Here are 17 insights from a16z's cryptocurrency partners (and some invited contributors) on future trends—covering a wide range of topics from smart agents and artificial intelligence, stablecoins, tokenization and finance, privacy and security, prediction markets, SNARKs and other applications, to how we will build them.
Original text: 17 things we're excited about for crypto in 2026 (a16zcrypto)
Author: a16zcrypto
Compiled by: Will Awang , Investment and Financing Lawyer specializing in Web3 & Digital Assets; Independent Researcher specializing in Tokenization, RWA, Payments, and DeSci
This week, a16z released its annual "Big Ideas" from partners across Applications, US Dynamics, Bio, Crypto, Growth, Infrastructure, and Accelerated Teams. Below are 17 insights from a16z's cryptocurrency partners (as well as some invited contributors) on future trends—covering a wide range of topics from smart agents and AI, stablecoins, tokenization and finance, privacy and security, prediction markets, SNARKs and other applications, to how we'll build our ecosystem.
We compiled it and found that it connected some threads, which were very consistent with the direction we are currently working on, which is very gratifying:
- The core of the crypto space is the blockchain infrastructure, built on top of the internet, which enables the high-speed flow of information and value.
- Stablecoins (tokenization of fiat currency) have been proven to either improve traditional business models or create entirely new ones (on-chain digital banks).
- The tokenization of other real-world assets like RWA remains to be verified, but the logic of on-chain trading of on-chain assets such as RWA perpetual contracts and private equity tokenization may be the best fit for the product market.
- AI agents and artificial intelligence are moving to the next stage, and blockchain and stablecoins will help them form network effects.
- Privacy is currently a nice thing for both on-chain finance and AI business, but as the market deepens, the need for privacy will become crucial.
- The crypto market in 2025 has shifted from idealism to pragmatism, with prediction markets clearly seen as the most practical solution. However, as the external regulatory environment becomes more moderate and clearer, founders who focus on the "product" aspect of product-market fit may ultimately emerge as the biggest winners. Trading itself is not wrong—it's an important function of the market—but it's not the ultimate goal.
a16z: 17 things we're excited about for crypto in 2026
https://a16zcrypto.com/posts/article/big-ideas-things-excited-about-crypto-2026
I. On Stablecoins, RWA Tokenization, Payments, and Finance
1.1 A more complete and intelligent stablecoin deposit and withdrawal channel
Last year, the total transaction volume of stablecoins was estimated to reach $46 trillion, and it continues to break historical records. This is more than 20 times the transaction volume of PayPal; nearly 3 times the transaction volume of Visa (one of the world's largest payment networks); and is rapidly approaching the transaction volume of ACH (the electronic network used in the United States for financial transactions such as direct deposits).
Today, you can send stablecoins in less than a second for less than a cent.
However, the unresolved issue is how to connect these digital currencies with the financial system people use every day—in other words, how to provide access channels for stablecoins.
A new generation of startups is filling this gap, connecting stablecoins with more familiar payment systems and local currencies. Some companies are using encryption to allow users to privately exchange their local balances for digital dollars; others are integrating with local networks, leveraging QR codes, real-time payment channels, and other features to enable interbank payments; still others are building truly interoperable global wallet layers and card issuance platforms, allowing users to use stablecoins for everyday merchant purchases. These approaches collectively expand the participation of the digital dollar in the everyday economy and may accelerate the adoption of stablecoins as a mainstream payment method.
As these fund deposit and withdrawal channels mature, the digital dollar will be able to directly integrate with local payment systems and merchant tools, leading to new transaction models. Workers can receive wages across borders in real time. Merchants can accept global dollars without bank accounts. Applications can settle accounts with users instantly anytime, anywhere. Stablecoins will transform from a niche financial tool into a fundamental settlement layer for the internet.
—Jeremy Zhang, a16z Encryption Engineering Team
Recommended reading: From Blockchain to Everyday Life: An Overview of Global Stablecoin Consumption Landscape in 2025
1.2 Thinking about RWA tokenization in a crypto-native way
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-chain. However, as more traditional assets go on-chain, their tokenization tends to be skeuomorphic—still based on existing concepts of real-world assets, rather than fully leveraging the native characteristics of cryptography.
However, synthetic products like perpetual contracts offer deeper liquidity and are generally easier to implement. Perpetual futures also provide easily understandable leverage, making them, in my opinion, the most product-market fit among native crypto derivatives. I also believe emerging market equities are one of the most worthwhile asset classes for perpetual trading. (The zero-day options market for certain stocks is often more liquid than the spot market, which would be an interesting perpetual experiment.)
It all boils down to the issue of "sustainability and tokenization"; however, we should see more crypto-native RWA tokenizations next year. Similarly, in the stablecoin market, we will see more crypto-native stablecoin products in 2026.
However, stablecoins lacking strong credit infrastructure backing resemble banks in the narrow sense, holding liquid assets deemed exceptionally safe. While narrow banking is an effective product in itself, I don't believe it will be a long-term pillar of the on-chain economy.
We're seeing many new asset management protocols facilitating on-chain lending based on off-chain collateral . These loans typically originate off-chain. I don't think tokenization offers much benefit beyond potentially distributing funds to users already on-chain. Therefore, debt assets should originate on-chain , not off-chain. On-chain origination reduces loan servicing costs, back-end infrastructure costs, and improves accessibility. The real challenges here are compliance and standardization, but developers are already working on addressing these issues.
—Guy Wuollet, Partner at a16z crypto
Recommended reading:
DigiFT 2025 RWA Report: From Tokenization to Innovative Adoption
Interview with DigiFT CEO Henry: What kind of on-chain finance future are we looking forward to?
1.3 Stablecoins have initiated a cycle of upgrading bank ledgers and spurred new payment scenarios.
Today's banks generally run software that is difficult for modern developers to recognize: In the 1960s and 70s, banks pioneered large-scale software systems. Second-generation core banking software emerged in the 1980s and 90s (e.g., Temenos' GLOBUS and Infosys' Finacle). But all of this software is outdated and upgrades are too slow. Therefore, the banking industry—especially the critical core ledger (the key database used to track deposits, collateral, and other liabilities)—still often runs on mainframe computers, is programmed in the COBOL language, and interacts via batch file interfaces rather than APIs.
The vast majority of global assets are stored on core ledgers that have been around for decades. While these systems are time-tested, trusted by regulators, and deeply integrated into complex banking scenarios, they also hinder innovation. Adding critical features such as Real-Time Payments (RTPs) can take months or even years and requires overcoming layers of technological debt and regulatory complexities.
This is where stablecoins come in. In the past few years, stablecoins have not only found a fit between products and the market and entered the mainstream market, but this year, traditional financial institutions have also embraced them with a completely new attitude .
Stablecoins, tokenized deposits, tokenized treasuries, and on-chain bonds enable banks, fintech companies, and financial institutions to develop new products and serve new customers. More importantly, they do not force these institutions to rewrite their legacy systems—systems that, while aging, have been reliably functioning for decades. Therefore, stablecoins offer a new avenue for institutional innovation.
—Sam Broner
Recommended reading:
McKinsey 2025 Global Payments Report: Reflections on Development Amidst Multiple Payment Tracks ;
Stablecoin payments and global fund transfer models
1.4 When the Internet Becomes a Bank
With the influx of AI agents, more and more business activities are being conducted automatically in the background instead of through user clicks, which necessitates a change in the way money and value flow.
In a world where systems no longer execute steps or instructions, but rather operate according to intent—for example, where funds are automatically transferred once an AI agent identifies a need, fulfills an obligation, or triggers a result—the flow of value must be as rapid and free as information is today. Blockchain, smart contracts, and new protocols have emerged in this context.
Smart contracts can already settle global USD payments in seconds. But by 2026, emerging primitives like x402 will make settlement processes even more programmable and responsive: agents can instantly, without permission, pay data, GPU time, or API call fees—no invoicing, reconciliation, or batch processing required. Software updates released by developers will include built-in payment rules, limits, and audit trails—no fiat currency integration, merchant onboarding, or bank involvement needed. Prediction markets will automatically settle in real time as events occur—odds updates, agent trading, and global payments cleared in seconds…without custodians or exchanges.
Once value can flow in this way, the "payment flow" ceases to be a separate operational layer and becomes a network behavior: banks become part of the internet infrastructure, and assets become infrastructure. If money becomes data packets that the internet can route, then the internet is not merely a support for the financial system... it becomes the financial system itself.
—Christian Crowley and Pyrs Carvolth, a16z crypto marketing team
Recommended reading: Crypto Mining in Latin America: Taking the Lead in Web3 On-Chain Digital Banking
1.5 Wealth Management for All
Traditionally, banks have offered personalized wealth management services only to high-net-worth clients: providing tailored advice and personalized portfolios across asset classes is both expensive and complex. But as more and more asset classes are tokenized, cryptocurrency platforms are enabling strategies—combining AI advice and driver assistance features—to be executed and rebalanced instantly at extremely low cost.
This is more than just robo-advisors; everyone can have active portfolio management, not just passive management. In 2025, traditional finance (TradFi) increased the proportion of cryptocurrencies in their portfolios (whether through direct allocation or through exchange-traded products), but this is just the beginning; by 2026, we will see the emergence of platforms designed for “wealth building” 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 share of this market.
Meanwhile, DeFi tools like Morpho Vaults automatically allocate assets to lending markets with the highest risk-adjusted yields, providing core yield allocation for portfolios. Holding remaining liquidity in stablecoins instead of fiat currency, and holding funds in tokenized money market funds instead of traditional money market funds, can further expand yield sources.
Finally, retail investors can now more easily access less liquid private market assets, such as private credit, pre-IPO companies, and private equity, as tokenization helps unlock liquidity in these markets while meeting compliance and reporting requirements. As the various components of a balanced portfolio (ranging in risk from bonds to equities to private equity and alternative investments) are gradually tokenized, they can be automatically rebalanced without the need for cumbersome procedures like wire transfers.
—Recommended reading by Maggie Hsu, a16z crypto marketing team: Crypto Yield 2025: User Insights into the Crypto Yield Market
II. On Intelligent Agents and Artificial Intelligence
2.1 From Know Your Customer (KYC) to Know Your AI Agent (KYA)
The bottleneck in the AI agent economy is shifting from intelligence to identity.
In the financial services sector, the number of "non-human identities" is now 96 times that of human employees—yet these identities exist like ghosts, without bank accounts. The key missing element here is KYA: Know Your AI Agent.
Just as people need credit scores to get loans, AI brokers also need cryptographically signed credentials to conduct transactions—linking brokers to their clients, their restrictions, and their responsibilities. Until then, merchants will continue to block AI brokers at their firewalls. This industry, which has spent decades building KYC infrastructure, now has only a few months to get KYA sorted out.
—Sean Neville, co-founder of Circle and architect of USDC; CEO of Catena Labs
2.2 Utilizing artificial intelligence to complete substantive research tasks
In January of this year, as a mathematical economist, I found it extremely difficult to get consumer-grade AI models to understand my workflow; however, by November, I was able to give models abstract instructions as if I were guiding doctoral students... and they sometimes even provided novel and correct answers.
Beyond my personal experience, we are beginning to see artificial intelligence applied in a wider range of research fields—especially in reasoning, where models can now not only directly assist in scientific discovery but also autonomously solve the Putnam Problem (perhaps the world’s most difficult college math exam).
Which fields most need this kind of research, and how it can be utilized, remains an open question. However, I anticipate that AI research will foster and encourage a new style of erudite research: one that encourages speculating on connections between ideas and quickly deriving more precise conclusions from more speculative answers. These conclusions may not be accurate, but they can still point in the right direction (at least within a certain topology). Ironically, this is somewhat like harnessing the power of model illusion: when models are "intelligent" enough, giving them the freedom to explore abstract spaces may still produce meaningless results, but sometimes it can lead to groundbreaking discoveries, just as people are often most creative when working without linear, definite directional constraints.
This reasoning approach requires a completely new AI workflow—not just direct interaction between agents, but also layers of nested models—where multi-layered models help researchers evaluate early-stage solutions and gradually extract truly valuable information. I've been using this method to write papers, while others are conducting patent searches, inventing new art forms, or (unfortunately) discovering new smart contract attack methods.
However, conducting research using a collection of encapsulated inference agents requires better interoperability between models, as well as a method to identify and appropriately compensate for the contributions of each model—both of which cryptographic techniques can help address.
—Scott Kominers, member of the a16z crypto research team, professor at Harvard Business School
2.3 Hidden Taxes on Open Networks
The rise of AI agents is imposing an invisible tax on the open web, fundamentally shaking its economic foundations. This shaking stems from a growing misalignment between the internet's contextual and executive layers: currently, AI agents extract data from ad-supported websites (the contextual layer) to provide convenience to users, but systematically bypass revenue streams that fund content (such as advertising and subscriptions) .
To prevent the open web from being eroded (and to protect the diverse content that underpins the development of AI), we need to deploy technological and economic solutions on a large scale. This could include next-generation sponsored content, micro-attribution systems, or other new financing models. Existing AI licensing agreements have also proven to be an unsustainable stopgap measure, often only compensating content providers for a portion of the revenue lost due to AI cannibalizing traffic.
The internet needs a completely new techno-economic model that allows value to flow automatically . A key transformation in the coming year lies in shifting from static licensing to real-time, usage-based compensation. This means testing and scaling systems—potentially leveraging blockchain-enabled micropayments and sophisticated attribution criteria—to automatically reward each entity that provides information for an agent to successfully complete a task.
—Liz Harkavy, a16z Cryptocurrency Investment Team
Recommended reading:
III. Regarding Privacy and Security
3.1 Privacy will be the most important moat in the crypto space.
Privacy is a key element in the global shift of finance to on-chain transactions, and it is also an element that almost all existing blockchains lack. For most blockchains, privacy is almost always an afterthought.
But today, privacy alone is enough to make a blockchain stand out from the crowd. Privacy has an even more important role: it can create a blockchain locking effect; or, in other words, a privacy network effect. This is especially important in today's world where performance alone is no longer enough to win.
Thanks to cross-chain protocols, migrating from one chain to another is effortless as long as all information is public. However, once information becomes private, the situation is quite different— crossing tokens across chains is easy, but crossing privacy across chains is difficult.
Moving within or outside private areas always carries risks; those monitoring the chain, mempool, or network traffic could identify you. Crossing the boundary between private and public chains—or even between two private chains—leaks various metadata, such as the correlation between transaction time and transaction size, making it much easier to track someone down.
Compared to numerous single-function, highly competitive emerging blockchains (whose block spaces are largely homogenized), blockchains with privacy features can generate stronger network effects. In fact, if a "general-purpose" blockchain doesn't have a thriving ecosystem, killer applications, or significant distribution advantages, almost no one will use it or develop on it—let alone remain loyal to it.
When users use public blockchains, they can easily transact with users on other chains—which chain they join is relatively unimportant. However, when users use private blockchains, their choice of chain becomes crucial, because once joined, they are less likely to easily switch chains, thus reducing the risk of information leakage. This creates a winner-takes-all situation. Because privacy is critical for most real-world applications, a few privacy chains may control the majority of cryptocurrencies.
—Ali Yahya, General Partner of a16z crypto
3.2 The (near-term) future of instant messaging must not only be resistant to quantum computing, but also achieve decentralization.
As the world prepares for quantum computing, many encryption-based instant messaging applications (such as Apple, Signal, and WhatsApp) have set an example and achieved significant results. However, the problem is that all mainstream instant messaging applications rely on our trust in private servers operated by a single entity. These servers are easily targeted by governments, which can easily shut them down, implant backdoors, or coerce users into handing over their private data.
What's the point of quantum encryption if a country can shut down your servers; if a company possesses the keys to a private server; or even if a company itself owns a private server? Private servers require "trust in me," but the absence of private servers means "you don't have to trust me." Communication doesn't need any company as an intermediary. Information transmission requires open protocols under which we don't need to trust anyone.
Our approach to achieving this goal is a decentralized network: no private servers, no single application, all open source, and top-tier encryption—including protection against quantum threats. In an open network, no individual, company, non-profit organization, or nation can deprive us of our communication capabilities. Even if a country or company shuts down an application, 500 new versions will emerge the next day. After a node is shut down, the existence of technologies like blockchain will provide economic incentives for a new node to immediately take its place.
When people control their information like they control their money—when they have that control—everything will change. Apps may come and go, but people will always control their information and identity; end users can now own their information even when they no longer use the app.
This is more important than quantum resistance and encryption; it's about ownership and decentralization. Without both, all we're doing is building a seemingly unbreakable encryption that can still be shut down.
—Shane Mac, Co-founder and CEO of XMTP Labs
3.3 Privacy as a Service
Behind every model, agent, and automated process lies a simple dependency: data. But most data pipelines today—the data that powers model inputs and outputs—are opaque, variable, and unauditable. This might not be a problem for some consumer applications, but many industries and users, such as finance and healthcare, demand confidentiality for sensitive data. It's also a significant obstacle for institutions currently seeking to tokenize real-world assets.
So how can we achieve secure, compliant, autonomous, and globally interoperable innovation while protecting privacy? There are many approaches, but I will focus on data access control: Who controls sensitive data? How does data flow? And who (or what) can access this data?
Without data access controls, anyone wanting to protect data confidentiality currently has to use centralized services or build custom systems—a time-consuming and labor-intensive process that prevents traditional financial institutions and other organizations from fully leveraging the capabilities and advantages of on-chain data management. As AI-powered systems begin to autonomously browse, transact, and make decisions, users and organizations across industries will need cryptographic safeguards, not just “best-effort trust.”
This is why I believe we need "privacy as a service": leveraging new technologies to provide programmable, native data access rules, client-side encryption, and decentralized key management, thereby enforcing who can decrypt what data under what conditions, and for how long… all of this is done on-chain. Combined with verifiable data systems, keys can become part of the internet's fundamental public infrastructure, rather than being patched up at the application layer afterward, making privacy a core infrastructure.
—Adeniyi Abiodun, Chief Product Officer and Co-founder of Mysten Labs
3.4 From "Code is Law" to "Standards are Law"
Recent DeFi hacks have targeted well-tested, mature protocols with strong teams, rigorous auditing mechanisms, and years of production experience. These incidents highlight a disturbing reality: current standard security practices still rely heavily on rules of thumb and case-by-case approaches.
To mature, DeFi security needs to shift from vulnerability patterns to design-level attributes, and from a "best-effort" approach to a "principled" approach.
- In the static/pre-deployment phase (testing, auditing, formal verification), this means systematically proving global invariants, rather than verifying carefully selected local invariants. Currently, several teams are building AI-assisted proof tools that can help write specifications, propose invariants, and alleviate the costly and extensive manual proof engineering work of the past.
- In the dynamic/post-deployment phase (runtime monitoring, runtime enforcement, etc.), these invariants can be translated into real-time safeguards: the last line of defense. These safeguards are directly encoded as runtime assertions that every transaction must satisfy.
So now, instead of assuming that every error is detected, we enforce key security properties in the code itself and automatically revert any transactions that violate these properties.
This is not just theoretical. In fact, almost all exploits to date have triggered these checks during execution, potentially preventing attacks. Therefore, the once-popular "code is law" concept has evolved into "standards are law": even entirely new attacks must meet the same security properties to ensure system integrity, thus leaving attacks either small-scale or extremely difficult to execute.
—Daejun Park, a16z Encryption Engineering Team
IV. Other Industries and Applications
4.1 The predicted market size is larger, more comprehensive, and more intelligent.
Prediction markets have become mainstream, and in the coming year, as they merge with cryptocurrencies and artificial intelligence, they will only become larger, more widespread, and more intelligent—while also presenting new and significant challenges for their builders.
First, more contracts will be launched. This means we'll be able to get real-time odds not only on major elections or geopolitical events, but also on a wide range of smaller, intertwined outcomes. As these new contracts reveal more information and integrate into the news ecosystem (which is already happening), they will raise important social questions, such as how to balance the value of this information and how to better design it to be more transparent and auditable—all of which can be achieved through cryptocurrency.
To handle the massive volume of contracts, new methods are needed to reach consensus and determine the truth behind them. While centralized platforms address the questions (Did an event actually happen? How do we verify it?), their limitations are demonstrated by controversial cases like the Zelensky suit market and the Venezuelan election market. To address these extreme cases and help expand prediction markets into more useful applications, novel decentralized governance and LLM oracles can help determine the truth behind controversial outcomes.
Artificial intelligence has opened up far more possibilities for oracles than LLMs. For example, AI agents trading on these platforms can search for global signals, providing short-term trading advantages and helping us discover new ways to think about the world and predict future trends. (Projects like Prophet Arena have already demonstrated the potential of this field.) Beyond acting as advanced political analysts we can query for insights, these agents can also reveal fundamental predictors of complex social events when we examine their emergent strategies.
Will prediction markets replace opinion polls? No; they can actually improve the efficiency of opinion polls (and opinion poll information can also be fed into prediction markets). As a political scientist, I'm most excited about how prediction markets can work in tandem with the rich and vibrant opinion polling ecosystem—but we need new technologies like artificial intelligence to improve the survey experience for respondents; we also need technologies like cryptocurrency to provide new ways to prove that respondents in opinion polls/questionnaires are not bots but real people, and so on.
—Andy Hall, Cryptocurrency Research Advisor at a16z, Professor of Political Economy at Stanford University
4.2 The Rise of Mortgage Media
The cracks in the traditional media model—and its so-called objectivity—have long been apparent. The internet has given everyone the right to a voice, and more and more operators, practitioners, and builders are beginning to engage directly with the public. Their views reflect their interests in the world, and surprisingly, audiences often respect them not because of their interests, but precisely because of those interests.
The real change isn't the rise of social media, but the emergence of encryption tools that enable people to make publicly verifiable commitments. As artificial intelligence makes generating massive amounts of content cheap and easy—anyone can say anything, whether the opinions or identities are real or fictitious—relying solely on human (or bot) voices is no longer sufficient.
Tokenized assets, programmable lock-up periods, prediction markets, and on-chain historical records provide a more solid foundation for trust: commentators can express their opinions and prove that they are consistent with their words and deeds; podcasters can lock up tokens to show that they are not engaging in speculative hype or "pump and dump"; analysts can link their predictions to publicly settled markets to create auditable performance records.
This is the rudimentary form of what I understand as " stakeholder media ": media that not only endorses the concept of "stake" but also provides corresponding evidence. In this model, credibility comes neither from feigned detachment nor unfounded assertions; rather, it stems from your ability to make transparent and verifiable commitments regarding your own interests. Stakeholder media does not replace other media forms but complements existing ones. It sends a new signal: not just "Believe me, I am neutral," but "This is the risk I'm willing to take, and how you can verify that what I'm saying is true."
—Robert Hackett, a16z crypto editorial team
4.3 Cryptocurrencies offer a new foundational technology that goes beyond blockchain.
For years, SNARKs (cryptographic proofs that verify the result of a computation without re-performing the computation) have been primarily used in the blockchain field. Their overhead is simply too high: the amount of work required to prove a computation can be a million times greater than directly running that computation. This approach is worthwhile when the cost is spread across thousands of validators, but impractical in other situations.
This is about to change. By 2026, zkVM provers will have approximately 10,000 times the overhead, with a memory footprint of only a few hundred megabytes—fast enough to run on a mobile phone and inexpensive enough to run anywhere. 10,000 times is a potentially phenomenal number, partly because high-end GPUs offer approximately 10,000 times the parallel throughput of laptop CPUs. By the end of 2026, a single GPU will be able to generate proofs that would otherwise be executed by a CPU in real time.
This could potentially turn a vision from early research papers into reality: verifiable cloud computing. If you're already running CPU workloads in the cloud—because your computational demands aren't sufficient for GPUs, or you lack the necessary expertise, or for historical reasons—you'll be able to obtain cryptographic correctness proofs at a reasonable cost. The prover is already optimized for GPUs; your code doesn't need to be.
—Justin Thaler, member of the a16z crypto research team, Associate Professor of Computer Science at Georgetown University
V. What else needs to be built?
5.1 For crypto businesses, transactions are merely a transit point, not the final destination.
Today, aside from stablecoins and some core infrastructure, almost all well-performing cryptocurrency companies seem to have already transitioned or are transitioning into the trading arena. But if "all cryptocurrency companies become trading platforms," what will become of the others? With so many players doing the same thing, market share will be eroded, ultimately leaving only a few true winners. This means that companies that transitioned to trading too early missed the opportunity to build more defensive and sustainable businesses.
I completely understand the efforts of any founder to improve their company's financial situation, but blindly pursuing immediate product-market fit can come at a cost. This problem is particularly pronounced in the cryptocurrency space, where the unique dynamics of tokens and speculative activity can lead founders down a path of short-sighted gratification in their search for product-market fit… much like the marshmallow experiment.
There's nothing wrong with transactions themselves—they're an important function of the market—but that's not the ultimate goal. Founders who focus on the "product" aspect of product-market fit are likely to be the bigger winners in the end.
—Arianna Simpson, General Partner, a16z crypto
5.2 Fully Unleashing the Potential of Blockchain: When the Legal Architecture Finally Matches the Technological Architecture
One of the biggest obstacles to building blockchain networks in the US over the past decade has been legal uncertainty. The scope of securities laws has been broadened, and enforcement has been selective, forcing founders to adopt a regulatory framework designed for the company rather than the network. For years, mitigating legal risks has replaced product strategy; the role of engineers has been overshadowed by lawyers.
This dynamic has led to a number of bizarre distortions: founders are told to avoid transparency; token distribution becomes legally arbitrary; governance degenerates into a show; organizational structures are optimized to circumvent legal risks; and tokens are designed to avoid economic value/failing to establish a business model. Worse still, crypto projects that manipulate the rules and defy conventional wisdom often outpace those that are genuinely well-built.
But regulatory oversight of the cryptocurrency market structure—with the government closer than ever to passing the bill—is expected to eliminate all these distortions next year. If passed, the legislation will incentivize transparency, establish clear standards, and replace “enforcement roulette” with a clearer, more structured path for financing, token issuance, and decentralization. Following GENIUS, the number of stablecoins exploded; legislation surrounding the cryptocurrency market structure will bring about even more significant changes, but this time the changes will target the entire network.
In other words, such regulation will enable blockchain networks to operate like other networks—open, autonomous, composable, trustworthy, neutral, and decentralized.
—Miles Jennings, a16z Crypto Policy Team and General Counsel
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