Protocol and Crypto Protocol differ in the interaction and exchange of content at this stage—the former seeks to exchange information gaps, capability disparities, and computational power differences with unclear boundaries, while the latter deals with relatively clear 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 currently prove this conjecture using mathematical methods, but intuitively, they will gradually integrate, and many parts will overlap, forming a mature Digital Protocol system.

There is a deeper hidden issue: At the current stage, AI Protocol is more inclined to establish communication for collaboration, while downplaying the features of financial governance power and blurring boundary perceptions, which is in stark contrast to Crypto Protocol’s philosophy of defining values through institutional rights. The gap is so pronounced that it leads one to believe they stem from two different ideologies. Apart from the apparent factors that the AI Agent economy is at an early developmental entry point distinct from Crypto Protocol, are there any hidden factors behind this?

Yes, it is quite clear—the political economic factors. Countries and regions comprising the world’s mainstream economies, grounded in traditional finance and legal compliance, are strongly influencing this gap issue. In other words, the current AI Protocol and Agent economy still operate under the previous systemic paradigm of human society; all Protocols related to money and management are passively avoiding or are temporarily weakened due to compensation frameworks governed by traditional finance and legal systems. However, with the accumulation of energy in the gap, compared to the rapid growth of AI, an irreconcilable situation will soon form, much like I summarized at a meeting at Cambridge CJBS last month:

“AI Agents will not think according to human societal inertia, nor do they have the motivation to adhere to traditional financial compliance habits. In the next decade, a majority of global financial laws will become ineffective or face severe challenges, because AI Agents only adhere to:

1. First principles

2. The principle of shortest path energy value and highest efficiency principle

3. Effective KYA instead of past aesthetic KYC”

The trend of integration from AI Protocol to Crypto Protocol is inherently driven by first principles.

4. The paradigm analogy between AI Agent microeconomics and biology

AI Agent microeconomics is a descriptor I first used recently while discussing with an AI expert friend in Oxford, which has since appeared more frequently in our communications with partners over the past half month.

Whether the current trend is labeled AI economy or Agent economy, we find that they exhibit certain behavioral characteristics that differ from human economics. Although there are some paradigmatic similarities, they are not entirely the same. Below I roughly outline some differences between the AI Agent economy and human social economics:

① AI Agents interact and transact at a higher frequency and with lower single transaction amounts;

② The economic value consumption and exchange of AI Agents directly point 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 costs and marginal learning costs of AI Agents approach zero;

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

⑦ The minimal economic unit and minimal value unit of AI Agent economics differ, allowing for a biological analogy.

In fact, these are just some distinctions currently visible or foreseeable; as AI continues to evolve, more differences are bound to emerge.

The last of the aforementioned distinctions, relating to the biological analogy, has become the cornerstone thought most beneficial to our business development since Q2 of 2026, also the most effective model for AI companies thinking about product, market, and management methods. Specific analogies are as follows:

① LLM as the core driving force of Agent thought, 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, akin to a cell;

④ The information communication boundaries of Agents typically align with a network protocol stack, akin to the lipid bilayer of cell membranes that conditionally allow material passage;

⑤ The value systems and environments outside of Agents, such as Skills, Prompts, Algorithms, CLI, and increasingly more Composite Skills, Skill Factories, etc., resemble the extracellular environment, including extracellular vesicles, tissue fluids, extracellular matrices, exchangeable nutrients, and various metabolic environments.

In the iterative development from Q1 to Q2 of 2026, AI Agents are gradually forming clearer boundaries, more defined subjectivity, and clearer principles of information, value, and energy exchange. An AI Agent microeconomic environment resembling a biological organism's environment is taking shape, embodying vast AI value and economic value that can be unearthed; AI Protocol and AI Finance are inevitable trends of explosion.

5. The inevitability of AIFi and the economic significance of the financial chip FinChip

Since the second half of last year, we have initiated thinking and layout work in the direction of AIFi (Artificial Intelligence Finance), and by the end of Q1 of 2026, the concept of AIFi has formed a clear trend. If we were to give AIFi a relatively clear definition, it would be: AI native value recognized and tokenized within the Agent economy, forming the financial systems and infrastructures of exchange transactions and capitalization.

The key distinction between AIFi and DeFi and TradFi lies in the fact that the value embedded in DeFi and TradFi is in Fi (i.e., Finance), while Decentralized and Traditional are merely forms of value; in contrast, AIFi's value exists in AI, while Fi becomes the form of value. This is not a mere verbal game but a result of the developmental transition of AI from quantitative change to qualitative change.

In simple terms, previously, AI served quantitative strategies, financial products, and production processes; it was simply a development tool for refining financial and production values. Today, however, the decision-making capabilities possessed by AI Agents have shifted the capacities and powers of value discovery from humans and companies to the Agents themselves, thereby altering the essence of the economic units.

In light of this trend, constructing the infrastructure for a new value system will be an important task. In an article published in February earlier this year titled "AI-Fi Financial Chip and Global Finance after OpenClaw Singularity" (Related Reading:AI-Fi Financial Chip and Global Finance After Openclaw Singularity, How to Avoid Being Left Behind?), I first introduced the concept of a financial chip (FinChip) and noted that the super smart financial assets created by combining AI Agents with Crypto Smart Contracts 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 established an independent AIFi system that integrates AI Autonomous and Crypto Protocol, and is compatible with the dual-phase environments of H2A and A2A; building the infrastructure for the AI Agent economy within the Open Network and gradually forming AI financial value is the economic significance of FinChip.

6. AI-Native as a paradigm upgrade distinct from Internet+

Whether it is AIFi, the principles of financial circuits (note 2), or the financial chip FinChip, the most important aspect is the need to natively integrate the essence of AI, Crypto, and Finance, forming a value system and management mechanism that are reasonably designed from a future perspective. AI-Native Thinking is the abstract yet counterintuitive logic of this stage, much like what was mentioned earlier: “AI follows first principles, as well as the principle of shortest path energy value and highest efficiency principle,” which is the most critical core challenge for current thoughts and endeavors in constructing new business paradigms.

In February this year, during the early phase of the AI upgrade explosion spearheaded by OpenClaw, I and several entrepreneurs contemplated a prediction: the upgrades of AI+ enterprises will be vastly different from the Internet+ enterprise upgrades.

Due to AI's rapid development speed, abstract forms, and deeper coupling with affairs, it will be extremely challenging to establish a set of effective industrial upgrade tool methodologies or general professional consulting opinions for a long time (for at least two years). The steep pressure will always exist, posing a significant challenge to all scientists, engineers, and entrepreneurs; the process of paradigm upgrading will be completely different from any past historical experiences.

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。