Identification, Recourse, Attribution: Decoding the Three Key Breakthroughs of the Next Generation AI Agent Economy

Written by: Decentralised.co

Compiled by: AididaoJP, Foresight News

In the article “Internet Pricing”, we discussed that when measuring payments is frictionless, machines will automatically make payments. Humans have failed to fully embrace micropayments because paying attention to the measuring process requires effort and mental energy. But machines are different; they only see 1s and 0s. Mental capacity or task switching does not affect their execution ability. If breaking down to sub-cent levels makes the process more efficient, they will do so, which is different from humans.

In the last article, we ended with a question: What should we do when an agent messes things up? Whether the agent's intentions are correct is not important. The key point is that we cannot supervise the agent at every step.

This puts us in a dilemma: the new technology has failed to inherit a major advantage of the old infrastructure, such as the ability to reverse payments in case of errors. This article will explore this issue. We will discuss what is needed for agents to achieve autonomy, who is building the infrastructure for this, and why new startups are emerging at the intersection of blockchain payment channels and autonomous agents.

Emerging Standards

Any commercial activity involves three parties: the buyer, the seller, and the intermediary that facilitates the transaction. The intermediary can be a platform or marketplace like Amazon, or a card organization network that processes payments like Visa.

Buyer

Consumer applications are typically responsible for handling funds or transactions and taking a cut from them. But what happens when the consumer is an AI acting on our behalf? There are several emerging standards currently seeking answers.

ChatGPT has 700 million active users, all trying to obtain information or services through AI. Although we have not yet directly bought and sold goods through an agency interface, it is commonly used to “discover” products. Whether buying running shoes or looking for hotels in El Calafate, I am using AI to compare prices. If I could purchase directly on the same interface, it would undoubtedly be much more convenient. This is precisely the purpose of OpenAI's collaboration with Stripe to launch the Autonomous Agent Commercial Protocol (ACP).

Source: OpenAI

This is currently the most direct way for agents to handle funds: users have full control throughout the process. After placing an order, ChatGPT sends the necessary information to the merchant's backend via ACP. The merchant then decides whether to accept or reject the order, processes the payment through the original payment service provider, and handles shipping and customer service as usual.

You can think of the ACP business as: you authorize an intern to spend a fixed budget, and you ultimately decide which product/service to purchase and from which merchant to complete the payment.

OpenAI and Stripe have ACP, while Google has launched the Agent Payment Protocol (AP2). Before diving into AP2, let's take a step back. What Google wants to solve is the “interoperability” issue. Currently, AI agents are operating in silos: Gemini doesn't communicate with Claude, and ChatGPT is unaware of what is happening in Perplexity.

Ideally, when tasks become complex and require collaboration, we hope that these agents can communicate in a common language. To this end, Google developed A2A (Agent-to-Agent Protocol) to allow different agents to communicate and coordinate.

But just being able to converse is not enough. Agents also need to be able to use tools, access APIs, and services. The Model Context Protocol (MCP) allows agents to use tools like Google Calendar, Notion, Figma, etc.

Source: Level Up Coding

MCP defines a universal language. As long as everyone “speaks” MCP, agents can use any tools without the need for additional customized code. The protocol was created by Anthropic, but the specifications are open and are being rapidly adopted by various companies. The MCP server essentially acts as a translation layer, sitting in front of the company's existing APIs, exposing services in a standardized format to any MCP-compatible agents.

Back to AP2, it can be simply understood as follows: MCP gives agents the ability to access data, files, and tools; A2A gives them a voice to communicate with each other; while AP2 provides them with a wallet, allowing them to spend money securely.

All these protocols put users at the control center, with agents having only limited consumption rights. This addresses the distribution and process issues, but it still hasn't solved: what to do when the agent makes a mistake?

Seller

The story is not only happening on the buyer's side. Sellers are also emerging with new standards, focusing on how machines pay for access to APIs, data, and content.

The most discussed topic at the moment is the x402 standard, an open protocol developed by Coinbase. It revives the HTTP status code 402 - “Payment Required” - which was defined back in 1997 but never used. The x402 gives new life to this status code by combining it with stablecoin payments, allowing microtransactions to be settled economically.

x402 turns HTTP requests into paid requests. Whenever payment is required, the server will make a request. Since the proxy has a preset budget, it will pay the server and obtain data in the same process. This makes “pay-per-request” or “pay-per-call” feasible in machine-to-machine transactions.

With x402, agents can make precise payments for what is needed at the moment. For example, pay 2 cents to read a paid article, or pay a fraction of a cent for an API call. Transactions can be settled on-chain within seconds, without the need to establish long-term relationships.

Source: Coinbase's x402 paper

Cloudflare draws on this concept to build a more specific “pay-per-capture” system. Its underlying technology also uses HTTP 402, but the key lies in Cloudflare's market dominance, as 20% of global internet traffic passes through its network, giving it immense influence.

“Pay-per-crawl” utilizes Cloudflare's edge network to require payment before providing content to AI crawlers. This turns access to content into a mandatory measurement. Publishers are facing a dramatic drop in traffic as people are no longer entering websites from search engines, but instead directly reading AI-generated summaries. With this system, publishers can charge AI labs directly each time a crawler accesses their content.

Card networks are also attempting to expand existing payment channels to handle agent transactions. Visa has launched the MCP server and the Acquirer Agent Toolkit. Mastercard has a project called “Agent Payment.” Both are in the early pilot stage, but they are important because Visa and Mastercard already have a global distribution network, relationships with issuing banks, and a wide merchant acceptance network. The basic idea is: register agents, set spending controls, allowing agents to initiate transactions on the existing human credit card payment network.

Urgently need to fill the trust gap

All the above standards assume that payments will proceed smoothly and that the results will meet expectations. ACP and AP2 involve human participation in the checkout process, providing a certain level of security. The x402 variant deals with machine-to-machine data access, which typically carries lower risks. Issuing organizations have extended their familiar protective mechanisms, but at the cost of slower settlements and higher fees.

Achieving large-scale micropayments, speed is the primary goal. Card payment network settlements take several days, and merchants have to pay a percentage of the transaction amount as fees. Cryptocurrency channel settlements take only a few seconds, with costs of less than one cent. However, this efficiency comes with irreversibility; once a cryptocurrency payment is completed, it cannot be undone.

Traditional commerce has built a whole set of infrastructure around “possible mistakes.” When there is a problem with credit card shopping, you have a procedure to follow: contact the bank, initiate a dispute, the issuing organization investigates and temporarily holds the funds, and finally decides on a refund or supports the merchant. In 2025, there were a total of 261 million disputed transactions, with a total value of 34 billion dollars.

However, the agents operating on the stablecoin channel have none of these guarantees.

When multiple agents begin to collaborate, the issues become more complex. When hundreds or thousands of multi-agent workflows intertwine, clarifying responsibilities can become a nightmare.

Issuing organizations will not bear this risk, at least not under the current profit model. Visa and Mastercard's agency programs still charge standard interchange fees, and settlement still takes several days. They could switch to instant stablecoin settlements, but that would mean giving up the dispute resolution system that serves as the basis for their fees.

The dispute resolution mechanism of traditional finance is not innate. The first credit card (Diners Club Card) emerged around 1950, but consumers had to wait 24 years to gain the right to dispute transactions. The modern infrastructure we take for granted today was gradually established as issues arose.

Autonomous agency business doesn't have so much time to waste. API requests have accounted for 60% of the dynamic HTTP traffic processed by Cloudflare. Bot and automated traffic now accounts for nearly half of the network traffic. The 700 million users of ChatGPT can directly check out on Etsy through ACP, and Shopify integration is also coming soon. There is already trading volume, and users have a potential need for agents to handle tasks; the use of agents for business activities is not far off.

Therefore, we are faced with a choice: to allow traditional financial infrastructure to continue its slow settlement, or to consciously build trust infrastructure to match the fast settlements of blockchain? The former will limit agency potential, while the latter presents opportunities and is an inevitable extension of autonomous agent business development.

So, what exactly should be done?

As expected, this involves two parts: before and after the transaction.

Before the transaction: Is agent trading allowed?

This depends on three points: identifying counterparties, fraud detection, and using credit scores to determine pricing and access permissions.

In the United States, Plaid connects nearly half of bank accounts, processing millions of account verifications daily. When you verify your identity on Venmo, it is Plaid that you are using.

Currently, any agent that interacts with the API, scrapes web pages, or initiates payments lacks mutual authentication. All the server sees is a vague ID (such as a wallet address or API key), unaware of who the caller is. Without a universal identity across services, it is impossible to build reputation, and each interaction starts from a “zero trust” model.

In 2024, American adults lost approximately $47 billion due to identity fraud.

We need a “Know Your Agent” (KYA) layer, similar to how Plaid provides identity infrastructure for fintech. It should issue persistent and revocable credentials that bind the agent to the human or organization behind it.

Card organizations have spent decades building systems that can identify suspicious patterns from millions of transactions. They understand normal human consumption behavior and can flag anomalies in real time. If an agent is compromised and unauthorized spending occurs across multiple merchants, there is currently no shared fraud map that can detect it.

Visa stated that after investing $11 billion to enhance security from 2019 to 2024, its system prevented $40 billion in fraudulent attempts. Stripe processes over $1.4 trillion in payments annually and uses this to train its Radar anti-fraud system. During Black Friday and Cyber Monday in 2024, Radar blocked 20.9 million fraudulent transactions worth $917 million.

Currently, there is a lack of such fraud detection layers in agency trading. When an agent makes an x402 payment, there is no shared system to flag abnormal behavior, such as a surge in spending or unusual frequency.

Without a persistent identity and reputation, every interaction with an agent starts from zero. Reputation is deeply embedded in human commerce: the ads you see are based on browsing history, Uber ratings affect driver acceptance of orders, and credit scores follow you to every financial institution. It should be the same for agents.

What to do if there are issues after the transaction?

Chargeback is a way for card networks to handle disputes: after a customer disputes a transaction through their bank, the funds are withdrawn from the merchant. However, this is often abused. In 2023, chargebacks caused merchants approximately $117.47 billion in losses. For every $1 lost to chargebacks, merchants typically incur an additional cost of $3.75 to $4.61 (including fees, product losses, and management overhead).

Source: Coinbase's x402 paper

Merchants only won 8.1% of the disputes in proactive defenses. 84% of customers believe that initiating a chargeback directly with the bank is simpler than requesting a refund from the merchant.

Stablecoin transactions initiated by the agent are settled in seconds and cannot currently be revoked. Cloudflare has proposed a delayed settlement extension for x402, allowing for a “waiting period” to be set before the final transfer of funds.

The developers are building prototypes of these infrastructures. At the ETHGlobal Buenos Aires hackathon, a team created Private-Escrow x402. Their escrow solution involves the buyer prepaying funds to a smart contract, while the payment is signed off-chain with a “payment intent.” A coordinator batches hundreds of such signatures into a settlement transaction, reducing the Gas fee by 28 times.

But this is just a basic component; it still needs to be productized.

Who will build all of this?

This reminds me of the era when telecom operators dominated the industry. They had billing relationships with every mobile user but missed out on the value generated by smartphones. App distribution and mobile advertising created hundreds of billions of dollars in revenue, which could have been captured by the operators.

Card organizations are now facing a similar situation. The trust infrastructure built over decades by Visa and MasterCard is precisely what is lacking in the autonomous agency economy. However, their business model relies entirely on interchange fees, which exist on the premise that they control the payment channels. They spend huge amounts of money maintaining that infrastructure, funded by a few percentage points of transaction volume. Providing consumer protection for stablecoin transactions would mean subsidizing competitors' payment channels with their own revenue.

If the card issuing organization does not take action, the next candidates are AI laboratories like OpenAI, Google, and Anthropic. They all hope that their agents will be widely used. However, operating a centralized identity registration authority means that they must take responsibility when agent behavior is inappropriate. They do not want to become the court of arbitration for your “wrong hotel booking.”

They prefer to have a third party build identity and traceability infrastructure for them to connect directly, just like how they connect to payment systems or search engines today.

Cloudflare is in a unique position. They have handled massive amounts of web traffic and have been running bot detection, with their “AI auditing” tool allowing publishers to track bot access. The leap from “identifying bots” to “verifying agent identity and reputation” is not technically a huge jump.

But Cloudflare has always prided itself on being a neutral infrastructure. Once it starts issuing trust scores or adjudicating disputes, it becomes more like a regulatory body - which is a different business and implies different responsibilities.

Three Entry Points for Startups

You cannot beat OpenAI in model quality, nor can you surpass Cloudflare in traffic. You have to find parts of the tech stack that their business models (at least for now) do not allow to be touched, yet still hold value. I believe there are three entry points: identity, recourse, and attribution.

Agent identity is the most direct. The registration model has been validated. Although Plaid is a classic case, it is very relevant: they verify identity for bank accounts. Startups can do the same for agents: issuing credentials, building reputations, and allowing merchants to check credit scores before receiving payments. Its moat comes from network effects: once enough merchants verify through your registration form, agents must maintain a good reputation record.

The recourse mechanism is more difficult because it requires taking on risk. It can be seen as insurance: a small fee is charged for each transaction, covering losses when issues arise. Scale is key. Card interchange fees range from 1.5% to 3%, which includes the cost of dispute resolution. The costs for stablecoin channels are significantly lower, so a recourse layer can easily provide comparable protection at a rate of 0.5% while still leaving room for profit.

Attribution mechanism is the most forward-looking, but it will inevitably emerge in the end. When agents start to influence purchasing decisions, brands will pay to affect the recommended content. An auction mechanism can be designed. However, it has a “cold start” problem, requiring brands, agents, and merchants to participate in the market for it to operate, whereas the first two entry points do not have this issue.

The importance of these three entry points varies with the stages of development of the agency economy:

Identity becomes crucial when the agent does not require manual approval for each transaction.

Recourse is crucial when the agent starts handling real funds.

Attribution will only be initiated when the trading volume between agents is sufficient to support the advertising market.

This leads to the actual development trajectory:

Source - Chart generated using Claude

Startups will build part of the agency economic infrastructure.

The development of agency can be divided into three stages:

As an interactive interface

Executed under human supervision

Mutual autonomous trading

We are in the first phase. ChatGPT's Etsy checkout integration is a good example: we browse products in the chat interface (though not all of them are like this), agents recommend options, but ultimately the decision is made by humans. Trust is entirely borrowed from existing facilities.

This stage belongs to the existing giants, as it is a distribution game for competing for user entry points. Value accumulation is in the hands of players who have the purchase decision interface.

The hallmark of the second stage is that the agents gain more autonomy. Agents no longer just suggest itineraries, but instead directly book flights, rental cars, and hotels. We provide the goals or constraints, the agents execute, and we accept the results.

At this point, the trust layer becomes indispensable. Without a recourse mechanism, users will not authorize agents; without authentication, merchants will not accept agent payments.

This is precisely the opportunity for startups. Existing giants may lack sufficient motivation to build trust facilities for stablecoin channels, as they already have tremendous growth potential at this stage (still led by themselves). OpenAI's revenue reached $13 billion this year. In contrast, Tether's profit in just the first ten months of 2025 reached $10 billion, with the annual profit expected to be even higher.

The identity, traceability, and attribution layers will be built by the new company, which is dedicated to addressing specific issues related to agency capabilities and user authorization boundaries.

The third stage is autonomous agency commerce. Your agent does not need to consult for daily decisions; it can negotiate with other agents, bid for computational resources, participate in advertising auctions, and continuously settle thousands of small transactions. Stablecoins will become the default settlement layer due to the volume, speed, and granularity required for machine-to-machine transactions.

In this stage, the focus of competition is no longer on the best model or the fastest public chain, but on who has built the most trusted infrastructure: the “passport” for agents, the “court” for adjudicating disputes, and the “credit system” that allows for over-balance transactions. These institutions providing software services will determine which agents can participate in the economy under what conditions.

Conclusion

We have paved the way for agents to “spend money”, but we have not yet built the mechanisms to verify “whether it should be spent”. HTTP 402 has been dormant for thirty years, only to awaken now that micropayments have become feasible. The technical issues have been resolved. However, the trust infrastructure that supports human commerce, such as identity verification, fraud detection, and dispute resolution, still lacks corresponding agent versions. We have solved the easy part. It will take time to ensure that agents can do business with confidence.