Crypto in 2026 According to a16z: These 17 Trends Will Reshape the Industry
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Crypto in 2026 According to a16z: These 17 Trends Will Reshape the Industry
17 insights about the future summarized by multiple partners at a16z.
Navigating Web3 tides with focused insightsAuthor: a16z New Media
Translation: TechFlow
Over the past two days, we've shared challenges and opportunities that the infrastructure, growth, life sciences & health, Speedrun, applications, and American Dynamism teams at a16z believe builders will face in 2026.
Today, we’re sharing 17 forward-looking insights summarized by multiple partners across a16z Crypto (and some special contributors). These themes span intelligent agents and artificial intelligence (AI), stablecoins, tokenization and finance, privacy and security, prediction markets, SNARKs (zero-knowledge proof technology), other applications—and how we’ll build in the future. (To stay updated on trends, builder guides, industry reports, and more crypto resources, be sure to subscribe to the a16z crypto newsletter.)
Tomorrow, we’ll wrap up this week with a special announcement and an exclusive invite from a16z—don’t miss it!
Here’s what we’re focusing on today:
Privacy will become the most important moat in crypto
Privacy is one of the key features needed to bring global finance on-chain—and it's also one of the few things missing from nearly every blockchain today. For most blockchains, privacy is merely an afterthought or even ignored altogether.
Yet today, privacy itself is compelling enough to differentiate a chain among many competitors. More importantly, privacy creates a “lock-in effect”—you could even call it a “privacy network effect.” This becomes especially critical in a world where competing purely on performance is no longer sufficient.
Thanks to bridge protocols, moving from one chain to another is extremely easy—as long as everything is public. But once privacy enters the picture, that convenience vanishes: moving tokens is easy, but moving secrets is hard. Transferring from a private chain to a public one—or between two private chains—always carries risks, such as third parties observing on-chain transactions, mempool activity, or network traffic identifying you. Crossing boundaries between private and public chains, or even between two private chains, leaks metadata like timing and scale correlations, making tracking easier.
Compared to numerous commoditized new chains whose fees may drop to zero due to competition (as blockspace essence becomes similar across chains), blockchains with privacy can generate stronger network effects. In fact, if a “general-purpose” blockchain lacks a thriving ecosystem, killer app, or asymmetric distribution advantage, there’s almost no reason for users to adopt or build on it—let alone develop loyalty.
On public blockchains, users can easily trade across chains—the choice of which chain to join doesn't matter much. But on privacy-focused blockchains, choosing a chain matters deeply because once users join, they're far less likely to migrate due to exposure risk. This creates a “winner-takes-all” dynamic. And since privacy is essential for most real-world use cases, a small number of privacy chains may dominate much of the crypto landscape.
—Ali Yahya, Partner, a16z Crypto
Prediction Markets: Bigger, Broader, Smarter Futures
Prediction markets have moved from niche to mainstream, and in the coming year, they'll grow bigger, broader, and smarter through convergence with crypto and AI—while presenting new and significant challenges for builders.
First, more contracts will be listed. This means we won't just get real-time probabilities about major elections or geopolitical events—we'll also see granular outcomes and complex cross-event dependencies. As these new contracts surface more information and integrate into news ecosystems (a trend already underway), they’ll raise important social questions: how to balance their informational value, how to design them better for transparency and auditability—problems solvable via cryptography (<SC will link to our related article>).
To handle larger volumes of contracts, we need new ways to reach consensus on truth resolution. Centralized platforms’ approaches (did an event really happen? How do we verify?) are crucial but exposed limitations in controversial cases like the Zelenskyy lawsuit market and Venezuela election market. To resolve edge cases and expand prediction markets into more useful applications, novel decentralized governance and large language model (LLM)-based oracles can help determine disputed outcomes.
AI’s use in oracles goes beyond LLMs. For example, AI agents trading on these platforms can scan global signals for short-term advantages, revealing new perspectives on the world and forecasting future developments. (Projects like Prophet Arena already hint at this potential.) Beyond serving as sophisticated political analysts we query for insights, studying these agents’ strategies might reveal fundamental predictors of complex social events.
Will prediction markets replace polls? No—they’ll make polls better (and poll data can feed into prediction markets). As a political scientist, I’m most excited about how prediction markets can work alongside a rich, vibrant polling ecosystem—but this requires new technologies: AI to improve survey experiences, and crypto to prove participants are human not bots, plus other functions.
—Andy Hall, Research Advisor, a16z Crypto (and Professor of Political Economy, Stanford University)
A More "Crypto-Native" View of Real-World Asset Tokenization and Stablecoins
We're seeing strong interest from banks, fintechs, and asset managers in bringing U.S. equities, commodities, indices, and other traditional assets on-chain. However, as more traditional assets go on-chain, this tokenization often remains "emulation"—based on current understanding of real-world assets rather than fully leveraging crypto-native capabilities.
But synthetic representations like perpetuals (perps) offer deeper liquidity and are typically easier to implement. Perpetuals also feature intuitive leverage mechanics, making them arguably the best-suited derivatives for crypto demand. I also believe emerging market equities are among the most promising asset classes to "perpify." (For instance, some stocks' 0-day-to-expiry options (0DTE) markets already show higher liquidity than spot markets—an intriguing opportunity for perpification.)
This comes down to "perpification vs. tokenization"—but either way, we should expect more crypto-native real-world asset (RWA) tokenization within the next year.
Similarly, in 2026, following stablecoins’ mainstream adoption in 2025, we’ll see more emphasis on “issuance, not just tokenization,” with outstanding stablecoin supply continuing to grow.
However, stablecoins without robust credit infrastructure resemble “narrow banks,” holding only specific liquid assets deemed particularly safe. While narrow banking is a valid product, I don’t believe it will serve as the long-term backbone of the on-chain economy.
We’ve already seen many new asset managers, curators, and protocols enabling on-chain loans backed by off-chain collateral. These loans are typically originated off-chain then tokenized. But I believe the benefits here are limited—perhaps just facilitating distribution to already-on-chain users. Therefore, debt assets should be originated directly on-chain rather than first off-chain then tokenized. On-chain origination reduces loan servicing and back-end structuring costs while improving accessibility. The challenge lies in compliance and standardization, but developers are already working on solutions.
—Guy Wuollet, General Partner, a16z Crypto
Crypto Businesses’ Pit Stop: Trading Isn’t the Final Destination
Today, aside from stablecoins and a few core infrastructures, nearly every successful crypto company has pivoted or is pivoting toward trading. But what happens to the industry if “every crypto company becomes an exchange”? When too many players do the same thing, attention gets diluted and only a few large companies win. It also means companies that pivot too early miss opportunities to build more defensible, enduring businesses.
While I empathize with founders trying to make their business models work, chasing short-term product-market fit comes at a cost. This is especially acute in crypto, where unique dynamics around tokens and speculation tempt founders toward instant gratification during product-market fit searches—a sort of “marshmallow test.” There’s nothing wrong with trading; it’s an important market function. But it shouldn’t necessarily be the end goal. Founders who focus on the “product” side of product-market fit may ultimately achieve greater success.
—Arianna Simpson, Partner, a16z Crypto
From KYC (“Know Your Customer”) to KYA (“Know Your Agent”)
The bottleneck in the agent economy is shifting from intelligence to identity.
In financial services, “non-human identities” now outnumber human employees 96 to 1—but these identities remain ghosted out of banking systems. What’s missing is critical infrastructure: KYA—Know Your Agent.
Just as humans need credit scores for loans, agents need cryptographically signed credentials to transact—credentials linking agents to principals, constraints, and responsibilities. Until this exists, merchants will keep blocking agents at firewalls. The financial industry spent decades building KYC infrastructure, but now it has only months to solve KYA.
—Sean Neville, Co-founder of Circle and USDC Architect; CEO, Catena Labs
The Future of Stablecoins: Better, Smarter Onramps and Offramps
Last year, stablecoin transaction volume hit an estimated $46 trillion, setting new records. To put this in perspective: it’s over 20x PayPal’s volume; nearly 3x one of the world’s largest payment networks, Visa; and rapidly approaching the volume of the U.S. Automated Clearing House (ACH)—the electronic network handling direct deposits and other financial transactions in the U.S.
Today, you can send a stablecoin transaction in under a second for less than a penny. Yet unresolved is how to connect these digital dollars to people’s everyday financial systems—in other words, how to build better stablecoin onramps and offramps.
A new generation of startups is filling this gap, connecting stablecoins to familiar payment systems and local currencies. Some use cryptographic proofs to let people privately swap local balances into digital dollars. Others integrate with regional networks, using QR codes, real-time payment rails, etc., for interbank transfers… Still others are building truly interoperable global wallet layers and card issuance platforms, letting users spend stablecoins at everyday merchants. Together, these approaches broaden participation in the digital dollar economy and could accelerate stablecoins becoming mainstream payment methods.
As these onramps and offramps mature, digital dollars will plug directly into local payment systems and merchant tools, enabling new behaviors: cross-border workers receiving salaries instantly; merchants accepting global dollar payments without bank accounts; apps settling with users instantly anytime, anywhere. Stablecoins will evolve from niche financial tools into the internet’s foundational settlement layer.
—Jeremy Zhang, a16z Crypto Engineering Team
Stablecoins: Unlocking Bank Ledger Upgrade Cycles, Enabling New Payment Scenarios
Today, many banks still run software systems unrecognizable to modern developers: Banks were early adopters of large software systems in the 1960s–70s; second-gen core banking software (like Temenos’ GLOBUS and Infosys’ Finacle) emerged in the 80s–90s. Yet these systems are aging, and upgrades are painfully slow. Thus, banking—especially critical core ledger databases tracking deposits, collateral, and other obligations—still widely runs on mainframe computers using COBOL, relying on batch file interfaces instead of modern APIs.
The vast majority of global assets still reside on these decades-old core ledgers. While battle-tested, trusted by regulators, and deeply embedded in complex banking operations, they also stifle innovation. Adding critical features like real-time payments (RTP) to these systems can take months or years, burdened by technical debt and regulatory complexity.
This is where stablecoins shine. Over recent years, stablecoins found product-market fit and entered the mainstream. This year, traditional financial institutions (TradFi) embraced stablecoins at unprecedented levels. Stablecoins, tokenized deposits, tokenized Treasuries, and on-chain bonds now let banks, fintechs, and financial institutions build new products and serve new customers. Crucially, they enable innovation without completely rewriting legacy systems—systems that, while outdated, have operated reliably for decades. Thus, stablecoins offer institutions a new path to innovation.
—Sam Broner
Decentralization Is the Future of Messaging—More Important Than Quantum Encryption
As the world moves toward quantum computing, encrypted messaging apps (like Apple, Signal, WhatsApp) are leading the charge with impressive results. But here’s the problem: nearly all major messaging apps rely on private servers operated by single organizations. These servers are easy targets for governments to shut down, implant backdoors, or compel access to private data.
If a country can shut down your server, if a company holds the keys to its private servers, or even if a company simply owns a private server, how meaningful is quantum encryption? Private servers require users to “trust me,” but without private servers, it means “you don’t need to trust me.” Communication doesn’t need a middleman company to operate.
Messaging needs open protocols where users don’t have to trust anyone. That’s achieved through decentralized networks: no private servers, no single app, all code open-source, and top-tier encryption—including quantum-resistant cryptography.
With open networks, no individual, company, nonprofit, or nation can take away our ability to communicate. Even if a country or company shuts down an app, 500 new versions will appear the next day. If a node goes down, economic incentives from technologies like blockchain ensure new nodes immediately replace it.
Everything changes when people control their messages with keys, just like they control their money. Apps may come and go, but users retain control over their messages and identities. Even if an app fails, end users still own their messages.
This isn’t just about quantum resistance and encryption—it’s about ownership and decentralization. Without both, we’re building encrypted systems that can’t be cracked but can still be shut down.
—Shane Mac, Co-founder and CEO, XMTP Labs
From “Code Is Law” to “Specifications Are Law”—A New Evolution in DeFi Security
Recent DeFi hacks have targeted battle-tested protocols run by strong teams, rigorously audited, and live for years. These incidents reveal an unsettling reality: current security practices still rely heavily on heuristics and case-by-case fixes.
For DeFi security to mature further, we must shift from patching vulnerability patterns to designing-in property guarantees—from “best effort” to “principled approach”:
In static/pre-deployment phases (testing, audits, formal verification, etc.), this means systematically verifying global invariants—not just hand-picked local ones. Today, AI-assisted proof tools being built by multiple teams can help write specifications, propose invariants, and offload expensive, time-consuming manual proof engineering.
In dynamic/post-deployment phases (runtime monitoring, runtime enforcement, etc.), these invariants can become real-time “guardrails”—a last line of defense. These guardrails are coded as runtime assertions, ensuring every transaction must satisfy them.
Thus, instead of assuming every bug was caught upfront, we embed critical security properties directly into code, automatically reverting any transaction violating them.
This isn’t theoretical. Practically every attack ever executed would trigger these checks mid-execution, potentially halting hackers. So, the “code is law” philosophy evolves into “specifications are law”: even novel attacks must satisfy security properties preserving system integrity, leaving only minor or extremely difficult exploits possible.
—Daejun Park, a16z Crypto Engineering Team
Cryptography Beyond Blockchains: A New Era of Verifiable Computation
For years, SNARKs (Succinct Non-Interactive Arguments of Knowledge)—a cryptographic proof technique verifying computations without re-executing them—were used almost exclusively in blockchains. This was due to high computational costs: proving a computation required ~1,000,000x more work than running it. This overhead justified only when amortized across thousands of verifiers, impractical elsewhere.
That’s changing. By 2026, zkVM (zero-knowledge virtual machine) provers will have ~10,000x overhead, requiring only hundreds of megabytes of memory—fast enough to run on phones, cheap enough for broad use. Why might “10,000x” be magical? Because high-end GPUs offer ~10,000x parallel throughput versus laptop CPUs. By late 2026, a single GPU could generate proofs in real time for CPU-executed computations.
This breakthrough could realize visions from early research papers: verifiable cloud computing. If you’re already running CPU workloads in the cloud—whether due to insufficient GPU utilization, lack of expertise, or legacy system constraints—you’ll gain cryptographic proofs of computational correctness at reasonable cost. And these provers are already optimized for GPUs, requiring no code changes.
—Justin Thaler, Researcher, a16z Crypto & Associate Professor of Computer Science, Georgetown University
AI Will Become a Research Assistant
As a mathematical economist, in January I struggled to get consumer-grade AI models to understand my workflow; by November, I could give abstract instructions like I would to a PhD student… and sometimes receive novel, correct answers. Beyond my experience, we’re beginning to see AI applied broadly in research, especially reasoning—models now not only participate directly in discovery but autonomously solve Putnam problems (among the hardest undergraduate math exams).
It’s still unclear where this research assistance will be most effective or exactly how it’ll work. But I expect AI research will foster and reward a new “versatile” research style: emphasizing the ability to speculate relationships between ideas and quickly extrapolate from more hypothetical answers. These answers may not be perfectly accurate but point in the right direction (at least topologically). Ironically, this leverages model “hallucinations”: when models are smart enough, giving them abstract space to explore may generate nonsense—but also spark discoveries, akin to human creativity in nonlinear, ambiguous directions.
This reasoning demands a new AI workflow—not just “agent-to-agent,” but “agent-wrapping-agent” structures. Here, layered models help researchers evaluate early models’ methods, gradually extracting valuable insights. I’m already using this to write papers; others use it for patent searches, creating new art forms, or (regrettably) finding novel smart contract attack vectors.
Efficiently running such reasoning-agent research systems requires better inter-model interoperability and methods to identify and fairly compensate each model’s contributions—challenges cryptography can help address.
—Scott Kominers, Member, a16z Crypto Research Team & Professor, Harvard Business School
The Open Web’s “Invisible Tax”: Economic Imbalance in the AI Age and How to Fix It
With the rise of AI agents, the open web faces an invisible tax fundamentally undermining its economic foundation. This erosion stems from growing mismatch between the web’s “Context Layer” and “Execution Layer”: currently, AI agents extract data from ad-supported content sites (context layer), providing user convenience while systematically bypassing revenue sources (ads, subscriptions) sustaining that content.
To prevent further erosion of the open web and protect the diverse content ecosystem fueling AI, we need large-scale technological and economic solutions. This may include next-gen sponsored content models, micro-attribution systems, or other novel funding mechanisms. Yet existing AI licensing agreements prove financially unsustainable—often compensating content providers for only a fraction of lost traffic revenue.
The web needs a new techno-economic model enabling automated value flows. The key shift over the next year will be moving from static licensing to real-time usage-based compensation. This means testing and scaling systems—possibly using blockchain-powered nanopayments and advanced attribution standards—to automatically reward every entity contributing information enabling AI agents to complete tasks successfully.
—Liz Harkavy, a16z Crypto Investment Team
The Rise of “Staked Media”: Rebuilding Trust with Blockchain
Cracks in traditional media’s notion of “objectivity” have been visible for a while. The internet gave everyone a voice, and now more operators, practitioners, and builders speak directly to the public. Their perspectives reflect their stakes in the world—and surprisingly, audiences often respect them for those stakes, not despite them.
The real change isn’t social media’s rise, but the arrival of crypto tools letting people make publicly verifiable commitments. In an age where AI makes generating infinite content cheap and easy—under real or fake identities, from any viewpoint—relying solely on what people (or bots) say is insufficient. Tokenized assets, programmable lockups, prediction markets, and on-chain histories provide stronger foundations for trust: commentators can prove they “put skin in the game” while sharing views; podcasters can lock tokens to show they won’t “pump and dump” speculatively; analysts can tie predictions to publicly settled markets, creating auditable records.
This is the dawn of what I call “staked media”: a form of media embracing not just “skin in the game” but providing proof. Here, credibility doesn’t come from feigned detachment or baseless claims, but from clear, transparent, verifiable commitments. “Staked media” won’t replace other media forms but complement them. It offers a new signal: not “trust me, I’m neutral,” but “this is the risk I’m willing to take, and here’s how you can verify my honesty.”
—Robert Hackett, a16z Crypto Editorial Team
“Secrets-as-a-Service”: How Privacy Protection Becomes Core Internet Infrastructure
Behind every model, agent, and automated system lies a simple yet critical factor: data. Yet most data pipelines today—flows into or out of models—are opaque, mutable, and un-auditable. This may suffice for some consumer apps, but for many industries and users (finance, healthcare), enterprises need to ensure sensitive data privacy. For institutions trying to tokenize real-world assets, this is a major barrier.
So how can we innovate securely, compliantly, autonomously, and globally while protecting privacy? While many approaches exist, I focus on data access control: Who controls sensitive data? How does it flow? Who (or what) can access it?
Without data access control, anyone wanting to protect data confidentiality relies on centralized services or custom solutions—time-consuming, expensive, and hindering traditional financial institutions and others from fully leveraging on-chain data management’s benefits. As agent systems begin browsing, trading, and deciding autonomously, users and institutions across sectors need cryptographic guarantees, not “best effort” trust.
Therefore, I believe we need “Secrets-as-a-Service”: a new technology offering 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 via on-chain mechanisms. Combined with verifiable data systems, “secrets” can become part of the internet’s basic public infrastructure, not a privacy feature bolted on post-hoc at the application layer. This makes privacy a core internet infrastructure.
—Adeniyi Abiodun, Chief Product Officer and Co-founder, Mysten Labs
Wealth Management for Everyone
Personalized wealth management has traditionally served only high-net-worth clients, as delivering customized advice across asset classes and personalized portfolio allocations is costly and complex. Yet as more asset classes become tokenized, crypto infrastructure enables AI-recommended and assisted personalized investment strategies to execute and adjust instantly at extremely low cost.
This isn’t just an upgrade to “robo-advisors”: everyone can enjoy active portfolio management, not just passive. In 2025, traditional finance (TradFi) allocated 2–5% of portfolios to crypto (via direct bank investments or ETPs)—but this is just the beginning. By 2026, we’ll see more platforms focused on “wealth accumulation” rather than just “wealth preservation” emerge—fintechs (like Revolut and Robinhood) and centralized exchanges (like Coinbase) leveraging their tech advantages to capture larger market shares.
Meanwhile, DeFi tools like Morpho Vaults can automatically allocate assets to lending markets with optimal risk-adjusted returns, forming a core yield engine for portfolios. Additionally, holding residual liquid funds as stablecoins instead of fiat and investing in tokenized money market funds rather than traditional ones further expands yield possibilities.
Finally, average investors now gain easier access to more illiquid private market assets like private credit, pre-IPO companies, and private equity. Tokenization unlocks these markets while still meeting compliance and reporting requirements. As components balancing portfolios become tokenized (from bonds to equities to private and alternative assets across the risk spectrum), these assets can rebalance automatically without cumbersome processes like bank transfers.
—Maggie Hsu, a16z Crypto Market Development Team
The Internet Becomes a Bank: The Future of Value Flow
With widespread adoption of AI agents and more transactions happening automatically in the background rather than through user clicks, how money—how value flows—must change. In a system operating on intent rather than step-by-step instructions, value movement may occur as AI agents identify needs, fulfill obligations, or trigger outcomes. Here, value must flow as quickly and freely as information does today, and blockchains, smart contracts, and new protocols are key to achieving this.
Today, smart contracts can settle dollar payments globally in seconds. By 2026, emerging foundational tools (like x402) will make this settlement programmable and reactive. Agents can pay each other instantly and permissionlessly for data, GPU time, or API calls—no invoicing, reconciliation, or batching; developers can release software updates with built-in payment rules, limits, and audit trails—no fiat integration, merchant onboarding, or bank involvement; prediction markets can settle automatically in real time as events unfold—no custodians or exchanges, odds updating live, agents trading, payments settling globally in seconds.
When value flows this way, “payment processing” ceases to be a separate operational layer and becomes part of network behavior. Banks become part of internet infrastructure, and assets become infrastructure. If money can be routed across the internet like data packets, then the internet doesn’t just support financial systems—it becomes the financial system.
—Christian Crowley and Pyrs Carvolth, a16z Crypto Market Development Team
When Legal Architecture Matches Technical Architecture: Unlocking Blockchain’s Full Potential
Over the past decade, one of the biggest obstacles to building blockchain networks in the U.S. has been legal uncertainty. Securities laws were extended and selectively enforced, forcing entrepreneurs into regulatory frameworks designed for companies, not networks. For years, mitigating legal risk replaced product strategy; engineers’ roles were overtaken by lawyers.
This dynamic created many strange distortions: entrepreneurs told to avoid transparency; token distributions made legally arbitrary; governance devolving into performative “theater”; organizational structures optimized for legal shields; token designs forced to avoid economic value, even lacking business models. Worse, crypto projects circumventing rules often grew faster than honest builders.
Yet the U.S. government is closer than ever to passing crypto market structure regulation, legislation expected to eliminate these asymmetries next year. If passed, this legislation would incentivize transparency, set clear standards, and replace the “enforcement roulette” with clearer, structured pathways for fundraising, token issuance, and decentralization. Just as GENIUS supercharged stablecoin adoption explosively, crypto market structure legislation will drive an even bigger transformation—one built for networks.
In other words, this regulation would allow blockchain networks to truly operate as networks—open, autonomous, composable, credibly neutral, and decentralized.
—Miles Jennings, a16z Crypto Policy Team & General Counsel
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