17 Insights on the Future Summarized by Multiple Partners from a16z

Author: a16z New Media

Translation: Deep Tide TechFlow

Over the past two days, we have shared insights on infrastructure, growth, life sciences and health, Speedrun, applications, and the challenges and opportunities that builders are expected to face in 2026, as identified by the American Vitality Team.

Today, we will share 17 insights about the future summarized by several partners in the a16z crypto space (along with some invited contributors). These topics cover everything from smart agents and artificial intelligence (AI), stablecoins, tokenization and finance, privacy and security, to prediction markets, SNARKs (zero-knowledge proof technology), and other applications… as well as how to build for the future. (To stay updated on trend updates, builder guides, industry reports, and other resources in the crypto space, be sure to subscribe to the a16z crypto newsletter.)

Tomorrow, we will conclude the week with a special announcement and an exclusive invitation from a16z, so don’t miss it!

Here are our highlights for today:

Privacy Will Become the Most Important Moat in the Crypto Space

Privacy is one of the key features driving the on-chain transformation of global finance, yet it is a component that is almost entirely missing from current blockchains. For most blockchains, privacy is merely a secondary or even overlooked feature.

However, today, privacy itself is compelling enough to allow a chain to stand out among numerous competitors. More importantly, privacy can create a "chain lock effect," which could even be termed a "privacy network effect." In a world where mere performance competition is no longer sufficient, this effect becomes particularly significant.

Due to the existence of cross-chain bridge protocols, as long as everything is public, migrating from one chain to another becomes extremely simple. However, once privacy is introduced, that convenience disappears: migrating tokens is easy, but migrating secrets is difficult. When transferring from a privacy chain to a public chain, or between two privacy chains, there are always risks, such as third parties observing on-chain transactions, mempool activity, or network traffic that could identify your identity. Crossing the boundaries between privacy chains and public chains, or even between two privacy chains, can leak various metadata, such as the correlation of transaction times and sizes, making tracking easier.

Compared to many homogeneous new chains, the fees of these new chains may drop to zero due to competition (the nature of block space has become similar across chains), and blockchains with privacy features can form stronger network effects. In fact, if a "general-purpose" blockchain does not have a thriving ecosystem, killer applications, or asymmetric distribution advantages, there is almost no reason to attract users to use or develop it, let alone user loyalty.

On public blockchains, users can easily transact with users on other chains—what chain they join does not matter. However, on privacy blockchains, which chain a user chooses becomes particularly important, as once they join a chain, they are less willing to migrate to avoid exposure risks. This phenomenon creates a "winner-takes-all" dynamic. And since privacy is a necessary condition for most real-world scenarios, a few privacy chains may dominate a large portion of the crypto market.

—Ali Yahya, Partner in the a16z Crypto Space

Prediction Markets: A Future of Greater Scale, Broader Scope, and Increased Intelligence

Prediction markets have moved from niche to mainstream, and in the upcoming year, they will become larger in scale, broader in scope, and smarter at the intersection of crypto technology and artificial intelligence (AI), while also presenting new significant challenges for builders.

First, there will be more contracts listed. This means we can not only obtain real-time probabilities about major elections or geopolitical events but also understand various intricate outcomes and complex intersecting events. As these new contracts reveal more information and gradually integrate into the news ecosystem (a trend that has already begun), they will also raise important social issues, such as how to balance the value of this information and how to better design these markets to make them more transparent and auditable—issues that can be addressed through crypto technology (SC will link to our related articles>).

To cope with the larger number of contracts, we need new ways to reach consensus on the truth to resolve contract issues. The solutions provided by centralized platforms (Did the event really happen? How do we confirm it?) are crucial, but controversial cases like the Zelensky lawsuit market and the Venezuelan election market expose their limitations. To address these edge cases and help prediction markets expand into more useful application scenarios, new decentralized governance and oracle systems based on large language models (LLMs) can help determine the truth of disputed outcomes.

AI applications in oracles can also go beyond LLMs. For example, AI agents trading on these platforms can search for global signals, providing advantages for short-term trading, thereby revealing new insights about the world and predicting what might happen in the future. (Projects like Prophet Arena have already showcased the potential in this field.) Besides serving as complex political analysts for us to query insights, studying the strategies of these agents may also reveal fundamental predictive factors of complex social events.

Will prediction markets replace polls? No; they will make polls better (and poll 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 this relies on new technologies, such as AI, which can improve the polling experience; and crypto technology, which can provide new ways to prove that poll/survey participants are human rather than bots, among other functionalities.

—Andy Hall, a16z Crypto Research Advisor (and Professor of Political Economy at Stanford University)

Viewing Tokenization of Real Assets and Stablecoins from a More "Crypto-Native" Perspective

We have seen banks, fintech companies, and asset management firms show strong interest in bringing U.S. stocks, commodities, indices, and other traditional assets on-chain. However, as more traditional assets go on-chain, this tokenization is often "reified"—based on current perceptions of real assets, failing to fully leverage crypto-native characteristics.

But synthetic representations like perpetual contracts (perps) not only provide deeper liquidity but are also generally easier to implement. Perpetual contracts also have easily understandable leverage mechanisms, making them the most aligned derivatives with the needs of the crypto market. I also believe that emerging market stocks are one of the asset classes most worthy of "perpetualization" (perpify). (For example, the liquidity of some stocks' "0-day-to-expiration options" (0DTE) markets is even higher than that of the spot market, providing a very interesting experimental opportunity for perpetualization.)

This boils down to the question of "perpetualization vs. tokenization"; however, we should see more crypto-native real asset (RWA) tokenization in the coming year.

Similarly, in 2026, after stablecoins enter the mainstream in 2025, we will see more trends of "issuance, not just tokenization," with the outstanding issuance of stablecoins continuing to grow.

However, stablecoins without a strong credit infrastructure resemble "narrow banks," holding only specific liquid assets deemed particularly safe. While narrow banks are an effective product, I do not believe they will become the backbone of the on-chain economy in the long term.

We have already seen many new asset managers, curators, and protocols begin facilitating on-chain asset-backed loans based on off-chain collateral. These loans are often initiated off-chain before being tokenized. However, I believe that in this case, the benefits of tokenization are limited, perhaps only facilitating the distribution of assets to users already on-chain. Therefore, debt assets should be initiated directly on-chain rather than first off-chain and then tokenized. On-chain initiation can reduce the costs of loan servicing and backend structuring, and improve accessibility. The challenge lies in compliance and standardization, but developers are already working to address these issues.

—Guy Wuollet, General Partner in the a16z Crypto Space

The Transit Hub of Crypto Business: Trading is Not the Final Destination

Today, apart from stablecoins and some core infrastructure, almost every well-performing crypto company has turned or is turning to trading business. But if "every crypto company becomes a trading platform," what will the future of the industry look like? When too many players are doing the same thing, it not only dilutes each other's market attention but also leads to only a few large companies becoming winners. This also means that companies that prematurely turned to trading missed the opportunity to build more defensive and sustainable businesses.

While I have great sympathy for entrepreneurs striving to make their companies financially viable, chasing short-term product-market fit also comes at a cost. This issue is particularly pronounced in the crypto space, as the unique dynamics of tokens and speculation can lead entrepreneurs to favor instant gratification in their search for product-market fit… this can be seen as a kind of "marshmallow test" (referring to the test of delayed gratification). Trading itself is not wrong; it is an important function of the market, but it is not necessarily the ultimate destination for business development. Entrepreneurs who focus on the "product" part of product-market fit may ultimately become the bigger winners.

—Arianna Simpson, Partner in the a16z Crypto Space

The Future of Stablecoins: Better, Smarter Entry and Exit Mechanisms

Last year, the trading volume of stablecoins was estimated to reach $46 trillion, continually setting new historical highs. To better understand this scale, it is equivalent to more than 20 times the trading volume of PayPal; nearly 3 times that of Visa, one of the world's largest payment networks; and rapidly approaching the trading volume of the U.S. Automated Clearing House (ACH)—the electronic network that processes financial transactions like direct deposits in the U.S.

Today, you can complete a stablecoin transaction in less than a second for less than a cent. However, the unresolved issue is how to connect these digital dollars to the financial systems that people use daily—in other words, how to build the onramps and offramps for stablecoins.

A new generation of startups is filling this gap by connecting stablecoins with more familiar payment systems and local currencies. Some companies use crypto proofs to allow people to privately exchange local balances for digital dollars. Others integrate with regional networks, utilizing features like QR codes and real-time payment rails to facilitate interbank payments… and some are building truly interoperable global wallet layers and issuance platforms that enable users to spend stablecoins at everyday merchants. These approaches collectively broaden the participation in the digital dollar economy and may accelerate the adoption of stablecoins as a mainstream payment method.

As these onramps and offramps gradually mature, digital dollars will directly connect to local payment systems and merchant tools, giving rise to new behavioral patterns: cross-border workers can receive their salaries in real-time; merchants can accept global dollar payments without needing a bank account; applications can achieve instant settlements with users anytime, anywhere. Stablecoins will transition from a niche financial tool to a foundational settlement layer of the internet.

—Jeremy Zhang, a16z Crypto Engineering Team

Stablecoins: Unlocking the Bank Ledger Upgrade Cycle and Opening New Payment Scenarios

Today, many banks still use software systems that modern developers find hard to recognize: in the 1960s and 70s, banks were early adopters of large software systems; by the 80s and 90s, second-generation core banking software (like Temenos's GLOBUS and InfoSys's Finacle) began to emerge. However, these systems have gradually aged, and the pace of upgrades has been too slow. As a result, the banking industry—especially the critical core ledger databases responsible for tracking deposits, collateral, and other obligations—still predominantly runs on mainframe computers, using COBOL programming language and relying on batch file interfaces rather than modern APIs.

The vast majority of global assets still depend on these core ledgers that have been in place for decades. Although these systems have been validated through long-term practice, gained the trust of regulators, and are deeply integrated into complex banking scenarios, they simultaneously hinder innovation. For instance, adding key features like real-time payments (RTP) to these systems may take months or even years, and requires navigating layers of technical debt and regulatory complexity.

This is where stablecoins shine. Over the past few years, stablecoins have not only found product-market fit and entered the mainstream, but this year, traditional financial institutions (TradFi) have embraced stablecoins with a new level of enthusiasm. Stablecoins, tokenized deposits, tokenized government bonds, and on-chain bonds are enabling banks, fintech companies, and financial institutions to build new products and serve new customers. More importantly, these institutions can innovate without needing to completely rewrite their legacy systems—these legacy systems, while aging, have been stable and reliable for decades. Thus, stablecoins provide institutions with a new avenue for innovation.

—Sam Broner

Decentralization is the Future of Messaging, More Important than Quantum Encryption

As the world gradually moves toward the era of quantum computing, many encryption-based messaging applications (like Apple, Signal, WhatsApp) are leading the way and achieving remarkable results. However, the problem is that almost all major messaging applications rely on a private server operated by a single organization. These servers can easily become targets for government shutdowns, backdoor implants, or forced data retrieval.

If a country can shut down your server, if a company holds the keys to a private server, or even if a company merely owns a private server, then what is the significance of quantum encryption? Private servers require users to "trust me," but without a private server, it means "you don't need to trust me." Communication does not need an intermediary company to operate.

Messaging needs open protocols that allow users to trust no one. The way to achieve this is through decentralized networks: no private servers, no single applications, all code is open source, and top-notch encryption technology is employed—including quantum-resistant encryption.

Through open networks, no individual, company, nonprofit organization, or country can strip away our ability to communicate. Even if a country or company shuts down a particular application, 500 new versions will emerge the next day. Even if one node is shut down, the economic incentives brought by technologies like blockchain will prompt new nodes to immediately take its place.

When people control their messages through keys just as they do their money, everything will change. Applications may come and go, but users will always control their messages and identities. Even if an application fails, end users can still own their messages.

This is not just about quantum resistance and encryption; it is about ownership and decentralization. Without these two, what we build is merely an uncrackable yet still closable encrypted system.

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

From "Code is Law" to "Norms are Law"—A New Evolution in DeFi Security

Recent DeFi hacking incidents have targeted battle-tested protocols operated by strong teams that have undergone rigorous audits and have been live for years. These events reveal a disturbing reality: current security standard practices still largely rely on heuristics and case-by-case handling.

To further mature DeFi security, we need to shift from patching against vulnerability patterns to designing properties that ensure security, moving from "best efforts" to a "principled approach":

In the static/pre-deployment phase (testing, auditing, formal verification, etc.), this means systematically verifying global invariants rather than just validating handpicked local invariants. Today, multiple teams are building AI-assisted proof tools that can help write specifications, propose invariants, and share the burden of the previously expensive and time-consuming manual proof engineering work.

In the dynamic/post-deployment phase (runtime monitoring, runtime enforcement, etc.), these invariants can be transformed into real-time "guardrails"—serving as a last line of defense. These guardrails will be directly encoded as runtime assertions, ensuring that every transaction must satisfy these assertions.

Thus, we no longer assume that every vulnerability is captured in advance; instead, we embed critical security properties directly into the code, automatically rolling back any transactions that violate these properties.

This is not just theoretical. In practice, almost every attack that has occurred has triggered these checks during execution, potentially halting the hacker's actions. Therefore, the idea of "code is law" is evolving into "norms are law": even novel attacks must satisfy the security properties that maintain system integrity, leaving only minor or extremely difficult-to-execute attacks.

—Daejun Park, a16z Crypto Engineering Team

Cryptographic Technology Beyond Blockchain: Ushering in a New Era of Verifiable Computation

For years, SNARKs (Succinct Non-interactive Arguments of Knowledge)—a cryptographic proof technology that verifies computations without re-executing them—have been primarily applied in the blockchain space. This is due to their high computational costs: the workload required to generate a proof for a computation can be up to 1,000,000 times that of directly running the computation. This high cost is worthwhile when it needs to be distributed among thousands of verifiers, but it seems impractical in other scenarios.

This situation is about to change. By 2026, the overhead of zkVM (Zero-Knowledge Virtual Machine) provers will drop to about 10,000 times, with memory usage requiring only a few hundred megabytes—fast enough to run on mobile devices and cheap enough to apply in various scenarios. Why might "10,000 times" be a magical number? This is because the parallel throughput capability of high-end GPUs is about 10,000 times that of laptop CPUs. By the end of 2026, a single GPU will be able to generate computation proofs executed by a CPU in real-time.

This breakthrough in technology is expected to realize the visions outlined in some early research papers: verifiable cloud computing. If you are already running CPU workloads in the cloud—whether due to insufficient computational power to utilize GPUs, lack of relevant expertise, or limitations of legacy systems—you will be able to obtain cryptographic proofs of computational correctness at a reasonable cost. Moreover, these provers have been optimized for GPUs, requiring no additional adjustments to your code.

—Justin Thaler, a16z Crypto Researcher & Associate Professor of Computer Science at Georgetown University

AI Will Become a Research Assistant

As a mathematical economist, I found it difficult to get consumer-grade AI models to understand my workflow back in January; by November, I was able to give the models abstract instructions as if I were instructing a PhD student… and they sometimes even provided novel and correct answers. Beyond my personal experience, we are also beginning to see AI applied in broader research fields, especially in reasoning—models are now not only directly involved in the discovery process but can also autonomously solve the Putnam problem (one of the hardest university math exams in the world).

It remains unclear in which fields this research assistance will be most effective and how it will specifically function. However, I anticipate that AI research will foster and reward a brand new "versatile" research style: one that emphasizes the ability to speculate relationships between different ideas and can quickly extrapolate from more hypothetical answers. These answers may not be entirely accurate, but they can still point in the right direction (at least under certain topological structures). Ironically, this approach somewhat resembles leveraging the power of model "hallucinations": when models are "smart" enough, giving them an abstract space to explore freely may generate some meaningless content, but it could also inadvertently trigger some discovery, just as humans often exhibit greater creativity when working in nonlinear, ambiguous directions.

This reasoning approach requires a completely new AI workflow—not just "agent-to-agent," but also a structure of "agent-wrapping-agent." In this structure, models at different levels help researchers evaluate the methods of early models and gradually distill valuable content from them. I have been using this method to write papers, while others use it for patent searches, creating new art forms, and even (regrettably) seeking new types of attacks on smart contracts.

However, to efficiently operate this research system centered around reasoning agents, better interoperability between models is needed, as well as a method to identify and reasonably compensate each model's contributions—issues that cryptographic technology can help address.

—Scott Kominers, a16z Crypto Research Team Member & Professor at Harvard Business School

The "Invisible Tax" of Open Networks: Economic Imbalance and Solutions in the AI Era

With the rise of AI agents, open networks are facing an invisible tax that is fundamentally undermining their economic foundation. This disruption stems from the increasing mismatch between the internet's "Context Layer" and "Execution Layer": currently, AI agents extract data from ad-supported content websites (Context Layer) to provide convenience to users while systematically bypassing the revenue sources that support this content (such as advertising and subscriptions).

To prevent further erosion of open networks and protect the diverse content ecosystem that fuels AI, we need to deploy technological and economic solutions on a large scale. This may include next-generation sponsored content models, micro-attribution systems, or other novel funding models. However, existing AI authorization protocols are proving financially unsustainable—these protocols often only compensate content providers for a small fraction of the revenue lost due to AI diverting traffic.

The network needs a completely new techno-economic model that automates the flow of value. A key shift in the coming year will be moving from static authorization models to compensation mechanisms based on real-time usage. This means testing and scaling systems—potentially leveraging blockchain-supported micropayment technologies and advanced attribution standards—to automatically reward every entity that contributes information for AI agents to successfully complete tasks.

—Liz Harkavy, a16z Crypto Investment Team

The Rise of "Staked Media": Reshaping Trust with Blockchain

The cracks in the traditional media model regarding "objectivity" have been evident for some time. The internet has given everyone a voice, and increasingly, operators, practitioners, and builders express their views directly to the public. Their perspectives reflect their interests in the world, and surprisingly, audiences often respect them for these interests rather than despite them.

The real change is not the rise of social media, but the arrival of cryptographic tools that enable people to make publicly verifiable commitments. In an era where AI makes generating infinite content cheap and easy—whether expressing views under real or false identities, from any perspective—relying solely on what people (or bots) say is no longer sufficient. Tokenized assets, programmable escrow, prediction markets, and on-chain history provide a more robust foundation for trust: commentators can prove they "put their money where their mouth is" while expressing opinions; podcasters can lock tokens to indicate they won't engage in speculative "pump and dump"; analysts can tie predictions to publicly settled markets, creating auditable records.

This is what I call the prototype of "Staked Media": a form of media that not only embraces the idea that "risk brings investment" but also provides proof. In this model, credibility no longer comes from a facade of detachment or baseless claims, but from clear, transparent, and verifiable commitments. "Staked Media" will not replace other forms of media but will complement existing models. It offers a new signal: not just "trust me, I'm neutral," but "this is the risk I'm willing to take, and here's how you can verify if I'm telling the truth."

—Robert Hackett, a16z Crypto Editorial Team

"Secrets-as-a-Service": How Privacy Protection Becomes Core Infrastructure of the Internet

Behind every model, agent, and automated system lies a simple yet critical factor: data. However, most data pipelines today—the data flows that input or output models—are opaque, variable, and un-auditable. This may be inconsequential for some consumer applications, but for many industries and users (such as finance and healthcare), businesses need to ensure the privacy of sensitive data. For institutions currently attempting to tokenize real-world assets, this poses a significant barrier.

So, how can we achieve secure, compliant, autonomous, and globally interoperable innovation while protecting privacy? While there are many approaches, I am particularly focused on data access control: who controls sensitive data? How does data flow? Who (or what) can access it?

In the absence of data access control, anyone wishing to protect data confidentiality currently has to rely on centralized services or customized solutions—this is not only time-consuming and costly but also hinders traditional financial institutions and other industries from fully leveraging the capabilities and advantages of on-chain data management. As agent systems begin to autonomously browse, trade, and make decisions, users and institutions across industries need cryptographic guarantees rather than "best-effort" trust.

Therefore, I believe we need "Secrets-as-a-Service": a new technology that can provide programmable native data access rules, client-side encryption, and decentralized key management, clearly specifying who can decrypt data under what conditions and for how long… all enforced through on-chain mechanisms. Combined with verifiable data systems, "secrets" can become part of the internet's basic public infrastructure, rather than an afterthought privacy feature at the application layer. This will make privacy a core infrastructure of the internet.

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

Wealth Management for Everyone

Personalized wealth management services have traditionally been available only to high-net-worth clients, as providing customized advice across different asset classes and personalizing portfolio allocations is both expensive and complex. However, as more asset classes become tokenized, the infrastructure of cryptographic technology enables AI-recommended and assisted personalized investment strategies to be executed and adjusted instantly at a very low cost.

This is not just an upgraded version of "robo-advisors": everyone can enjoy active portfolio management, not just passive management. By 2025, traditional finance (TradFi) will have allocated 2-5% of assets in portfolios to the crypto space (through direct investments via banks or exchange-traded products, ETPs), but this is just the beginning; by 2026, we will see more platforms focused on "wealth accumulation" rather than just "wealth preservation"—fintech companies (like Revolut and Robinhood) and centralized exchanges (like Coinbase) will leverage their technological advantages to capture a larger market share.

Meanwhile, decentralized finance (DeFi) tools like Morpho Vaults can automatically allocate assets to lending markets with the best risk-adjusted returns, providing core yield distribution for portfolios. Additionally, holding excess liquidity in stablecoins rather than fiat currency and investing in tokenized money market funds instead of traditional money market funds can further expand yield possibilities.

Finally, ordinary investors now have easier access to more illiquid private market assets, such as private credit, pre-IPO companies, and private equity. Tokenization technology unlocks these markets while still meeting compliance and reporting requirements. As the various components of balanced portfolios gradually become tokenized (from bonds to stocks to the risk spectrum of private and alternative assets), these assets can be automatically rebalanced without cumbersome operations like bank transfers.

—Maggie Hsu, a16z Crypto Market Expansion Team

The Internet Becomes Banking: The Future of Value Flow

With the widespread adoption of AI agents and more transactions being completed automatically in the background rather than relying on user clicks, the flow of funds—i.e., the way value moves—needs to change accordingly. In a world where systems operate based on intent rather than step-by-step instructions, the movement of funds may occur as AI agents identify needs, fulfill obligations, or trigger outcomes. At this point, value needs to flow as quickly and freely as today's information, and blockchain, smart contracts, and new protocols are key to achieving this goal.

Today, smart contracts can settle dollar payments globally in seconds. By 2026, emerging foundational tools (like x402) will make this settlement programmable and responsive. Agents can pay each other instantly and without permission for data, GPU time, or API calls—without invoicing, reconciliation, or batch processing; developers can release software updates with built-in payment rules, limits, and audit trails—without fiat integration, merchant onboarding, or bank involvement; prediction markets can automatically settle in real-time as events progress—without custodians or exchanges, odds update in real-time, agents trade, and payments are completed globally in seconds.

When value can flow in this way, the "payment process" will no longer be a separate operational layer but will become part of network behavior. Banks will become part of the internet's infrastructure, and assets will evolve into infrastructure. If funds can be routed like data packets on the internet, then the internet will not only support the financial system; it will itself become the financial system.

—Christian Crowley and Pyrs Carvolth, a16z Crypto Market Expansion Team

When Legal Frameworks Match Technological Frameworks: Unlocking the Full Potential of Blockchain

Over the past decade, one of the biggest obstacles to building blockchain networks in the U.S. has been legal uncertainty. Securities laws have been extended and selectively enforced, forcing entrepreneurs into a regulatory framework designed for companies rather than networks. For years, mitigating legal risks has replaced product strategy; the role of engineers has been supplanted by lawyers.

This dynamic has led to many strange distortions: entrepreneurs have been told to avoid transparency; token distribution has become legally arbitrary; governance has evolved into superficial "theater"; organizational structures have been optimized for legal protection; token designs have been forced to avoid economic value, even lacking business models. Worse still, those crypto projects that evade rules often develop faster than honest builders.

However, the U.S. government is currently closer than ever to regulating the crypto market structure, and this legislation is expected to eliminate all these asymmetries next year. If passed, this legislation will incentivize transparency, establish clear standards, and replace the "enforcement roulette" with clearer, structured pathways for financing, token issuance, and decentralization. Driven by GENIUS, the adoption of stablecoins has already seen explosive growth; legislation around crypto market structure will be an even more significant transformation, but this time it is designed for networks.

In other words, this regulation will enable blockchain networks to operate truly as networks—open, autonomous, composable, trustlessly neutral, and decentralized.

—Miles Jennings, a16z Crypto Policy Team and General Counsel

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