Agent Payments This Year: Hype Without Market Adoption
- Key Insight: After a year of practical experience in the agent payments sector, the author finds that genuine demand for agent commerce has not yet materialized on a large scale. The payments layer itself is not the core bottleneck; the real challenges lie in human-agent coordination, task verification, and result settlement. Coordination capabilities will be the key differentiator for future competition.
- Key Factors:
- Agent payment projects from giants like Stripe and Coinbase show underwhelming data: Coinbase's x402 sees a real daily transaction volume of approximately $17,000, half of which are test transactions. Stripe's Agent transactions have only reached single-digit completions.
- The agent shopping experience is inferior to traditional e-commerce for most product categories (e.g., clothing, electronics), as users require visual comparison and browsing, making chat-based interfaces less efficient. Potential advantages are limited to high-frequency, low-decision scenarios (e.g., ordering food) or complex checkout processes.
- Machine-to-machine API payments (e.g., stablecoin micropayments) face structural challenges: developers are already accustomed to solving small-value payments via subscriptions or prepaid credit points, while large SaaS companies are reluctant to abandon annual enterprise contracts in favor of pay-per-use billing.
- Agent-to-agent payments remain theoretical, with no real transaction volume. The true difficulty lies in agent discovery, trust establishment, term negotiation, and dispute resolution—far exceeding the payment technology itself.
- Agent finance is the only area with genuine existing demand. Funds and DeFi users already have an established willingness to pay, and AI can enhance capabilities like real-time monitoring and automated portfolio rebalancing. However, competition favors traditional institutions that already possess licenses and customer relationships.
- The moves by major players are defensive in nature, backed by ample cash flow and long time horizons. Startups, however, must focus on markets that exist today rather than waiting for a future wave.
Original Title: a year inside agentic payments: the uncomfortable truth
Original Author: @13yearoldvc
Translation by: Peggy
Editor's Note: This article offers 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. Companies like Stripe, Visa, Coinbase, and Google are all making moves. Concepts such as stablecoin micropayments, x402, machine-to-machine settlements, and agent-driven e-commerce are heating up. However, after actually building a product and interacting with merchants and developers, the author found that genuine demand hasn't materialized at scale yet.
The article breaks down several typical scenarios: agent-driven shopping isn't clearly better than traditional e-commerce for most product categories because users still need images, comparisons, and browsing; machine API payments seem suitable for stablecoin micropayments, but most current developers already solve this with subscriptions, credit top-ups, and existing billing systems; payments between agents, while a long-term vision, are still in the early stages with a lack of real transaction volume.
Relatively speaking, agent finance is one of the few areas where demand 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 frameworks, and customer relationships.
The author's final assessment is that the agent economy doesn't truly lack a payment layer alone; rather, it needs more complex coordination capabilities—how to enable agents to collaborate with humans, verify task completion, and settle outcomes. Payment is just one component. For giants, early positioning is a defensive move; but for startups, the real priority is finding markets that exist today.
Here is the original text:
Over the past year, I've been building infrastructure for the Agent economy, speaking with teams at Stripe, Visa, Coinbase, Google, and dozens of startups pushing agent commerce forward. I've mapped the space, shipped products, and tried to find the real market.
But the reality is: genuine demand hasn't arrived yet. For startups looking to enter this space, there are still many structural problems to overcome.
Stripe launched 288 new products at its Sessions conference last month, and agent-related documentation now accounts for nearly 40% of total documentation views. Its agent commerce marketplace has been integrated with over 1,000 merchants. Yet at Sessions, 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, with a baseline requirement of at least $250 million in annual revenue to be eligible. Today, only companies at the level of Amazon or Walmart have the capability to close the identity verification loop.
Coinbase had reported that as of April, there were 69,000 active agents and 165 million transactions on x402. However, independent on-chain analysis shows a real daily transaction volume of approximately $17,000, about half of which are test transactions (CoinDesk, March 2026).
What We Learned Building shop.fast.xyz
Agent-to-Merchant, i.e., Agentic Commerce
We built shop.fast.xyz to directly validate agentic commerce. Real products, real merchants, real transactions.
But for most product categories, the current AI shopping experience is significantly worse than traditional e-commerce. When buying clothes, electronics, or furniture, users want to see images, browse options, and compare side-by-side. Chatbot-style dialogue is actually a regression: you're replacing a rich visual interface with a string of text conversations. Humans shop with their eyes first.
Agents performed well on 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." The model layer works. But it can't replace the experience of "seeing ten items at once and choosing one." Chat interfaces can include product carousels and interactive displays, but at that point, you're essentially rebuilding an e-commerce front-end inside a chat window. For shopping scenarios requiring visual comparison, we haven't yet found a convincing reason why a chat shell would be better than the original e-commerce interface.
We did see demand on the merchant side, but it's more defensive in nature. Merchants want their stores to be discoverable by agents, not because a large number of consumers are already shopping via agents today, but because they fear being left behind if agents become the dominant channel in the future. This represents the so-called Agentic Engine Optimization (AEO) opportunity—but currently, it's a "nice-to-have," not a "must-have." Merchants are preparing for a wave that has yet to arrive.
Where conversational commerce truly improves the experience is in high-frequency, low-decision-cost purchases where users already know what they want. The clearest example is ordering food. The market is large enough, the frequency high enough, and the decision fast enough, e.g., "Order me pad thai from that place I liked last time." In this scenario, conversational agents might win. But the major food delivery platforms don't open APIs. The only path is computer use—having AI operate apps visually, like a human. This process is slow, fragile, and the inference cost doesn't justify itself for a $15 lunch.
Another opportunity lies in online stores so complex that users genuinely struggle. Think cascading discounts, coupon codes, loyalty points, and messy checkout flows. An agent that can understand "apply my coupons, redeem points, find the cheapest shipping, and complete the transaction using my language" could indeed simplify a currently broken shopping experience. This is especially valuable for elderly users, non-native speakers, cross-regional shopping, or in very specific scenarios with niche, complex needs.
But both opportunities require massive B2C distribution capabilities. You're competing with the likes of DoorDash and Amazon for user entry points. Distribution at a consumer scale is the incumbent's advantage. The supply side of agentic commerce is ready, but the demand side is constrained by user experience and distribution channels—and more infrastructure won't solve these two problems.
What We Learned with x402 and MPP
Agent-to-Web/API, i.e., Machine Commerce
We spoke with dozens of developers about their real payment needs. The pattern was almost identical: current 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 costs on Stripe are effectively around 2.9% plus $0.30, making sub-$1 API calls uneconomical. But at today's low transaction volumes, topping up credits solves the problem. Developers pre-fund accounts, and the issue disappears.
The deeper problem lies in the vendor market. Most large SaaS companies don't want to sell fractional 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, niche data sources, independent developers, MCP servers, and the like. Protocols like MPP and x402 are well-suited for this segment. But by definition, this is a market for professional, niche users—and developers have historically been among the least willing to pay for things.
When Stripe Projects launched, it onboarded 32 service partners, including Vercel, Supabase, Cloudflare, Twilio, and others—covering most core services developers use to build and deploy software, all accessible through existing billing systems. The top of the developer tech stack is already well-served. The opportunity for new payment rails lies beyond that top 30 service providers: it exists, but its scale is inherently smaller than what grand narratives suggest.
Content access follows the same logic. Agents are constantly scraping and summarizing articles, and publishers are starting to push back. But when content monetization arrives at scale, it will likely happen through CDN service providers that already sit between publishers and the internet—like Cloudflare, which already offers AI audit tools—or through bulk licensing agreements between publishers and AI labs. Infrastructure opportunities will flow to existing players who already have distribution.
What We Learned with Agent-to-Agent Payments
Commerce between agents is the long-term vision, but it remains almost entirely theoretical today. No one has yet generated meaningful transaction volume. The truly difficult parts are being tackled by various startups, including agent discovery, trust establishment, term negotiation, and dispute resolution.
Once such a 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 will involve multiple parties, unlike the default bilateral buyer-seller model of existing rails. When it does happen, we believe it will explode rapidly and at massive scale.
This is precisely the long-term bet for dedicated settlement infrastructure—and it's a real bet. But a "real long-term bet" and a "current market" are not the same thing. We were among those declaring this market would arrive for months, and we built a whole infrastructure stack around it over the past few years, including our distributed network. Theoretically, it can scale to over 1 billion TPS with sub-50 millisecond latency and an average consensus time of 10 milliseconds. But we must return to where the market is today.
What We Learned with Agent Finance
You could say this is the only category where real demand already exists. Customers are already there and are already paying. Fund managers, treasury teams, and DeFi users already spend money on financial tools today. Integrating AI into existing workflows is a natural product path.
Agent finance will also create entirely new modes of behavior. An agent capable of autonomously monitoring and rebalancing hundreds of positions in real-time can operate in ways humans cannot manually replicate. This represents a genuine capability uplift, not just automation.
The challenge lies in the competitive landscape. The financial industry is heavily regulated and relies on established relationships. Incumbents hold licenses, compliance infrastructure, and customer relationships. Startups can find inroads in less regulated areas like DeFi, or sectors where incumbents are slow to act, or areas where AI creates new capabilities that giants don't yet possess. Overall, however, the competitive dynamics in this category favor incumbents more than the previous three, because adding AI to an existing product and customer base is far easier than building products and acquiring customers starting from AI.
An Honest Conclusion
So, why is everyone still doing this? Two reasons.
The first is incentives. Large companies have enough cash flow to bet on a future that may take years to materialize. For them, being five years early is a rounding error; being one year late could be catastrophic. So they have to do it.
The second is a cognitive blind spot. When your business is payments, every problem looks like a payment problem. The agent economy needs a payment layer, so everyone goes and builds a payment layer.
But payment is just one part of a much larger problem. The truly difficult questions aren't about moving money between agents, but about coordinating work between agents and humans, verifying whether tasks are completed, and settling the outcomes. Payment is just a part of settlement. Settlement is just a part of coordination. And coordination is the real prize.
Large-scale coordination will naturally create a need for settlement mechanisms. Payment will become one instrument in this orchestration, not the entire piece. The companies that truly solve coordination will eventually incorporate payment, not the other way around, with payment companies swallowing coordination.
Most current giants are defensively building for a future of "machines transacting at scale." For them, the timeline doesn't matter because they have near-infinite runways.
But startups don't have that luxury. We must find where the market truly is right now. We can't just wait for the wave to arrive.
A year of building has led us in an unexpected direction. There is indeed activity there, growing quickly, and underserved. It exists outside the four categories we mapped.
