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Why the Agentic Economy Needs its Native Settlement Layer, and a Fundamental Rethink of AI Payments

I used to work at Google for years as a software engineer and tech lead. I built the systems that power online advertising – basically, everything that figures out which ads you see, when they pop up, and if you actually click on them. I worked on recommendation engines, data tracking, and how to turn viewers into customers. I pretty much helped build the whole infrastructure of how companies grab your attention online.

Around 2024, I began to see a shift in how people use AI. When someone asks an AI to do research, they simply wait for the answer – they don’t browse through links or explore websites. This eliminates the traditional online behaviors – like page views, scrolling, and clicking – that advertising and platforms like Google and Meta rely on. It became clear that if AI agents are going to function in the real world, they’ll need a way to make payments.

If AI agents were going to act in the world, book, procure, settle, transact, how would money move?

When I decided to leave Google and start AEON, I wasn’t betting on AI itself – everyone already understood its potential. My real conviction was that reliably *settling* transactions would become the biggest challenge in a world of AI agents, and that current systems simply weren’t designed to manage that complexity. That’s what drove me to build AEON.

The Unit of Value is Changing

I noticed a fundamental change happening in how the economy works. Previously, the online economy focused on how people behaved – things like clicks, how long they spent online, and what they looked at. But with AI, things are different. AI doesn’t click or browse; it makes direct requests for information – what are called API calls – and completes tasks automatically, at incredible speed. This means the basic unit of economic activity is moving away from individual clicks and towards these API calls. This shift requires a completely new kind of infrastructure, one that wasn’t designed for the old way of measuring attention.

Existing payment methods were built for people, not machines. They rely on verifying a person’s identity for every transaction and are designed for the speed at which humans typically make purchases. However, these systems don’t work well for small, automated transactions – fees that are reasonable for a $50 purchase become too high for tiny API calls costing only fractions of a cent. It’s like trying to use outdated technology to power modern software.

Why Traditional Rails Hit a Ceiling

The payments world is paying attention to AI. In the last year and a half, major companies like Visa, Mastercard, Stripe, and Google have all launched projects focused on using artificial intelligence for payments.

Google and Mastercard’s new Verifiable Intent system is a significant step forward in building trust for automated shopping. It uses secure digital proofs to confirm that a real person authorized a purchase, rather than an unauthorized program, helping to prevent fraudulent transactions.

I’ve been analyzing this situation, and while understanding what people *want* to achieve is crucial, it’s only part of the battle. Actually making those intentions a reality – the settlement phase – is where we hit real roadblocks. It’s become clear that simply throwing more resources or technical skill at the problem won’t fix the underlying structural issues we’re facing.

There are three key problems with current identity verification systems. First, “Know Your Customer” (KYC) processes are built for people, relying on things like passports and bank accounts to prove identity. AI agents, being just code, can’t provide these things. Stripe’s solution of giving each agent a virtual credit card seems good, but it quickly becomes unworkable at a large scale – having ten thousand agents each with their own card undermines the security measures that traditional finance relies on.

Currently, most automated systems still need a person to approve each purchase. While OpenAI’s connection with Stripe is a step forward, it still requires a human to complete the payment. True automation—where an agent can independently handle transactions—is hindered by the fact that traditional payment systems have no way to verify who or what started the process. What we have now isn’t truly agent-driven commerce; it’s just a slightly easier way to pay.

Finally, consider the sheer volume of transactions. What’s considered a lot for a person – maybe fifteen transactions a day – is nothing compared to what an AI could do. An AI working on a complicated task might make thousands of tiny payments every minute for things like accessing data or using computing power. Charging a 30-cent fee for each transaction worth just a tenth of a cent isn’t a minor inconvenience—it makes the whole operation financially unworkable.

Simply adding more money to the current system won’t fix these problems. They stem from fundamental design flaws.

Rethink of AI Payments in the Agentic Economy

All the new payment methods being developed – like x402, AP2, and ACP – address the basic question of how someone can make a payment. However, they all assume there’s a business ready and able to accept that payment. In reality, very few businesses are set up to handle these new types of payments.

x402, Coinbase’s protocol for embedding payments directly in HTTP requests, is technically elegant. An agent makes an API call; the payment rides alongside it. No account setup, no human confirmation. But the receiving merchant must accept stablecoins, and today, most don’t.

Essentially, the core issue is settlement – how these transactions finalize, are confirmed, and link to actual value in the real world.

AEON acts as the bridge connecting advanced AI agents to the real-world economy. We’re creating a system that allows these agents to work together smoothly, integrating with key developing standards like x402, ERC-8004, Google AP2, and MCP. This ensures different AI systems can easily communicate and coordinate with each other.

As an analyst, I’m particularly impressed with AEON’s execution layer. It features a completely programmable settlement runtime, meaning agents can build and deploy transaction logic on the fly. This allows for things like conditional payments, continuous micropayments, secure escrow between agents, and automated compliance – all without needing any manual oversight. It’s a really powerful and flexible system.

At the infrastructure layer, AEON operates a unified node network bridging on-chain and real-world environments, allowing agent-initiated transactions to settle continuously across both digital and physical economies. Our merchant network covers more than 50 million businesses across the globe, integrated directly into national payment infrastructure like Brazil’s PIX, the Philippines’ QR Ph, and Nigeria’s NIBSS. An AI agent initiates a crypto payment; the merchant receives local currency in real time without hardware upgrades and migration.

We became an official x402 ecosystem partner, launched facilitator infrastructure on BNB Chain, and integrated ERC-8004 for on-chain agent identity, a verifiable machine ID that doesn’t require a passport. Today, AEON serves over 2 million users and processes more than 30 million transactions monthly across nearly 20 emerging markets, operating at scale as an early settlement backbone for agentic finance. And we just secured investment led by the top institutions including YZi Labs, IDG Capital, HashKey Capital, Stanford Blockchain Builders Fund, and more.

What Comes Next

The competition between the x402, AP2, and ACP protocols is being resolved surprisingly quickly. Google’s AP2 has already been successfully connected with x402. Initially, many believed one protocol would dominate, but now it appears they will work together. This suggests the real challenge isn’t choosing a protocol, but building a reliable system for processing transactions that all protocols can use.

The settlement infrastructure doesn’t dominate crypto conference agendas. It’s not a compelling narrative. There are no governance tokens, no novel consensus mechanisms, no viral mechanics. It’s regulatory relationships, local banking integrations, and currency conversion infrastructure. Deeply unglamorous.

TCP/IP and SWIFT aren’t widely recognized, despite being essential. The underlying systems that facilitate global transactions are usually unseen, undervalued, and ultimately more reliable than the apps and services we actually use.

Two waves are coming.

We’re seeing two major shifts in how AI is used for business. First, AI agents are moving beyond just making suggestions – they’re now able to independently handle tasks like reordering supplies, renewing subscriptions, and purchasing items, all without needing your approval each time. Second, systems are starting to automatically settle payments and data exchanges between themselves, in real-time, without any human involvement.

I quit a secure job at a major tech company because I was convinced this technology needed to be developed quickly, and I felt like the opportunity wouldn’t last. Now, other big companies are proving I was right. However, simply believing in an idea is different from actually building the complex and often unglamorous systems needed to make it work.

The old way of capturing attention online relied on things like ads, tracking, and automated bidding. But a new approach, where individuals have more control, requires a different foundation. We’re currently developing that new foundation.

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2026-05-21 14:50

The Unit of Value is Changing

Why Traditional Rails Hit a Ceiling

Rethink of AI Payments in the Agentic Economy

What Comes Next

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