Agent 결제这一年：광란 속에서, 시장은 아직 오지 않았다

Original Title: a year inside agentic payments: the uncomfortable truth

Original Author: @13yearoldvc

Translation by: Peggy

Editor's Note: This article provides a relatively sober builder's perspective: over the past year, agentic payments have become a hot narrative at the intersection of AI, payments, and crypto, with companies like Stripe, Visa, Coinbase, and Google all making moves. Concepts such as stablecoin micropayments, x402, machine-to-machine settlements, and agent-driven e-commerce have also gained traction. However, after actually building products and engaging with merchants and developers, the author found that genuine demand has yet to materialize on a large scale.

The article breaks down several typical scenarios: agent-based shopping is not superior to traditional e-commerce for most product categories, as users still need images, comparisons, and browsing. Machine API payments seem suitable for stablecoin micropayments, but most developers currently solve this through subscriptions, prepaid credits, and existing billing systems. Payments between agents, while a long-term vision, remain in the early stages with no real transaction volume.

Relatively speaking, agent finance is one of the few areas where demand already exists. Funds, treasury teams, and DeFi users already pay for financial tools, and AI can bring tangible capability improvements like real-time monitoring and automated portfolio rebalancing. However, this market also favors traditional institutions that already possess licenses, compliance, and customer relationships.

The author's final assessment is that the agent economy lacks not just a mere payment layer, but more complex coordination capabilities – how to facilitate collaboration between agents and humans, verify task completion, and settle outcomes. Payment is just one part of this. For incumbents, early investment is a defensive move; but for startups, the real priority is finding markets that already exist today.

Below is the original text:

For the past year, I've been building infrastructure for the Agent economy, talking to teams at Stripe, Visa, Coinbase, Google, and dozens of startups pushing agent commerce forward. I've mapped the landscape, shipped products, and tried to find real markets.

But the reality is: genuine demand hasn't emerged yet. For startups looking to enter this space, there are still many structural problems.

Stripe launched 288 new products at its Sessions conference last month, and Agent-related documentation now accounts for nearly 40% of all documentation page views. Its Agent commerce marketplace has onboarded over 1,000 merchants. Yet, at the Sessions event, the number of agents that actually registered and completed transactions was in the single digits.

Visa mentioned that its Agent token currently requires 3 to 9 months of KYC approval, and companies basically need annual revenues of at least $250 million to be eligible for access. Today, only companies at the level of Amazon or Walmart have the ability to close the identity verification loop.

Coinbase previously reported that as of April, there were 69,000 active agents and 165 million transactions on x402. However, independent on-chain analysis shows that actual daily transaction volume is around $17,000, with roughly half being test transactions (CoinDesk, March 2026).

What We Learned Building shop.fast.xyz

Agent-to-Merchant: Agentic Commerce

We built shop.fast.xyz to test agentic commerce head-on. Real products, real merchants, real transactions.

But for most product categories, the current AI shopping experience is clearly inferior to traditional e-commerce. When buying clothes, electronics, or furniture, users want to see images, browse options, and compare side-by-side. A chatbot-style conversation is a regression: you replace a rich visual interface with a text-based dialogue. Humans shop with their eyes first.

Agents performed well at what we initially thought would be the hardest part. They can understand what users want and handle requests like "something similar, but a bit cheaper" quite well. The model layer works. But it can't replace the experience of looking at ten items simultaneously and picking one. You could add product carousels and interactive displays to the chat interface, but at that point, you're essentially rebuilding an e-commerce frontend inside a chat window. For shopping scenarios requiring visual comparison, we haven't found a compelling answer for why a chat shell is better than the original e-commerce interface.

We did see demand on the merchant side, but it's largely defensive. Merchants want their stores to be discoverable by agents, not because many consumers are already shopping through agents today, but because they fear being left behind if agents become a mainstream channel. This is the so-called Agentic Engine Optimization (AEO) opportunity, but it's currently a "nice-to-have," not a "must-have." Merchants are preparing for a wave that hasn't yet arrived.

Conversational commerce truly excels in high-frequency, low-decision-cost purchases where users already know what they want. The clearest example is food ordering. The market is large enough, the frequency high enough, and the decision fast enough – like "order me pad thai from the place I liked last time." In these scenarios, conversational agents might win. However, major food delivery platforms don't open their APIs. The only path is computer use – making AI visually operate apps like a human. This process is slow, fragile, and the inference costs simply don't justify a $15 lunch.

Another opportunity lies in online stores so complex that users genuinely struggle. Think stacked discounts, promo codes, loyalty points, and chaotic checkout flows. An agent that can "apply my coupons, redeem points, find the cheapest shipping, and handle it in my language" could simplify a broken shopping experience. This is especially valuable for elderly users, non-native speakers, especially for cross-regional shopping, or in very specific scenarios with niche and complex needs.

But both opportunities require massive B2C distribution capabilities. You're competing with DoorDash and Amazon for user entry points. Consumer-scale distribution is the incumbent's advantage. The supply side of agentic commerce is ready, but demand is constrained by user experience and distribution channels. More infrastructure won't solve these two problems.

What We Learned from x402 and MPP

Agent-to-Web/API: Machine Commerce

We spoke with dozens of developers about their real payment needs. The pattern was almost identical: today's Agent API usage is essentially recurring consumption – compute, inference, data sources. Developers already have subscriptions, API keys, linked accounts, and billing relationships with core service providers.

The typical argument for stablecoin payments is that credit card fees on Stripe effectively cost at least 2.9% plus $0.30, making API calls under $1 uneconomical. But at today's low transaction volumes, prepaid credits solve the problem. Developers pre-fund their accounts, and the issue disappears.

The deeper problem lies in the supplier market. Most large SaaS companies don't want to offer piecemeal API access at fractions of a cent. Their business model relies on multi-year enterprise contracts. Companies dependent on large committed revenue streams will resist new pricing models that bypass this structure.

Machine commerce is structurally a long-tail market. It serves small services, vertical data sources, independent developers, MCP servers, etc. Protocols like MPP and x402 are well-suited for this niche. But by definition, it's a market for professional users, and developers have historically been among the least willing demographic to pay.

When Stripe Projects launched, it had 32 service provider partners, including Vercel, Supabase, Cloudflare, Twilio, covering most core services developers use to build and deploy software – all accessible through existing billing systems. The top of the developer technology stack is already well-served. The opportunity for new payment rails lies outside those top 30 providers: it's real, but inherently smaller in scale than the grand narratives suggest.

The same logic applies to content access. Agents are constantly scraping and summarizing articles, and publishers are fighting back. But when content monetization truly scales, it will likely happen through CDN providers already positioned between publishers and the internet – Cloudflare has already launched AI audit tools – or through bulk licensing agreements between publishers and AI labs. The infrastructure opportunity will flow to existing players that already have distribution.

What We Learned from Agent-to-Agent Payments

Commerce between agents is a long-term vision, but currently almost entirely theoretical. No one has yet generated meaningful transaction volume. The truly difficult parts – agent discovery, trust building, term negotiation, and dispute resolution – are being tackled by various startups.

Once this transactional structure truly takes shape, it will look completely different from existing payment rails. Neither party has a human identity; latency requirements are sub-second; transaction amounts can range from fractions of a cent to millions of dollars; and settlements involve multiple parties, unlike the bilateral buyer-seller model default in existing rails. When it happens, we believe it will explode at incredible speed and scale.

This is the long-term bet on dedicated settlement infrastructure, and the bet is real. But a "real long-term bet" is not the same as a "current market." We were among those claiming this market would arrive for several months and built an entire infrastructure stack around it over the past few years, including our distributed network. Theoretically, it can scale to over 1 billion TPS with sub-50ms latency and an average consensus time of 10ms. But we have to return to where the market is now.

What We Learned from Agent Finance

This is arguably the only category where genuine demand already exists. Customers exist and are already paying. Fund managers, treasury teams, and DeFi users already spend money on financial tools. Integrating AI into existing workflows is a natural product path.

Agent finance also creates entirely new behavioral patterns. Agents capable of autonomously monitoring and rebalancing hundreds of positions in real-time can operate in ways humans cannot manually replicate. This offers genuine capability enhancement, not just automation.

The challenge is the competitive landscape. The financial industry is heavily regulated and relationship-dependent. Incumbents have licenses, compliance infrastructure, and customer relationships. Startups can enter less regulated spaces like DeFi, find areas where incumbents are slow to move, or areas where AI creates new capabilities incumbents lack. However, the competitive dynamics in this category generally favor incumbents more than the previous three, because adding AI to existing products and customers is much easier than building products and customers starting from AI.

An Honest Summary

So, why is everyone still doing this? Two reasons.

First, incentives. Large companies have enough cash flow to bet on a future that might take years to materialize. For them, entering five years early costs a rounding error; entering one year late could be catastrophic. So they have to do it.

Second, cognitive blind spots. When your business is payments, every problem looks like a payment problem. The agent economy needs a payment layer, so everyone builds a payment layer.

But payment is just one part of a larger problem. The truly difficult issues are not moving money between agents, but coordinating work between agents and humans, verifying completion, and settling outcomes. Payment is only a part of settlement. Settlement is only a part of coordination. And coordination is the real prize.

Large-scale coordination naturally creates demand for settlement mechanisms. Payment will be one instrument in this concert, not the entire composition. The companies that truly solve coordination will eventually incorporate payment, not the other way around, where payment companies swallow coordination.

Most incumbents are defensively building for a future of "machines transacting at scale." For them, the timeline doesn't matter because they have nearly infinite runways.

But startups don't have that luxury. We have to find where the market truly is right now. We can't just wait for the wave.

A year of building has led us to an unexpected direction. There is activity there, growing fast, and underserved. It exists outside the four categories we mapped.

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