a16z: What Entrepreneurial Opportunities Lie in the Blue Ocean of Agent Payment Transactions?

marsbitОпубликовано 2026-03-02Обновлено 2026-03-02

Введение

a16z explores the emergence of AI Agents as autonomous economic actors and the resulting shift in payment infrastructure. Unlike human "tourists" who engage in one-off retail transactions, Agents behave more like "locals"—relying on pre-negotiated B2B terms, supplier relationships, and credit systems. This shift challenges traditional card-based payment rails, which are ill-suited for high-frequency, micro-value, or programmatic transactions. Key insights include: - Agents will operate like scaled platforms, leveraging long-term partnerships rather than per-transaction negotiations. - Existing payment systems (e.g., credit cards) face technical and economic constraints (e.g., minimum fees, lack of programmability) for Agent-driven commerce. - Stablecoins emerge as a superior alternative due to their global reach, low cost, and programmability—enabling features like streaming payments, microtransactions, and automated arbitration. The article argues that stablecoins can serve as the foundational layer for future Agent payment ecosystems, facilitating seamless integration, reduced friction, and new financial primitives like dynamic billing and cross-system interoperability.

Editor's Note: As AI Agents evolve from auxiliary tools into autonomous 'digital executors,' the payment ecosystem is also undergoing transformation. Traditional internet transactions primarily revolved around the retail process of 'user click - checkout - payment.' However, in the age of Agents, the entities conducting transactions are no longer just humans but intelligent systems capable of continuous operation and establishing long-term cooperative relationships.

This article presents a vivid analogy: Agents will not make payments like 'tourists' on a per-transaction basis but will behave more like 'locals'—completing transactions through stable supplier relationships, credit, and pre-negotiated commercial terms. In this model, traditional payment systems centered around card swiping may only handle a portion of transactions, while programmable payment tools like stablecoins are poised to play a larger role in new payment scenarios.

Below is the original text:

Step into a marketplace. If you are a tourist, you often see a bustling scene: crowds weaving through, examining goods, comparing prices, sampling products, haggling with vendors, and pulling out coins or cards to complete transactions. It seems that every interaction is an independent business deal—an instant negotiation where trust is settled immediately through cash or cards.

But in reality, most transactions don't happen this way.

If you look more closely, you'll notice that the marketplace is mostly filled with locals. They head purposefully to familiar merchants. Restaurant owners go to their trusted butchers, fishmongers, and farmers; tailors visit repairers, weavers, and artisans. There's little haggling between them, and many transactions are even settled on credit.

When we discuss how Agents will handle payments, we often instinctively adopt the 'tourist' perspective. But Agents will behave more like locals.

The differences between Agents and humans—such as infinite replicability, flexible resource allocation, and near-zero startup costs—mean that a few Agents can establish dominance in specific domains. Even if the barrier to building Agents continues to lower, relationship networks, partnerships, and trust mechanisms will remain critical factors determining the quality of the experience.

The truly dominant Agents won't need tourist-style payment channels; they will need supplier relationships, working capital, and credit lines.
Agents will bring 'tourists' (i.e., users) along to complete transactions.

So, what will this model look like?

As Agents gradually evolve into enterprise-like platforms, their payment models will shift from retail payment networks to pre-negotiated B2B terms and credit systems. Existing payment infrastructure is not well-suited to meet this demand.

This恰恰 presents an opportunity for a new generation of payment networks, such as stablecoins. But this depends on entrepreneurs building solutions around new payment scenarios, such as Agent payments, streaming payments, and high-frequency, small-value, global commercial transactions.

This article will elaborate on this perspective in three parts: First, the key differences between Agents and humans and how these differences will shape future payment models; second, why existing payment systems fall short of meeting Agent needs; and third, the capabilities required for a new generation of payment infrastructure to succeed in future competition.

How Agents Differ from Humans

Understanding Agents and payments requires answering two questions:

1. Do Agents behave more like individuals or more like enterprises?

2. Are Agent decisions more short-term transactions or long-term collaborations?

The answer is: Agents behave more like enterprises and will establish long-term relationships.

Agents are often 'lightweight instances' built atop larger commercial systems. For example, an 'intelligent travel guide Agent' supported by a major travel platform, or a franchise operator fine-tuned for local market demand within an existing supply chain system.

Why will Agents behave like enterprises?

First, superior experiences often come from advance design, not on-the-spot negotiation.

Users do not want their Agent to start comparing prices, contacting merchants, or renegotiating terms at checkout. The ideal Agent should have already done this work: it knows which suppliers are reliable, prices are already agreed upon, and it can directly complete the transaction.

This is a commercial relationship, not a tourist-style one-off transaction.

In fact, similar models already exist in human society. Travel agents, literary agents, talent agents, watch dealers, and real estate agents are all types of 'Agents.' These agents establish long-term relationships with publishers, production companies, watch distributors, or lending institutions, and each transaction is customized atop this foundation.

Second, Agents can be infinitely replicated, but the advantages of scaled enterprises cannot be copied.

The most successful Agents will leverage the advantages of scale: lower computing costs, better supplier prices, deeper system integration, and more stable technical components.

Scale reinforces scale. A travel agent booking a million airline tickets a year will inevitably get better terms from airlines than an agent booking only ten tickets a year.

This trend is already emerging. Only products like ChatGPT have sufficient user distribution to establish partnerships with platforms like Shopify, Amazon, and Expedia. Small startups often have to rely on automated browsers or reverse API interfaces while bearing retail-level fee structures.

This is also why Agents will ultimately become centralized, or at least most Agents will be built on large platforms.

Agents themselves are easy to develop, but economic principles dictate that only a few core Agents will emerge in each vertical domain, possessing deep supplier relationships and able to use profits to continuously optimize the experience.

Meanwhile, specialized Agents in vertical domains can also collaborate with user-side Agents to provide more complete services.

Two Types of Payment Relationships

If Agents behave more like enterprises, then two types of payment relationships need to be designed: User → Agent; Agent (or Agent platform) → Supplier

Users pay the Agent, potentially in various ways: subscription fees, per-task fees, credit lines, authorizing the Agent to use the user's account

The Agent, in turn, pays suppliers through B2B terms, such as: pre-negotiated prices, bulk discounts, Net-30 invoices, sub-agent settlements

Judging from the structure of current corporate spending, Agents will still occasionally use retail payment channels, but this will only constitute a small fraction of overall expenditure.

In fact, this is quite similar to today's credit card system. Card issuers establish retail relationships with consumers, bearing risk and providing credit and rewards; while acquirers establish commercial relationships with merchants, completing transactions through negotiated fees, scaled settlements, and working capital arrangements.

Agents and Credit Cards: A Seeming Fit

Many believe that credit cards are actually a quite suitable payment tool for Agents.

Reasons include: global acceptance, suitability for the $20 to $1000 transaction range, built-in arbitration and chargeback mechanisms, provision of monthly statements. Monthly statements are particularly important as they help users understand their spending.

In the future, when Agents replace kids and iPads as the primary source of 'surprise bills,' this may become even more crucial.

But two problems exist in reality: 1. Credit card technology is not suitable for Agent scenarios; 2. The fee model of credit cards traps the industry in a classic 'innovator's dilemma.'

Credit Card Technology is Difficult to Upgrade

Almost all credit card systems default to human involvement: human approval, user interface interaction, traditional payment types (one-time or subscription).

Virtual card technologies like Stripe Link and Visa 3D took over 15 years to mature. But the development speed of Agents far outpaces the upgrade rhythm of payment infrastructure. Thousands of PSPs, POS systems, merchant backends, and client interfaces cannot be adapted in a short time.

Credit Cards Cannot Cover Extreme Payment Scenarios

For example: an Agent making real-time streaming payments to a compute service provider, or an Agent paying micro-fees for API calls—these transactions are difficult to execute via credit card.

The reason is simple: Visa does not support transactions below $0.01; the credit card economic model relies on a fixed fee of around $0.30.

Technically, Visa could support micropayments, but this would directly impact its business model. More complex is that Agent payment scenarios often fall outside the traditional value range of credit cards. For instance, many early Agent scenarios involve API service fees, which are difficult to refund or resell. Credit cards can still play a role, but the innovator's dilemma often limits the pace of change in established systems.

Traditional Payments Still Have a Role

As Agent platforms gradually evolve into enterprise-like systems, a large amount of high-frequency spending will be handled through B2B terms: invoices, Net-30, discounts, credit lines.

In this model, the 'payment network' itself is not critical. Settlement might happen via wire transfer, ACH, or batch transfer. Traditional payments remain effective in mature commercial relationships. But Agents will not exist solely in this environment.

Agents are emerging rapidly, and they often operate in scenarios where traditional payments are least efficient: first-time partnerships, cross-border payments, complex reconciliation, new Agent-Vendor models, instant payments, micro-loans.

In these scenarios, stablecoins are a superior payment tool. More importantly, building new features on programmable money is far easier than on traditional payment infrastructure.

Once new commercial relationships are established on stablecoins, they tend to maintain this form long-term. Over time, the proportion of stablecoins in the payment system is likely to continuously increase.

Opportunities for New Payment Technologies

Stablecoins are essentially a new financial platform.

They possess the following characteristics: faster, lower cost, globally available, backed 1:1 by high-quality liquid assets.

More crucially, stablecoins are programmable. Functions like arbitration, billing, credit, escrow, and conditional payments can all be flexibly implemented within the same system.

Compared to banks or credit cards, stablecoin payments are easier to embed into: APIs, databases, Agent checkout flows.

This significantly simplifies reconciliation, approval, and system integration processes, which is particularly important for entrepreneurs building Agent commercial ecosystems.

Economically, stablecoins also solve the efficiency problems credit cards face on both ends: no $0.30 minimum fee, large transfers aren't eroded by interchange fees.

Therefore, whether it's: an Agent paying $0.001 per second for compute, or a business settling a $50,000 supplier invoice, the same payment network can be used.

Building More Stablecoin Infrastructure

A common objection is: the on/off ramp costs for stablecoins are high.

For the 'tourist,' this is indeed a problem. But when users have an Agent acting as a 'guide,' this friction rapidly decreases.

Agents can help users complete currency exchange and only execute necessary transactions, thereby saving fees. If combined with billing and arbitration mechanisms, we approach a complete system.

Imagine a scenario: a user browses multiple brands in a department store, selects goods, and finally checks out just once. The store backend is responsible for distributing funds to the various merchants. Agents will need a similar model. The user sees: 'Your Agent wants to book a flight, hotel, and rent a car for you.' Not three separate checkout flows.

The Agent platform handles supplier relationships, and the user only needs to confirm the transaction intent.

Conclusion

Agents will not pay like tourists. They will transact like locals, through relationships, credit, and long-term collaboration. This means the true scale of future payments will flow through pre-negotiated B2B terms, not card swipes.

But we are currently in a critical window. Agents are emerging, entrepreneurs are building new commercial systems, and they need payment tools they can use today.

Credit cards are not ready: micropayments are too costly, reconciliation is complex, technical debt is heavy, reliance on manual risk control.

Stablecoins, however, are ready. They are programmable, global, easy to integrate, and can support Agent payments from day one.

Payment relationships exhibit strong path dependency. Once new commercial relationships are built on stablecoins, they tend to persist long-term. In the coming years, as the ecosystem matures and on/off ramp friction decreases, a cohort of startups will build new capabilities around this infrastructure: billing systems, arbitration mechanisms, credit systems, batch approvals, and cross-system interoperability.

A new era of payments may be beginning right here.

Связанные с этим вопросы

QHow do AI Agent payment models differ from traditional human-centric payment systems?

AAI Agent payment models shift from retail-style 'tourist' transactions (one-time, card-based payments) to B2B-like 'local' relationships involving pre-negotiated terms, credit lines, and supplier networks. Agents prioritize long-term partnerships over immediate negotiations, relying on stable agreements rather than per-transaction payments.

QWhy are traditional credit cards inadequate for AI Agent-driven transactions?

ACredit cards are designed for human-involved retail payments with fixed fees (~30 cents per transaction), minimum charge amounts (e.g., no sub-cent payments), and slow infrastructure upgrades. They struggle with micro-payments, real-time streaming payments for APIs, cross-border efficiency, and automated reconciliation required by Agents.

QWhat advantages do stablecoins offer for AI Agent payment infrastructure?

AStablecoins provide programmable, low-cost, global payments with 1:1 asset backing. They support micro-transactions (e.g., $0.001 API call), bulk settlements, and embedded features like arbitration, billing, and conditional payments without legacy constraints like interchange fees or minimum charges.

QHow might AI Agent platforms structure their relationships with users and suppliers?

AAgent platforms act as intermediaries: users pay Agents via subscriptions, task-based fees, or credit authorizations, while Agents pay suppliers through pre-negotiated B2B terms (e.g., net-30 invoices, bulk discounts). This mirrors enterprise procurement rather than retail checkout flows.

QWhat entrepreneurial opportunities exist in Agent payment systems according to a16z?

AOpportunities include building stablecoin-based infrastructure for micro-payments, cross-border transactions, automated billing/arbitration systems, credit mechanisms, and tools for batch approvals. These solutions address Agent-specific needs like high frequency, low-value global trades and seamless supplier integration.

Похожее

While Everyone Says NFTs Are 'Dead', the Art World is Quietly Completing an 'On-Chain Renaissance'

While many declare NFTs "dead" and dismiss them as overhyped JPEGs, a significant institutional shift is quietly underway within the art world, signaling a "on-chain renaissance." Traditional art, a ~$60B market, is stagnant, aging, and highly concentrated, facing a massive $80 trillion generational wealth transfer to digital-native heirs. Contrary to the narrative, leading institutions have been building infrastructure for digital and on-chain art. Major museums like MoMA, the Centre Pompidou, LACMA, and the Guggenheim have acquired seminal NFT works into their permanent collections. Top galleries like Pace, Gagosian, and Hauser & Wirth have launched NFT platforms or accepted crypto, with Pace giving a solo show to generative artist Tyler Hobbs. Auction houses Sotheby's and Christie's operate dedicated on-chain sales platforms. This follows a historical pattern where every major art movement—from Impressionism to Pop Art—was initially mocked before institutional acceptance. NFT art, only 7-12 years old, is progressing faster. Auction data shows resilience, with works by Beeple ($69.3M), Pak (~$91M), and Dmitri Cherniak ($6.2M in a bear market) achieving high prices. A new cohort of collectors (e.g., FlamingoDAO, PleasrDAO) and "Medici" figures like Cozomo de' Medici are accumulating foundational works. The core argument is that NFTs represent not a speculative asset class but a new ownership system for digital culture, solving provenance issues through immutable, timestamped blockchain records. The medium has survived the speculative crash and is being institutionalized. The bet isn't on short-term price rallies but on the long-term cultural significance of on-chain art as the defining medium for the next generation of collectors.

marsbit10 мин. назад

While Everyone Says NFTs Are 'Dead', the Art World is Quietly Completing an 'On-Chain Renaissance'

marsbit10 мин. назад

Jensen Huang's Message to Graduates: AI Won't Replace You, But Those Who Excel at Using AI Will

NVIDIA CEO Jensen Huang, addressing 2026 graduates at Carnegie Mellon University, emphasized that AI will not replace people, but those who leverage AI effectively will have an advantage. He delivered this message during a commencement speech where he also received an honorary doctorate, his seventh. Huang reflected on his personal journey as an immigrant, starting from humble beginnings as a dishwasher to co-founding NVIDIA. He shared early struggles, including a near-bankruptcy moment saved by honesty with Sega, highlighting resilience and learning from failure. He positioned the current era as the dawn of the AI revolution, a shift as significant as past computing waves. Huang explained that AI is redefining computing from human-written software to machine learning, creating a new industry focused on manufacturing intelligence. While acknowledging fears about job displacement, he argued that AI amplifies human capabilities rather than replaces human purpose. Tasks may be automated, but the core meaning of professions remains. Huang urged graduates to embrace this transformative time with responsibility and optimism. He stated that AI should democratize technology, bridging gaps and enabling broader participation in creation and problem-solving. His final advice was to actively engage with the opportunity: "So run, don’t walk," and to put their hearts into their work.

marsbit17 мин. назад

Jensen Huang's Message to Graduates: AI Won't Replace You, But Those Who Excel at Using AI Will

marsbit17 мин. назад

Three Scenarios for BTC's Future Direction and a Duel Between Two Strong Forces | Special Invited Analysis

**Title: Three Scenarios for BTC's Future Trajectory and a Key Duel | Invited Analysis** The market remains at a critical juncture. Over the past week, Bitcoin (BTC) consolidated broadly between $79,500 and $80,600, validating previous technical analysis. The current focus is on whether this marks the start of a new uptrend or a pause within a larger correction. **BTC Multi-Cycle Analysis & Three Possible Scenarios** BTC's daily chart structure, following its peak at $126,200 in October 2025, presents three primary technical scenarios based on Elliott Wave theory: 1. **Bullish Scenario (End of Correction):** The corrective A-B-C wave from $126,200 ended at the $60,000 low in February 2026. The current price action is the start of a major Wave I uptrend. A subsequent Wave II pullback would not break below $60,000. 2. **Bearish Scenario 1 (Complex Correction):** The correction is unfolding as an A-B-C-D-E pattern. The current move from $60,000 is a D-wave rally. After its completion, a final E-wave decline could potentially breach the $60,000 level. 3. **Bearish Scenario 2 (Larger Correction):** The entire move down from $126,200 to $60,000 was a large A-wave. The current rally is a B-wave correction within a larger A-B-C structure, to be followed by a C-wave decline below $60,000. *Analysis suggests Scenario 2 is less probable due to time disproportions between waves. The battle is effectively between the Bullish Scenario (1) and Bearish Scenario (3).* **Key BTC Levels & Weekly Strategy** On the 4-hour chart, BTC trades above a crucial consolidation zone ("Central Pivot C"). * **Key Resistance:** $83,500-$84,500; $89,000-$90,500. * **Key Support:** $78,500-$79,500 (pivot upper bound); $73,500-$75,000; $69,500-$70,500. **Weekly Outlook:** The market direction hinges on BTC's ability to hold above or break below the $78,500-$79,500 support zone. * **Mid-term Strategy:** Neutral/Wait-and-see stance due to unclear direction. * **Short-term Tactics:** Two contingency plans using 30% max capital: * **Plan A (Bullish):** Look for long entries if price holds above $78,500-$79,500 with confirming signals. Initial stop-loss below $78,500. * **Plan B (Bearish):** Consider short positions if price breaks below $73,500-$75,000 with confirming signals. Initial stop-loss above $76,500. **HYPE Analysis & Strategy** HYPE's daily chart shows a seven-segment structure from its January low of $20.46, forming a "rising pivot" zone. * **Key Level to Watch:** $45.76 (previous high). A break above would confirm the bullish structure remains intact. * **Short-term Strategy:** Focus on pivot zone boundaries ($38.41 upper, $34.44 lower). * **Long:** Consider on support near $38.41 with bullish confirmation signals. * **Short:** Consider on a break below $34.44 with bearish confirmation signals. * Position size must be below 30% with strict stop-loss discipline. **Risk Management Reminder:** Always set an initial stop-loss upon entry. Move stop-loss to breakeven at +1% profit, then trail it upwards to lock in profits dynamically. All views are based on technical analysis for informational purposes only and do not constitute investment advice. The market is inherently risky.

Odaily星球日报25 мин. назад

Three Scenarios for BTC's Future Direction and a Duel Between Two Strong Forces | Special Invited Analysis

Odaily星球日报25 мин. назад

Sequoia Interview with Hassabis: Information is the Essence of the Universe, AI Will Open Up Entirely New Scientific Branches

Demis Hassabis, co-founder and CEO of Google DeepMind and Nobel laureate, discusses the path to AGI and its profound implications in a Sequoia Capital interview. He outlines his lifelong dedication to AI, tracing his journey from game development (e.g., *Theme Park*)—a perfect AI testing ground—to neuroscience and finally founding DeepMind in 2009. He emphasizes the critical lesson of being "5 years, not 50 years, ahead of time" for successful entrepreneurship. Hassabis reiterates DeepMind's two-step mission: first, solve intelligence by building AGI; second, use AGI to tackle other complex problems. He highlights the transformative potential of "AI for Science," particularly in biology where tools like AlphaFold have revolutionized protein folding. He envisions AI-powered simulations drastically shortening drug discovery from years to weeks and enabling personalized medicine. Furthermore, he predicts AI will spawn new scientific disciplines, such as an engineering science for understanding complex AI systems (mechanistic interpretability) and novel fields enabled by high-fidelity simulators for complex systems like economics. He posits a fundamental worldview where information, not just matter or energy, is the essence of the universe, making AI's information-processing core uniquely suited to understanding reality. He defends classical Turing machines as potentially sufficient for modeling complex phenomena, including quantum systems, as demonstrated by AlphaFold. On consciousness, Hassabis suggests first building AGI as a powerful tool, then using it to explore deep philosophical questions. He believes components like self-awareness and temporal continuity are necessary for consciousness but that defining it fully remains an open challenge. He predicts AGI could arrive around 2030 and, once achieved, would be used to probe the deepest questions of science and reality, much as envisioned in David Deutsch's *The Fabric of Reality*.

链捕手43 мин. назад

Sequoia Interview with Hassabis: Information is the Essence of the Universe, AI Will Open Up Entirely New Scientific Branches

链捕手43 мин. назад

Morgan Stanley 2026 Semiconductor Report: Buy Packaging, Buy Testing, Buy China Chips, Avoid Traditional Tracks

Morgan Stanley 2026 Semiconductor Report: Buy Packaging, Buy Testing, Buy Chinese Chips; Avoid Traditional Segments. The core theme is the shift in AI compute supply from NVIDIA dominance to a three-track system of GPU + ASIC + China-local chips. The key opportunity is capturing share in this expansion, while non-AI semiconductors face marginalization due to resource reallocation to AI. Key investment conclusions, in order of priority: 1. **Advanced Packaging (CoWoS/SoIC) - Highest Conviction**: TSMC is the primary beneficiary of explosive demand, driven by massive cloud capex. Its pricing power and AI revenue share are rising significantly. 2. **Test Equipment - Undervalued & High-Growth Certainty**: Chip complexity is causing test times to double generationally, structurally driving handler/socket/probe card demand. Companies like Hon Hai Precision (Foxconn), WinWay, and MPI offer compelling value. 3. **China AI Chips (GPU/ASIC) - Long-Term Irreversible Trend**: Export controls are accelerating domestic substitution. Companies like Cambricon, with firm customer orders and SMIC's 7nm capacity support, are positioned to benefit from lower TCO (30-60% vs NVIDIA) and growing local cloud demand. 4. **Avoid Non-AI Semiconductors (Consumer/Auto/Industrial)**: These segments face a weak, structurally hindered recovery due to AI's resource "crowding-out" effect on capacity and supply chains. 5. **Memory - Severe Internal Divergence**: Strongly favor HBM (Hynix primary beneficiary) and NOR Flash (Macronix). Be cautious on interpreting price rises in DDR4/NAND as true demand recovery. The report emphasizes a 2026-2027 time window, stating the AI capital expenditure cycle is far from over. Key macro variables include persistent export controls and AI's systemic "crowding-out" effect on traditional semiconductor supply chains.

marsbit1 ч. назад

Morgan Stanley 2026 Semiconductor Report: Buy Packaging, Buy Testing, Buy China Chips, Avoid Traditional Tracks

marsbit1 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

2025 год — год институциональных инвесторов, в будущем он будет доминировать в приложениях реального времени.

1.8k просмотров всегоОпубликовано 2025.12.16Обновлено 2025.12.16

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на AI (AI) представлены ниже.

活动图片