Author: a16z New Media; Translator: TechFlow TechFlow
Over the past two days, we've shared insights on infrastructure, growth, life sciences and health, Speedrun, applications, and what the U.S. Vitality team believes will be the challenges and opportunities for builders in 2026.
Today, we're sharing 17 insights into the future of crypto from several of a16z's partners (and invited contributors). These topics range from smart agents and artificial intelligence (AI), stablecoins, tokenization and finance, privacy and security, to prediction markets, SNARKs (zero-knowledge proofs), and other applications… and how things will be built in the future. (To stay up-to-date with trend updates, builder guides, industry reports, and other crypto resources, be sure to subscribe to the a16z Crypto Newsletter.)
Tomorrow, we'll be closing the week with a special announcement and an exclusive invitation from a16z—don't miss it!
Here are our key points for today:
Privacy will become the most important moat in the crypto space.
Privacy is one of the key features driving global finance onto the blockchain, and it is also a component that almost all current blockchains lack. For most blockchains, privacy is merely a secondary or even ignored feature.
However, privacy itself is now attractive enough to set a blockchain apart from its competitors. More importantly, privacy can create a "chain reaction," or even a "privacy network effect." This effect is especially important in a world where simply competing on performance is no longer sufficient.
Thanks to cross-chain bridge protocols, migrating from one chain to another becomes extremely simple, as long as everything is public. However, this convenience disappears once privacy is introduced: migrating tokens is easy, but migrating secrets is difficult. There are always risks involved in moving from a privacy chain to a public chain, or migrating between two privacy chains. For example, third parties observing on-chain transactions, mempools, or network traffic might identify you. Crossing the boundaries between privacy and public chains, or even between two privacy chains, can leak various metadata, such as the correlation between transaction time and size, making tracking much easier.
Compared to numerous homogeneous new blockchains, whose fees may drop to zero due to competition (the nature of the block space has become similar across chains), blockchains with privacy features can generate 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 cultivate user loyalty.
On public blockchains, users can easily transact with users on other chains—it doesn't matter which chain they join. However, on privacy blockchains, which chain a user chooses becomes extremely important, because once they join a chain, they are less likely to migrate to avoid exposing themselves to risks. This phenomenon creates a "winner-takes-all" dynamic. And since privacy is a prerequisite for most real-world scenarios, a few privacy chains may dominate the majority of the crypto market.
—Ali Yahya, Partner in the Crypto Space at a16z
Predicting the Market: A Larger, Wider, and Smarter Future
Prediction markets have gone from niche to mainstream, and in the coming year, they will become larger, more widespread, and more intelligent as they converge with cryptography and artificial intelligence (AI), while also bringing new and significant challenges to their builders.
First, more contracts will be listed. This means we'll not only have access to real-time probabilities of major elections or geopolitical events, but also insights into a wide range of sub-sectors 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 questions, such as how to balance the value of this information and how to better design these markets to make them more transparent and auditable—questions that can be addressed through cryptography (<SC will link to our related article>).
To cope with a larger number of contracts, we need new ways to reach consensus on the truth to resolve contract issues. The centralized platform's approach (did an event really happen? How do we confirm it?) is crucial, but its limitations have been exposed in controversial cases like the Zelensky lawsuit market and the Venezuelan election market. To address these marginal cases and help expand prediction markets into more useful applications, novel decentralized governance and oracles based on Large Language Models (LLMs) can help determine the truth behind controversial outcomes.
AI can even surpass LLM in its application to oracles. For example, AI agents trading on these platforms can search for global signals, providing an advantage for short-term trading, thereby revealing new ideas about the world and predicting future events. (Projects like Prophet Arena have already demonstrated the potential of this field.) Beyond providing insights as sophisticated political analysts, these agents may also reveal fundamental predictors of complex social events when their strategies are studied.
Will prediction markets replace polls? No; they will make polls better (and poll information can also be fed into prediction markets). As a political scientist, I'm most interested in how prediction markets can work in tandem with a rich and vibrant polling ecosystem—but this requires relying on new technologies, such as AI, which can improve the polling experience; and encryption, which can provide new ways to verify that poll/survey participants are human and not bots, among other features.
—Andy Hall, Crypto Research Advisor at a16z (and Professor of Political Economy at Stanford University)
Viewing the tokenization of real-world assets and stablecoins from a more "crypto-native" perspective
We've seen banks, fintech companies, and asset management firms showing strong interest in putting U.S. stocks, commodities, indices, and other traditional assets on the blockchain. However, as more and more traditional assets go on-chain, this tokenization often becomes "physical"—based on current understanding of real-world assets, failing to fully utilize the native features of crypto.
However, synthetic representations like perpetual contracts not only offer deeper liquidity but are also generally easier to implement. Perpetual contracts also feature easily understood leverage mechanisms, making them, in my opinion, the most suitable derivatives for the crypto market. I also believe that emerging market equities are one of the most worthwhile asset classes to perpify. (For example, the liquidity of some stocks' zero-day expiration options (0DTE) markets is even higher than that of the spot market, providing a very interesting opportunity to experiment with perpetuation.)
This boils down to a question of "persistence vs. tokenization"; but in any case, we should see more crypto-native reality assets (RWA) tokenization in the coming year.
Similarly, in 2026, after stablecoins have entered the mainstream in 2025, we will see more of a trend of "issuance, not just tokenization", and the outstanding issuance of stablecoins will continue to grow.
However, stablecoins without a strong credit infrastructure are more like “narrow banks,” holding only specific liquid assets deemed particularly safe. While narrow banks are an effective product, I don’t believe they will become the backbone of the long-term on-chain economy.
We've seen many new asset managers, curators, and protocols facilitating on-chain asset-backed lending based on off-chain collateral. These loans are typically initiated off-chain and then tokenized. However, I believe the benefits of tokenization in this scenario are limited, perhaps only facilitating asset distribution 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 reduces loan servicing and back-end structuring costs and improves accessibility. The challenges lie in compliance and standardization, but developers are already working to address these issues.
—Guy Wuollet, General Partner, a16z Crypto Insights
A transit point for crypto transactions: Transactions are not the final destination
Today, aside from stablecoins and some core infrastructure, almost every well-performing crypto company has shifted or is shifting towards trading. But what will the future of the industry look like if "every crypto company becomes a trading platform"? When too many players are doing the same thing, it not only diminishes each other's market visibility but also results in only a few large companies emerging as winners. This also means that companies that shift to trading too early miss the opportunity to build a more defensive and sustainable business.
While I sympathize with entrepreneurs struggling to keep their companies financially sound, chasing short-term product-market fit also comes at a price. This is particularly pronounced in the crypto space, where the unique dynamics of tokens and speculation can lead entrepreneurs to prioritize instant gratification in their search for product-market fit—a kind of "marshmallow test." Transactions themselves aren't inherently wrong; they're an important function of the market. However, they aren't necessarily the ultimate destination for business development. Entrepreneurs who focus on the "product" aspect of product-market fit are likely to ultimately emerge as bigger winners.
—Arianna Simpson, Partner in the Crypto Space at a16z
From Know Your Customer (KYC) to Know Your Agent (KYA)
The bottleneck in the agent economy is shifting from intelligence to identity.
In the financial services sector, the number of "non-human identities" now exceeds that of human employees by 96 to 1—yet these identities remain like ghosts, unable to enter the banking system. The critical infrastructure missing here is KYA: Know Your Agent.
Just as humans need credit scores to obtain loans, agents need cryptographically signed credentials to conduct transactions—credentials that link the agent to their principal, obligations, and responsibilities. Until this mechanism is in place, merchants will still block agents from accessing the system through their firewalls. The financial industry has spent decades building KYC infrastructure, and now it has only months to address the KYA issue.
—Sean Neville, co-founder of Circle and USDC architect; CEO of Catena Labs
The Future of Stablecoins: Better and Smarter Entry and Exit Mechanisms
Last year, stablecoin trading volume was estimated at $46 trillion, and continues to break records. To better understand this scale, this is more than 20 times the trading volume of PayPal; nearly three times that of Visa, one of the world's largest payment networks; and rapidly approaching the trading volume of the Automated Clearing House (ACH) in the United States—the electronic network used in the US to process financial transactions such as direct deposits.
Today, you can complete a stablecoin transaction in less than a second and at a cost of less than a cent. However, the unresolved issue is how to connect these digital dollars with the financial system people use every day—in other words, how to build onramps and offramps mechanisms for stablecoins.
A new generation of startups is filling this gap, connecting stablecoins with more familiar payment systems and local currencies. Some companies use cryptographic proofs to allow people to privately exchange their local balances for digital dollars. Others are integrating with local networks, leveraging features like QR codes and real-time payment tracks to enable interbank payments… Still others are building truly interoperable global wallet layers and card-issuing platforms, allowing users to spend stablecoins at everyday merchants. These approaches collectively broaden participation in the digital dollar economy and could accelerate the adoption of stablecoins directly as a mainstream payment method.
As these entry and exit mechanisms mature, the digital dollar will be directly integrated into 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 bank accounts; and applications can achieve instant settlements with users anytime, anywhere. Stablecoins will gradually transform from a niche financial tool into a fundamental settlement layer of the internet.
—Jeremy Zhang, a16z Encryption Engineering Team
Stablecoins: Unlocking bank ledger upgrade cycles and opening up new payment scenarios
Today, many banks still use software systems that are difficult for modern developers to recognize: In the 1960s and 70s, banks were early adopters of large-scale software systems; by the 1980s and 90s, second-generation core banking software (such as Temenos' GLOBUS and InfoSys' Finacle) began to emerge. However, this software has become outdated, and upgrades have been too slow. Therefore, the banking industry—especially the critical core ledger databases responsible for tracking deposits, collateral, and other obligations—still predominantly runs on mainframe computers, uses the COBOL programming language, and relies on batch file interfaces rather than modern APIs.
The vast majority of global assets remain tied to these decades-old core ledgers. While these systems have been proven in practice, trusted by regulators, and deeply integrated into complex banking scenarios, they also hinder innovation. For example, adding critical functionalities such as real-time payments (RTP) to these systems could take months or even years and involve navigating layers of technical debt and regulatory complexities.
This is precisely where stablecoins shine. Over the past few years, stablecoins have not only found a product-market fit and entered the mainstream, but this year, traditional financial institutions (TradFi) have embraced them to a whole new level. 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 completely rewriting their legacy systems—systems that, while aging, have operated reliably for decades. Therefore, stablecoins offer institutions a completely new avenue for innovation.
—Sam Broner
Decentralization is the future of messaging, more important than quantum encryption.
As the world gradually moves into the era of quantum computing, many encryption-based messaging applications (such as Apple, Signal, and WhatsApp) are leading the trend 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 are easily targeted by governments for shutdowns, backdoor implants, or forced access to private data.
What's the point of quantum encryption if a country can shut down your server, if a company possesses the keys to a private server, or even if a company simply owns one private server? A private server requires users to "trust me," but without a private server, it means "you don't need to trust me." Communication doesn't need an intermediary company to operate.
Messaging requires open protocols so that users don't need to trust anyone. The way to achieve this is through decentralized networks: no private servers, no single application, all code is open source, and top-notch encryption technologies are used—including quantum-resistant encryption.
With open networks, no individual, company, non-profit organization, or country can deprive us of our ability to communicate. Even if a country or company shuts down an application, 500 new versions will appear the next day. Even if a node is shut down, the economic incentives provided by technologies such as blockchain will prompt a new node to immediately take its place.
Everything will change when people control their messages with keys, just like they control their own money. Applications may come and go, but users will always control their messages and identities. Even if an application fails, the end user will still have control over their messages.
This isn't just about quantum resistance and encryption; it's about ownership and decentralization. Without both, all we're building is an encryption system that's unbreakable but can still be shut down.
—Shane Mac, Co-founder and CEO of XMTP Labs
From "Code is Law" to "Regulations are Law"—A New Evolution in DeFi Security
Recent DeFi hacks have targeted battle-tested protocols—protocols operated by strong teams, rigorously audited, and years in the making. These incidents reveal a disturbing reality: current security standards still rely heavily on rules of thumb and case-by-case approaches.
To further mature DeFi security, we need to shift from patching vulnerability patterns to ensuring properties at the design level, and from a "best-effort" approach to a "principle-based approach":
In the static/pre-deployment phase (testing, auditing, formal verification, etc.), this means systematically verifying global invariants, rather than just manually selected local invariants. Currently, multiple teams are building AI-assisted proof tools to help write specifications, propose invariants, and offload 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"—a last line of defense. These guardrails are directly encoded into runtime assertions, ensuring that every transaction must satisfy these assertions.
Therefore, instead of assuming that every vulnerability is caught in advance, we now embed key security attributes directly into the code and automatically roll back any transactions that violate these attributes.
This is not just theory. In practice, almost every attack that has occurred triggers these checks during execution, potentially stopping the hacking. Therefore, the idea of "code is law" is evolving into "standards are law": even novel attacks must meet security properties that maintain system integrity, ultimately leaving only minor or extremely difficult-to-execute attacks.
—Daejun Park, a16z Encryption Engineering Team
Encryption Technology Beyond Blockchain: Ushering in a New Era of Verification Computation
For years, SNARKs (zero-knowledge concise non-interactive proofs)—a cryptographic proof technique that verifies computation without re-executing it—have been almost exclusively used in the blockchain field. This is because their computational cost is prohibitively high: the amount of work required to generate a computational proof can be 1,000,000 times that of directly running the computation. This exorbitant cost is worthwhile when it needs to be amortized across thousands of validators, but it proves impractical in other scenarios.
This situation is about to change. By 2026, the overhead of zkVM (zero-knowledge virtual machine) provers will drop to approximately 10,000 times, requiring only a few hundred megabytes of memory—fast enough to run on mobile phones and cheap enough for a wide range of applications. Why is "10,000 times" such a magical number? This is because the parallel throughput of high-end GPUs is approximately 10,000 times that of laptop CPUs. By the end of 2026, a GPU will be able to generate computational proofs that would otherwise be executed by a CPU in real time.
This technological breakthrough promises to realize some of the visions expressed in earlier research papers: verifiable cloud computing. If you are already running CPU workloads in the cloud—whether due to insufficient computational resources 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 are already optimized for GPUs, requiring no additional tweaks to your code.
—Justin Thaler, a16z Cryptography Researcher & Associate Professor of Computer Science at Georgetown University
AI will become a research assistant.
As a mathematical economist, I struggled to get consumer-grade AI models to understand my workflow in January; by November, I could give them abstract instructions as if they were PhD students… and they sometimes even provided novel and correct solutions. Beyond my personal experience, we're also seeing AI applied in broader research areas, particularly in reasoning—models are now not only directly involved in the discovery process but can also autonomously solve the Putnam problem (possibly one of the world's most difficult college-level math exams).
It remains unclear in which areas this research-aiding approach will be most effective, and how exactly it will work. However, I anticipate that AI research will foster and reward a new, “versatile” research style: one that emphasizes the ability to infer relationships between different ideas and to quickly extrapolate from more hypothetical answers. These answers may not be entirely accurate, but they can still point in the right direction (at least within a certain topological framework). Ironically, this approach somewhat leverages the power of model “illusion”: when models are “smart” enough, giving them an abstract space to explore freely may generate some meaningless content, but it may also accidentally trigger some discoveries, much like how humans are often more creative when working in non-linear, ambiguous directions.
This reasoning approach requires a completely new AI workflow—not just "agent-to-agent," but a "agent-wrapping-agent" structure. In this structure, different layers of models help researchers evaluate the methods of earlier models and gradually extract valuable insights. I'm already using this approach to write papers, while others are using it for patent searches, creating new art forms, and even (unfortunately) searching for new ways to attack smart contracts.
However, to operate this research system around inference agents efficiently, better interoperability between models is needed, as well as a method to identify and reasonably compensate for the contribution of each model—and these are precisely the problems that encryption technology can help solve.
—Scott Kominers, member of the a16z cryptography research team & professor at Harvard Business School
The "Hidden Tax" of Open Networks: Economic Imbalances and Solutions in the AI Era
With the rise of AI agents, the open web is facing a hidden tax that is fundamentally undermining its economic foundation. This damage stems from the growing mismatch between the internet's "context layer" and "execution layer": currently, AI agents extract data from ad-supported content websites (the context layer) to provide convenience to users, while systematically bypassing the revenue streams that support this content (such as advertising and subscriptions).
To prevent further erosion by the open web and to protect the diverse content ecosystem that fuels AI, we need to deploy technological and economic solutions on a large scale. This could include next-generation sponsored content models, micro-attribution systems, or other novel funding models. However, existing AI licensing agreements are proving financially unsustainable—these agreements often only compensate content providers for a small fraction of the revenue lost due to AI diverting traffic.
The internet needs a completely new techno-economic model to automate the flow of value. A key shift in the coming year lies in moving from a static authorization model to a compensation mechanism based on real-time usage. This means testing and scaling systems—potentially leveraging blockchain-enabled nanopayment technologies and advanced attribution criteria—to automatically reward every entity that contributes information to the successful completion of tasks by AI agents.
—Liz Harkavy, a16z Crypto Investment Team
The Rise of "Staking Media": Reshaping Trust with Blockchain
The cracks regarding "objectivity" in traditional media models have been apparent for some time. The internet has given everyone the right to speak, and today, more and more operators, practitioners, and builders are expressing their views directly to the public. Their perspectives reflect their interests in the world, and surprisingly, audiences often respect them because of these interests, rather than because of them.
The real change isn't the rise of social media, but the arrival of crypto tools that enable people to make publicly verifiable commitments. In an era where AI makes generating limitless content cheap and easy—whether from a real or fake identity, or from any perspective—relying solely on what people (or bots) say is no longer sufficient. Tokenized assets, programmable lock-up periods, prediction markets, and on-chain history provide a stronger foundation for trust: commentators can demonstrate they "walk the talk" when they express their opinions; podcasters can lock up tokens to show they won't speculatively "pump and dump"; analysts can link predictions to publicly settled markets, creating auditable records.
This is precisely the prototype of what I call “Staked Media”: a media form that not only embraces the “risk-taking” philosophy but also provides proof. In this model, credibility no longer comes from feigned detachment or unfounded claims, but from clear, transparent, and verifiable commitments. “Staked Media” will not replace other forms of media but rather complement existing models. It provides a new signal: not just “believe me, I am neutral,” but “this is the risk I am willing to take, and how you can verify whether I am telling the truth.”
—Robert Hackett, a16z Encrypted Editing Team
"Security as a Service": How Privacy Protection is Becoming a Core Infrastructure of the Internet
Behind every model, agent, and automation system lies a simple yet crucial element: data. However, most data pipelines today—the flow of data into or out of models—are opaque, variable, and unauditable. This may be harmless for some consumer applications, but for many industries and users, such as finance and healthcare, ensuring the privacy of sensitive data is paramount. And for institutions currently attempting to tokenize real-world assets, this presents an even greater obstacle.
So, how can we achieve secure, compliant, autonomous, and globally interconnected innovation while protecting privacy? While there are many approaches, I'm more concerned with data access control: Who controls sensitive data? How does data flow? Who (or what) can access it?
In the absence of data access controls, anyone wishing to protect data confidentiality currently relies on centralized services or customized solutions—a time-consuming and costly endeavor that hinders traditional financial institutions and other industries from fully leveraging the capabilities and advantages of on-chain data management. As proxy systems begin to autonomously browse, transact, and make decisions, users and institutions across industries require cryptographic guarantees, not merely "best-effort" trust.
Therefore, I believe we need "Secrets-as-a-Service": a new technology that provides programmable native data access rules, client-side encryption, and decentralized key management, explicitly defining who can decrypt data under what conditions, and the effective duration of decryption—all enforced through on-chain mechanisms. Combined with verifiable data systems, "secrets" can become part of the internet's fundamental public infrastructure, rather than a privacy feature added after the fact at the application level. This would make privacy a core part of the internet's infrastructure.
—Adeniyi Abiodun, Chief Product Officer and Co-founder of Mysten Labs
Wealth management for everyone
Personalized wealth management services have traditionally been limited to high-net-worth clients because providing customized advice and portfolio allocation across different asset classes is both expensive and complex. However, with more asset classes becoming tokenized, the infrastructure of crypto technology enables AI-recommended and assisted personalized investment strategies to be executed and adjusted instantly at extremely low cost.
This is more than just an upgraded version of "robo-advisors": everyone can enjoy active portfolio management, not just passive management. In 2025, traditional finance (TradFi) had already shifted 2-5% of its portfolio allocation to the crypto space (through direct bank investments or exchange-traded products, ETPs), but this is just the beginning; by 2026, we will see the rise of more platforms focused on "wealth accumulation" rather than just "wealth preservation"—fintech companies (such as Revolut and Robinhood) and centralized exchanges (such as Coinbase) will leverage their technological advantages to gain 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 return distribution for portfolios. Furthermore, holding remaining liquidity in stablecoins instead of fiat currency and investing in tokenized money market funds instead of traditional money market funds can further expand return potential.
Finally, ordinary investors now have easier access to a wider range of 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 a balanced portfolio are progressively tokenized (from bonds to equities, and across the risk spectrum of private and alternative assets), these assets can be automatically rebalanced without the need for cumbersome procedures like bank transfers.
—Maggie Hsu, a16z Crypto Market Development Team
The Internet as a Bank: The Future of Value Flow
With the widespread adoption of AI agents and the increasing number of transactions completed automatically in the background rather than relying on user clicks, the way money—that is, value—flows needs to change. 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 results. In this context, value needs to flow as quickly and freely as information does today, and blockchain, smart contracts, and new protocols are key to achieving this goal.
Today, smart contracts can settle USD payments globally in seconds. By 2026, emerging infrastructure tools (such as x402) will make this settlement programmable and reactive. Agents can instantly and permissionlessly pay each other 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 logs—without fiat currency integration, merchant onboarding, or bank involvement; prediction markets can automatically settle in real time as events unfold—without custodians or exchanges, odds updated in real time, agent trading, and payments completed globally in seconds.
When value can flow in this way, the "payment process" will no longer be a separate operational layer, but part of network behavior. Banks will become part of the internet infrastructure, and assets will evolve into infrastructure. If funds can be routed through the internet like data packets, then the internet will not only support the financial system, but will become the financial system itself.
—Christian Crowley and Pyrs Carvolth, a16z Crypto Markets Expansion Team
When legal architecture matches technological architecture: Unleashing the full potential of blockchain
One of the biggest obstacles to building blockchain networks in the US over the past decade has been legal uncertainty. Expanded and selectively enforced securities laws have forced entrepreneurs into a regulatory framework designed for companies, not networks. For years, mitigating legal risks has replaced product strategy; the role of the engineer has been superseded by lawyers.
This dynamic has led to a number of strange distortions: entrepreneurs are told to avoid transparency; token distribution becomes legally arbitrary; governance degenerates into a superficial "drama"; organizational structures are optimized as legal umbrellas; and token designs are forced to avoid economic value, or even lack a business model. Worse still, crypto projects that circumvent the rules often grow faster than those that build integrity.
However, the U.S. government is now closer than ever to regulating the crypto market structure, with legislation expected to eliminate all these asymmetries next year. If passed, this legislation will incentivize transparency, establish clear standards, and replace the “enforcement roulette” with a clearer, more structured path, providing standardized guidance for financing, token issuance, and decentralization. While stablecoin adoption has exploded under GENIUS, legislation surrounding the crypto market structure will be an even more significant transformation, this time for the network.
In other words, this regulation will enable blockchain networks to truly operate as networks—open, autonomous, composable, trustworthy, neutral, and decentralized.
—Miles Jennings, Crypto Policy Team and General Counsel at a16z
