Agentic Data Battle: Intent

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Key Friction Point in Agent (M2M) Transactions. Example of why real agentic transactions are 2-3 yrs away. We have a new party in a transaction that everyone needs to trust: the agent. Mastercard/Google Verifiable Intent is a LONG WAY from satisfying the need. It’s a self-attestation (see the Technical Addendum at the end of the Blog).

My prior blogs have focused extensively on the trust challenge in agentic commerce: authenticating the consumer and the agent (the actor). As I discussed in EMVCo and DPCs, financial institutions must verify and authenticate the four pillars of a transaction: the User, the Instrument, the Actor (Agent), and the Action (Payment). Today, I want to dive deeper into the fourth pillar—the Action—and the emerging battle over intent data.

A New Party to the Transaction

For decades, payment transactions have involved a familiar cast: the consumer, the merchant, the issuer, and the network. Each party has well-defined roles, risk allocation, and data flows governed by established rule sets. Agentic commerce introduces a new party: the Agent.

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Can Processors Win a Role in Agentic?

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Adyen’s stock is down over 40% this year. Investors aren’t just punishing one company; they’re repricing the entire processor category as agentic commerce threatens to restructure who controls economics and merchant relationships. The market sees what I’ve been writing about for 18 months: processors are at risk of becoming dumb pipes.

Yesterday, Adyen announced Adyen Agentic a suite of modular APIs encompassing Agentic Feed (product/inventory), Agentic Cart (checkout orchestration), and Agentic Payments (authentication, fraud, tokenization). The positioning is explicit: a “universal translator” that lets merchants integrate once and participate across every agent platform, protocol, and payment method.

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Google Ads in the Agentic Era: Merchant Center Becomes the Center

Great article in Search Engine Journal surrounding the shift in Google Ads: the product feed is no longer just a catalog. It’s becoming THE primary bidding signal.

This shift matters for payments strategists because it reveals how Google is positioning itself as the orchestration layer for agentic commerce. The advertising infrastructure and the commerce infrastructure are converging, and Merchant Center is the “last mile” integration point to merchant data from store level product inventory, to pricing, to SKU level purchase feeds (for measurement).

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The Power to Price

The best lever of economic margin for investors to track is power to price. In classical economics, pricing power is not merely a reflection of market share, but rather the capacity of an economic actor to minimize transaction costs while maintaining strategic control over data, risk, and user experience. Historically, eCommerce has operated under a macroeconomic paradigm where merchants absorb the operational and financial frictions of the conversion funnel, while payment networks and processors leverage their scale to price security, identity, VAS and settlement infrastructure.

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Federated Models Need Measurement

A follow on blog to my Intent data post yesterday. Where intent is needed for authorization, measurement is needed by every “specialist” participating in an agentic interaction. As background I was founder/CEO of Commerce Signals, focused on measurement and card transaction data. Measurement is a powerful business. In fact, I would say Google started out as a measurement company with the PageRank algorithm. By keeping track of what users clicked on which link for which search word, they created the directory of the internet. Let’s dig a little deeper into why measurement is key in agentic, and for all federated models.

Google is not building a monolithic “central brain” to disintermediate the ecosystem. Instead, as discussed in my UCP Blog (also see Ask Macy’s Case Study), they are fostering a world of specialist collaborative models that interact across three specific technical layers:

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Owning Your Bot’s Actions: Target Part 2

In my previous post, covering Target’s “Your Bot is Your Responsibility”  was the only move they could make. When you let an AI bot loose with your credit card, you are effectively handing your car keys to a teenager; you can’t act surprised when there’s a dent in the bumper. But Target’s stance isn’t just a legal shield; it is a flare gun fired over a massive Governance Gap. Today’s agentic commerce is high on technology and standards, but dangerously low on the commercial terms that actually make markets function. To be clear, it’s not for lack of effort from V/MA, nor is it technology; it is resistance to change.

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MPP Phase 2 Live – Ask Tom Goes Agentic

Long blog – First 2 Pages are economic implications, last 6 pages are tech deep dive

MPP is a big deal because value exchange enables specialization and market forces to operate (as discussed in last week’s MPP – Addressing the Internet’s “Original Sin”.MPP and X402 are BIG.. really big. A whole new market. This isn’t about cash replacement or taking share from xx this is about enabling a new Economy. Today’s blog is 4 paragraphs of the economic implications (for investors and CEOs), followed by 4 pages on tech detail covering what I built. Please note “Ask-Tom” is just a model of an x402 service…. of course it won’t generate much demand (service ID is at bottom).

First, let me try to explain why this is such a big deal from an economic perspective. The foundational driver for MPP’s success is the radical reduction of transaction costs through standardized commercial terms. As outlined in my 2016 blog Small Wins, the forces that once drove asset-heavy, integrated organizations are atrophying in favor of “refragmentation” and specialized networks. Historically, the economic cost of inking a bilateral contract for every micro-interaction was prohibitive (ex “Account Creation” bottleneck that stifled agentic autonomy). Following the principles of Ronald Coase’s Transaction Cost Economics, MPP and x402 provide the multilateral governance and common commercial rules necessary to bypass these friction points. By establishing trust and speed through a common interface, these protocols allow for the “Small Win” of a single transaction to scale into a global network effect, where the cost of connection approaches zero.

This standardization enables the “Value Assembly” of “super-specialists” who can target previously unreachable “shale deposits” of niche market demand (see Network Effects and Value Assembly). A successful network enables specialists like “Ask-Tom” to provide high-value, grounded intelligence without the overhead of building independent settlement or reconciliation infrastructure. This is far beyond mere “agentic commerce”; it is an evolution in how software and hardware interact with EVERYTHING ECONOMICALLY. For example, MPP’s session-based economics provides a virtual “bar tab” for agents to execute tasks within human-granted budgets, paying only for precise resource consumption. This creates a sustainable commercial model where the incentives for specialization and market forces to operate on software service at a hyper granular level. Market forces in turn encourage specialists to solve increasingly granular problems across diverse domains, and unlocks the “shale deposits” of data that doesn’t play. I’ll discuss what this could look like next week as a follow up to Value Assembly.

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2025: The Great Decoupling

Year-End Payments Recap

Summary: B2B Stablecoin and The End of the Interface Era

As we close the books on 2025, the payments industry finds itself at  a moment that future historians will likely designate as the end of the “Interface Era” and the dawn of the “Agentic Era.” For the past three decades, the digitization of payments has been defined by the migration of human intent from POS to digital screens. From the first e-commerce transaction to the ubiquity of mobile wallets, the fundamental atomic unit of the economy remained the same: a human being, interacting with a graphical user interface (GUI), making a conscious decision to exchange value for goods or services.

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Discount “On Chain”. Value Exchange and Commercial Frameworks Will Define Success

Case studies in Agentic and JPM Kinexys

Key Themes

  1. Value exchange requires a commercial construct such as a contract, marketplace agreement or commercial network.
  2. Tech is enabling fragmentation both within an organization and across domains with finer-grained access to services (ex APIs), faster settlement (ex blockchain), immutable digital representations of physical world goods (ex NFT), digital trust and assertions (ex W3C Verifiable Credentials), …etc.
  3. While the tech is progressing at light speed, the real battle surrounds the structures, incentives and politics for how value is exchanged, and risk is assumed. 
  4. This atomization of products, services and organizations has created new opportunities for value orchestrators. For example, what if the battle for AI and Agentic Commerce is not about LLMs efficacy, but about enabling consumers to choose the best agent and permission it from their phone (ex Apple). 
  5. Free and Open are great tech models, but terrible business ones (ex Open Banking). Fragmented voluntary Agreements in Web3 and Agentic Commerce spaces struggle to scale due to high transaction costs associated with establishing bilateral trust.
  6. We are in a flux period where incumbent marketplaces and networks will dominate.  For example, there is little prospect for OpenAI to disrupt Google across 7B+ Devices, 3B+ consumer accounts, GC, Advertising, Analytics, Consumer/Enterprise Services. While the buzz of “on chain” finance is loud, application of DLT in closed private blockchains is driving the majority of growth by bringing new efficiencies to established businesses (JPM Kinexys). 
  7. While alternative “federated” and decentralized models are possible, their core challenges surround economics and governance. Who owns the end-end risk?  Who manages bad actors or system flaws? Where is the commercial agreement that assigns risk? 
  8. The next 10 yrs will NOT be a uniform movement toward one single future, but a fragmentation of how value exchange happens. For example, how identity is handled in Agentic commerce will depend on WHO owns the risk for the transaction (merchant, bank, PSP, Platform, Consumer)?  
  9. At the consumer end, I see mobile platforms acting as the controller/orchestrator for trusted interaction across healthcare, retail, government, agentic … etc. I wouldn’t count Apple “out” of the AI race as they may assume the consumer interface role for “everything”.
  10. Kinexsys Case Study – Closed network, strong governance, massive scale. 

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