Editor: Sonal Chokshi, a16z

Translated by: Tim, PANews

Stablecoins, RWA, Payments, and Finance

Better and Smarter On/Off-Ramp for Stablecoins

Last year, the trading volume of stablecoins was estimated to reach $46 trillion, continuously setting historical records. Specifically, this is more than 20 times the trading volume of the payment platform PayPal; nearly 3 times that of Visa, one of the world's largest payment networks; and is rapidly approaching the transaction scale of the U.S. Automated Clearing House (ACH), which processes electronic transactions like direct deposits.

Today, transfers of stablecoins can be completed in less than one second at a cost of less than one cent. However, the unresolved issue is how to connect these cryptocurrencies with the financial infrastructure that people use in their daily lives. In other words, it is about establishing exchange channels between stablecoins and traditional currencies.

A new generation of startups is filling this gap by linking stablecoins with mainstream payment systems and local currencies. Some companies use cryptographic verification technology to allow people to exchange local account balances for digital dollars. Others connect to regional payment networks, utilizing features like QR codes and real-time payment systems for interbank transfers. Additionally, some companies are building truly interoperable global digital wallet layers and issuance platforms, enabling users to pay with stablecoins at everyday merchants. These innovations collectively broaden the participation in the digital dollar economy and are expected to accelerate the direct adoption of stablecoins as a mainstream payment method.

As these on/off-ramps mature, digital dollars will begin to directly connect with local payment systems and merchant toolboxes, giving rise to new behavioral patterns. Workers can receive cross-border salaries in real-time, merchants can accept globally circulating digital dollars without needing a bank account, and payment applications can achieve instant settlement of value with users around the world. Stablecoins will fundamentally transform from marginal financial tools into the foundational settlement layer of the internet.

——Jeremy Zhang, a16z crypto engineering team

Understanding RWA and Stablecoins in a More Crypto-Native Way

We have observed a strong interest from banks, fintech companies, and asset management firms in bringing traditional assets such as U.S. stocks, commodities, and indices on-chain. As more traditional assets are tokenized, this tokenization often remains superficial, still limited to the current concept of real-world assets, failing to fully leverage the crypto-native characteristics.

However, synthetic products like perpetual contracts can provide deeper liquidity and are generally easier to implement. Perpetual contracts also offer an easy-to-understand leverage mechanism, which is why I believe they are the crypto-native derivatives with the strongest product-market fit. At the same time, I also believe that emerging market stocks are one of the asset classes most suitable for perpetualization. (The liquidity of zero-date options markets for certain stocks often exceeds that of the spot market, providing an intriguing experimental case for perpetualization.)

Ultimately, this is a choice between "perpetualization and tokenization." Regardless, we expect to see more crypto-native RWA asset tokenization in the coming year.

Following a similar line of thought, by 2026, we will see more "native issuance" of stablecoins, rather than just tokenization. Stablecoins will become mainstream in 2025, with the number of issued stablecoins continuing to grow.

However, stablecoins lacking a strong credit infrastructure appear like narrow banks, holding specific liquid assets considered ultra-safe. While narrow banks are a legitimate financial product, I believe they will not become the backbone of the on-chain economy in the long run.

Recently, many new asset managers, curators, and protocols have emerged, starting to offer asset-backed loans on-chain using off-chain assets as collateral. These loans are typically initiated off-chain before being tokenized. I believe that tokenization offers little benefit in this regard, except possibly for allocation to users already on-chain. This is why debt assets should be initiated on-chain rather than tokenized after being initiated off-chain. On-chain initiation can reduce loan management costs, backend structural costs, and improve accessibility. The challenging part will be compliance and standardization, but builders are already working to address these issues.

——Guy Wuollet, a16z crypto general partner

Stablecoins Initiate a Banking Ledger Upgrade Cycle and New Payment Scenarios

The software systems that banks operate are often unfamiliar to modern developers: in the 1960s and 70s, the banking industry was a pioneer of large software systems. The second generation of core banking systems emerged in the 80s and 90s (for example, through Temenos's GLOBUS and InfoSys's Finacle). However, these software systems have aged and are updated slowly. Therefore, the banking industry, especially the critical core ledger systems that record deposits, collateral, and other debts, still often run on mainframes, programmed in COBOL, and interact through batch file interfaces rather than APIs.

The vast majority of global assets rely on these decades-old core ledgers. While these systems are well-tested, trusted by regulators, and deeply integrated into complex banking business scenarios, they also hinder innovation. Adding key features like real-time payments can take months or even years and requires overcoming layers of technical debt and regulatory complexity.

This is where stablecoins come into play. The past few years have not only seen stablecoins find product-market fit and enter the mainstream, but this year traditional financial institutions have embraced them in unprecedented ways. Stablecoins, tokenized deposits, tokenized government bonds, and on-chain bonds enable banks, fintech companies, and financial institutions to develop new products and serve new customers. More importantly, they do not require these institutions to rewrite those traditional systems that, while outdated, have been operating stably for decades. Therefore, stablecoins provide a new path for institutional innovation.

——Sam Broner

Internet Banking

As agents emerge on a large scale and more business activities are conducted automatically in the background rather than through user clicks, the flow of money to value needs to change.

In a world driven by intent rather than step-by-step instructions, AI agents can mobilize funds by identifying needs, fulfilling obligations, or triggering outcomes, and value must flow as quickly and freely as today's information transmission. This is where blockchain, smart contracts, and on-chain protocols come into play.

Smart contracts can already complete global dollar payment settlements in seconds. By 2026, emerging primitives like x402 will make settlements programmable and responsive: agents can achieve instant permissionless payments for data, GPU computing power, or API calls without needing to issue invoices, reconcile, or batch process. Software updates released by developers will come with built-in payment rules, limits, and audit trails, without requiring fiat integration, merchant onboarding, or financial institution involvement. Prediction markets can self-settle in real-time as events unfold, such as dynamic odds updates, allowing agents to trade freely, with global payout settlements completed in seconds, all without the involvement of custodians or exchanges.

Once value can flow in this way, the "payment flow" will no longer be a separate operational layer but will transform into a network behavior: banks will become the foundational pipeline of the internet, and assets will become infrastructure. When money transforms into internet-routable packets of information, the internet will not only support the financial system; it will become the financial system itself.

——Christian Crowley and Pyrs Carvolth, a16z crypto GTM team

Democratization of Wealth Management

Traditionally, personalized wealth management services have been the exclusive domain of high-net-worth clients of banks: providing customized advice and achieving personalized portfolio allocations across different asset classes is not only costly but also extremely complex. However, as more asset classes become tokenized, personalized strategies combining AI recommendations and collaborative systems can be executed and rebalanced instantly and at low cost.

This is not just within the realm of robo-advisors; today, everyone can access active investment portfolio management, no longer limited to passive management. By 2025, traditional financial institutions increased their exposure to cryptocurrencies (either through direct investment or via ETPs), but this is just the beginning. By 2026, we will see platforms emerging that focus on "wealth growth," rather than merely "wealth preservation." Fintech companies (like Revolut and Robinhood) and centralized exchanges (like Coinbase) will leverage their technological advantages to capture more market share.

Meanwhile, DeFi tools like Morpho Vaults can automatically allocate assets to lending markets with the best risk-adjusted returns, providing core yield-generating asset allocation for portfolios. Holding remaining liquidity balances in stablecoins rather than fiat and investing in RWA money market funds instead of traditional money market funds can further enhance yield potential.

Finally, retail investors can now more easily invest in private market assets with lower liquidity, such as private credit, pre-IPO companies, and private equity, with tokenization helping to unlock the potential of these markets while still meeting compliance and reporting requirements. As various assets in a balanced portfolio become tokenized (with risk ranges from bonds and stocks to private investments and alternative investments), portfolios can automatically rebalance without the need for fund transfers and other procedures.

——Maggie Hsu, a16z crypto GTM team

AI and Agency

From "Know Your Customer" (KYC) to "Know Your Agent" (KYA)

The constraints of the agent economy are gradually shifting from intelligence levels to identity verification.

In the financial services industry, the number of "non-human identities" has exceeded that of human employees by 96 times, yet these identities remain unaccounted for. The missing key foundation here is KYA: Know Your Agent.

Just as humans need credit scores to obtain loans, agents (AI agents) also need cryptographic signature credentials to conduct transactions, linking the agent to its authorized entity, operational limits, and liability. Until this mechanism is perfected, merchants will continue to intercept agents at the firewall level. The KYC infrastructure built over decades must now solve the KYA challenge within months.

——Sean Neville, Co-founder of Circle, architect of USDC, and current CEO of Catena Labs

We Will Leverage AI to Complete Research Work

As a mathematical economist, I found it difficult to get general AI models to understand my workflow back in January. By November, I was able to issue abstract instructions to the model as if I were guiding a PhD student, and they sometimes even provided novel and correct answers. Beyond my personal experience, we are witnessing AI being applied in broader research fields, particularly in reasoning, where current models can not only assist directly in scientific discovery but also autonomously solve Putnam math competition problems (which may be the most challenging math exam at the university level globally).

The question of which fields will benefit the most from these research assistance tools and how they will function remains open. However, I anticipate that AI research will give rise to and reward a new type of polymathic research model: one that favors the ability to infer connections between different concepts and quickly deduce from more speculative answers. These answers may not be precise, but they can still point in the right direction (at least within a certain topological structure). Ironically, this is somewhat akin to harnessing the power of model hallucinations: when models are sufficiently "intelligent," allowing them abstract space for divergent thinking may still produce meaningless content, but it can sometimes lead to breakthrough discoveries, just as human creativity often flourishes in nonlinear, non-explicitly directed thought.

Reasoning in this manner will require a new AI workflow, not just interactions between individual agents, but a nested agent model operation, where multiple layers of models help researchers evaluate early research ideas and gradually eliminate falsehoods to ultimately distill valuable content. I have been using this approach to write papers, while others have employed it for patent searches, creating new forms of art, or (unfortunately) discovering new types of smart contract attacks.

However, running such a nested agent research system requires better interoperability between models and a mechanism to identify and reasonably compensate each model's contributions. These are two key issues that cryptographic technology is expected to help resolve.

——Scott Kominers, a16z crypto research team member, Harvard Business School professor

The Invisible Tax of Open Networks

The rise of AI agents is imposing an invisible tax on open networks, fundamentally disrupting their economic foundations. This disruption stems from the increasing misalignment between the internet's contextual layer and its execution layer: currently, AI agents extract data from ad-dependent websites (the contextual layer) while providing convenience to users, systematically bypassing the revenue channels that support content creation (such as advertising and subscription models).

To prevent the erosion of open networks and protect the diverse content that drives AI development, we need to deploy technological and economic solutions on a large scale. This may include next-generation sponsorship schemes, attribution systems, or other novel funding models. Existing AI licensing agreements are proving to be stopgap measures, often compensating content providers only a fraction of the revenue lost due to AI siphoning traffic.

The network needs a new economic model where value can flow automatically. A key shift in the coming year will be from static licensing to real-time, usage-based compensation mechanisms. This means testing and promoting relevant systems, possibly leveraging blockchain-enabled nano-payments and precise traceability standards to automatically reward every entity that provides information for AI agents to successfully complete tasks.

——Liz Harkavy, a16z crypto investment team

Privacy and Security

Privacy Will Become the Most Important Moat in the Crypto Space

Privacy is a key requirement for the on-chain operation of global finance, yet it is a characteristic that almost all existing blockchains currently lack. For most blockchains, privacy features are merely an afterthought.

However, privacy itself is now sufficient to distinguish one blockchain from all others. Moreover, privacy plays an even more critical role: it creates an on-chain lock-in effect, which could be termed a privacy network effect. This is particularly important in a world where performance alone can no longer differentiate competitors.

With bridging protocols, as long as all information is public, migration between different blockchains becomes effortless. However, once private information is involved, the situation changes entirely: bridging tokens is easy, but bridging secrets is extremely difficult. There is always a risk of being identified by a monitored blockchain, memory pool, or network traffic when entering or exiting a private zone. Crossing the boundaries between private chains and public chains, or even between two private chains, can leak various metadata, such as the correlation of transaction times and sizes, making it easier to track others.

Compared to many homogeneous new chains (whose fees are likely driven to zero due to competition, as there is no essential difference in block space across chains), privacy-enabled blockchains often form stronger network effects. The reality is that if a "generic" public chain lacks a thriving ecosystem, killer applications, or distribution advantages, users or developers have little reason to use it or build on it, let alone remain loyal to it.

When users utilize public chains, they can easily transact with users on other chains, making the choice of which chain to join less important. However, when users use private chains, the choice of which chain is crucial, as once they join a particular chain, the likelihood of migration is low, and they bear the risk of privacy exposure, creating a winner-takes-all scenario. Given that privacy protection is vital for most real-world applications, a few privacy-protecting chains may dominate the entire crypto market.

——Ali Yahya, a16z crypto general partner

Future Messaging Needs to Be Quantum-Resistant and Decentralized

As the world prepares for the quantum era, many encryption-based communication applications (such as Apple iMessage, Signal, WhatsApp) have led the way and made significant contributions. However, the problem is that all mainstream communication software relies on our trust in privately operated servers run by a single organization. These servers are easy targets for government shutdowns, backdoor implants, or coercion to hand over private data.

If a country can shut down an individual's server, if a company holds the keys to a private server, or if a company owns a private server, then what use is quantum encryption? Private servers require people to "trust me," but without private servers, it means "you don't need to trust me." Communication does not need a company to act as an intermediary. Information transmission requires open protocols, and we should not have to trust anyone.

The way to achieve this is through the decentralization of the network: no private servers, no reliance on a single application, all using open-source code, and equipped with top-notch encryption technology, including defenses against quantum computing threats. In an open network, no individual, company, nonprofit organization, or state can strip us of our communication capabilities. Even if a country or company shuts down one application, 500 new versions will emerge the next day. Even if a node is shut down, new nodes will immediately take its place, driven by the economic incentives brought by technologies like blockchain.

When people can own their information through private keys just as they own currency, everything will change. Applications may come and go, but people will always control their information and identity, allowing end users to truly own their information, even if they do not own the application itself.

This is not just a matter of surpassing quantum defenses and encryption technology; it also concerns ownership and decentralization. If either is missing, what we build is merely an encryption system that appears unbreakable but can still be shut down at any time.

——Shane Mac, Co-founder and CEO of XMTP Labs

Privacy as a Service

Behind every model, agent, and automated process lies a simple element: data. However, today, most data pipelines, whether inputting or outputting data from models, are opaque, volatile, and difficult to audit. This may be acceptable for some consumer applications, but for many industries and users (such as finance and healthcare), businesses must protect the privacy of sensitive data. This is also a major obstacle faced by many institutions hoping to achieve RWA tokenization.

So how can we promote secure, compliant, autonomous, and globally interoperable innovation while protecting privacy? There are many methods, but I want to focus on data access control: who controls sensitive data? How does it flow? And who (or what) can access it?

In the absence of data access control mechanisms, users wishing to ensure data confidentiality currently have to rely on centralized service platforms or build customized systems. This approach is not only time-consuming and costly but also hinders entities like traditional financial institutions from fully unleashing the functional advantages of on-chain data management. As intelligent agent systems begin to autonomously browse, trade, and make decisions, users and institutions across industries need cryptographic verification mechanisms, rather than merely relying on a "best-effort trust model."

This is why I believe we need "privacy as a service": this new technology can provide programmable native data access rules, client-side encryption, and decentralized key management, precisely controlling who can decrypt which data under what conditions and within what time frame, all executed on-chain. Combined with verifiable data systems, data privacy protection will thus be upgraded to a core component of the internet's foundational public infrastructure, rather than just a remedial application layer patch, making privacy protection a true core infrastructure.

——Adeniyi Abiodun, Co-founder and Chief Product Officer of Mysten Labs

From "Code is Law" to "Rules are Law"

Recently, some battle-tested DeFi protocols have suffered from hacking attacks, despite having strong teams, rigorous auditing processes, and years of stable operation. These events highlight a disturbing reality: the current industry's security standards still primarily rely on case-by-case and experiential judgments.

To mature, DeFi security needs to shift from vulnerability patterns to design aspects, from "best effort" to "principled" approaches:

In static deployment and pre-deployment phases (testing, auditing, formal verification), this means systematically verifying global invariants rather than just validating manually filtered local invariants. Several teams are currently developing AI-assisted proof tools that can help draft technical specifications, propose invariant hypotheses, and significantly reduce the manual proof engineering that has historically led to excessively high verification costs.

In dynamic, post-deployment phases (runtime monitoring, runtime execution, etc.), these invariance conditions can be transformed into dynamic guardrails, serving as the last line of defense. These guardrails will be directly encoded as runtime assertions that every transaction must satisfy.

In this way, we will no longer assume that all vulnerabilities can be discovered; instead, we will enforce key security properties in the code, and any transaction that violates these properties will be automatically rolled back.

This is not just theoretical. In practice, almost all exploitation attacks trigger one of these security checks during execution, potentially preventing the hacker's attack. Therefore, the once-popular notion of "code is law" has evolved into "rules are law": even new types of attack methods must meet the security property requirements that maintain system integrity, so the remaining attack methods are either trivial or extremely difficult to execute.

——Daejun Park, a16z crypto engineering team

Other Tracks and Applications

Prediction Markets Becoming Bigger, Broader, and Smarter

Prediction markets have gradually become mainstream, and next year, with their integration with cryptocurrencies and artificial intelligence, they will only become bigger, broader, and smarter, while also presenting new challenges that entrepreneurs need to address.

First, there will be more contracts listed. This means we will not only be able to obtain real-time odds for major elections or geopolitical events but also for various niche outcomes and complex cross-events. As these new contracts emerge, bringing more information and becoming part of the news ecosystem (which is already a reality), they will raise important social issues regarding how we should weigh the value of this information and how to optimize designs to make them more transparent, auditable, and full of possibilities, all of which are achievable through cryptocurrencies.

To cope with the significant increase in contracts, we need new consensus methods to verify the authenticity of contracts. Centralized platform adjudication (e.g., did a specific event occur? How to confirm it?) is crucial, but controversial cases like the Zelensky lawsuit and the Venezuelan election have exposed its limitations. To address these edge cases and help prediction markets expand into more practical application areas, new decentralized governance mechanisms and large language model oracles will assist in determining the factual truth in disputed outcomes.

The potential of artificial intelligence in predictive capabilities has been astonishing. For example, AI agents operating on these platforms can globally scan trading signals to gain short-term trading advantages, helping to uncover new dimensions of understanding the cognitive world and enhancing the ability to predict future events. These agents can serve not only as high-level political analysts for human consultation but also reveal the predictive factors of complex social events when we study their strategies.

Can prediction markets replace opinion polls? No, they can make opinion polls better (and polling information can also be input into prediction markets). As a political scientist, I am most interested in how prediction markets can work in synergy with a rich and vibrant polling ecosystem, but we need to leverage new technologies like artificial intelligence to improve the survey experience and use cryptocurrencies to provide new methods to prove that poll respondents are real people and not bots.

——Andy Hall, a16z crypto research advisor, Professor of Political Economy at Stanford University

The Rise of Betting Media

The so-called objectivity has been cracking in traditional media models for some time. The internet has given everyone a platform to voice their opinions, and more operators, practitioners, and builders are now speaking directly to the public. Their viewpoints reflect their stakes in the world, and contrary to intuition, audiences respect them; they not only do not mind that they have their own interests at play but are welcomed for that very reason.

The innovation here is not the rise of social media but the arrival of cryptographic tools that allow people to make publicly verifiable commitments. Artificial intelligence enables the cheap and easy generation of infinite content, claiming anything from any viewpoint or identity (whether real or fictional), relying solely on the words of people (or bots) may seem insufficient. Tokenized assets, programmable lock-ups, prediction markets, and on-chain historical records provide a more solid foundation for trust: a commentator can publish an argument while proving they are putting real money on the line. A podcast host can lock tokens to indicate they are not opportunistically buying and selling or "pump and dumping." An analyst can link predictions to publicly settled markets, creating an auditable trail.

I see this as an early form of "betting media": this type of media not only embraces the idea of "self-interest" but can also provide corresponding proof. In this model, credibility does not come from pretending to be neutral or from empty assertions but from the actual stakes corresponding to your willingness to make publicly verifiable commitments. Betting media will not replace other forms of media; it is a complement to existing media. It provides a new signal: no longer "trust me, I am neutral," but rather "this is the risk I am willing to take, and you can verify that what I say is true."

——Robert Hackett, a16z crypto editorial team

Cryptocurrencies Provide a New Building Block with Applications Beyond Blockchain

For years, SNARKs (a cryptographic proof technology that verifies computation results without re-executing the calculations) have been primarily confined to the blockchain space. The overhead has been too high: the workload required to generate computational proofs can be up to a million times greater than executing the computation directly. This overhead is justifiable when it can be distributed across thousands of validating nodes, but it becomes impractical in any other scenario.

This situation is about to change. By 2026, the overhead of zkVM provers will drop to about ten thousand times, with memory usage requiring only a few hundred megabytes, making it fast enough to run smoothly on mobile devices and low-cost enough to be deployed anywhere. The reason ten thousand times is significant is that the parallel throughput of high-end GPUs is about ten thousand times that of laptop CPUs. By the end of 2026, a single GPU will be able to generate proofs in real-time that a CPU would execute.

This could unlock the vision in old research papers: verifiable cloud computing. If you are already running CPU workloads in the cloud, whether due to insufficient computational capacity for GPU processing, lack of relevant expertise, or legacy system reasons, you will be able to obtain cryptographic proofs of the correctness of computational results at a reasonable price. The prover itself is optimized for GPUs, and your code does not need to be adjusted accordingly.

——Justin Thaler, a16z crypto research team, Associate Professor of Computer Science at Georgetown University

Light Trading, Heavy Building

Treating trading as a transit point rather than an endpoint is the business philosophy of crypto enterprises.

Today, aside from stablecoins and some core infrastructure, it seems that every well-developed crypto company is pivoting to or planning to pivot to trading. But what would happen if "every crypto company became a trading platform"? A large number of companies crowding into the same business will only lead most participants to engage in self-destructive competition, ultimately leaving only a few winners. This means that those hastily turning to trading are missing the opportunity to build a more defensive and sustainable business model.

While I deeply sympathize with founders striving to keep their businesses financially afloat, the pursuit of immediate product-market fit comes at a cost. In the crypto space, this issue is particularly pronounced. The unique atmosphere surrounding tokens and speculation often leads founders down the path of seeking instant gratification in their quest for product-market fit. It can be likened to a marshmallow experiment.

Trading itself is not inherently wrong; it is an important market function, but it does not have to be the final destination. Founders who focus on the "product" part of product-market fit may be more likely to become the ultimate winners.

——Arianna Simpson, a16z crypto general partner

How to Unlock the Full Potential of Blockchain After Legal and Technical Alignment

One of the biggest obstacles to creating blockchain in the United States over the past decade has been legal uncertainty. Securities laws have been misapplied, and selective enforcement has often forced founders to adhere to regulatory frameworks designed for ordinary companies rather than those tailored for blockchain. For years, businesses have substituted product strategy with risk mitigation, relegating engineers to the background while lawyers have taken center stage.

This situation has given rise to many strange phenomena: founders are advised to remain opaque. Token distribution has become arbitrary, relying solely on legal evasion. Governance mechanisms have devolved into mere theatrics. Organizational structures exist only for compliance, not effectiveness. Token designs deliberately avoid economic value and even shy away from business models. Worse still, those crypto projects skirting the edges of the rules often outperform those honest builders.

However, regulatory structures around crypto markets are closer than ever to being enacted, which could eliminate all these distortions next year. If the bill passes, it will incentivize industry transparency, establish clear standards, and provide clearer structured pathways for financing, token issuance, and decentralization processes, replacing the current "enforcement roulette" regulatory state. After the passage of the GENIUS Act, stablecoins have seen explosive growth; legislation surrounding the structure of crypto markets will bring even more significant changes, but this time the transformation will primarily target the network ecosystem.

In other words, such regulation will enable blockchain to truly operate as a network, remaining open, autonomous, composable, trustlessly neutral, and decentralized.

——Miles Jennings, a16z crypto policy team and General Counsel

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