Original Title: 17 things we're excited about for crypto in 2026
Original Author: a16z New Media
Translated by: Peggy, BlockBeats
Editor’s Note: As we enter 2026, the crypto industry is undergoing a profound structural redefinition: from stablecoins and RWA, to AI agent ecosystems, privacy networks, prediction markets, and the reshaping of legal frameworks, outlining a key year of technological and institutional turning points. The crypto industry is shifting from "performance competition of chains" to "network effect competition," from "code is law" to "specifications are law," and from transaction-driven to product-driven; AI is driving the comprehensive evolution of the agent economy and prediction systems.
This article gathers 17 forward-looking observations from various teams at a16z, providing a framework for understanding the next phase of crypto narratives and industry directions.
Here is the original text:
This week, partners from a16z's teams including Apps, American Dynamism, Bio, Crypto, Growth, Infra, and Speedrun released their annual "Big Ideas" trend outlook.
The following content compiles observations from several partners of the a16z crypto team (as well as a few guest authors) on future developments, covering themes from smart agents and AI, stablecoins and asset tokenization, financial innovation, to privacy and security, prediction markets, SNARKs, and other application scenarios… extending to future building methods.
About Stablecoins, RWA Tokenization, Payments, and Finance
Smarter and More Efficient Stablecoin On/Off-Ramp Infrastructure
Last year, the trading volume of stablecoins was estimated to reach $46 trillion, continuously breaking historical records. To better understand this scale: this figure is over 20 times that of PayPal; nearly 3 times the trading volume of Visa, one of the world's largest payment networks; and is rapidly approaching the annual trading volume of the U.S. Automated Clearing House (ACH), which is typically used for direct deposit of wages.
Today, you can complete a stablecoin transfer in less than a second and at a cost of less than 1 cent. But the real unresolved issue is: how to connect these digital dollars to the financial networks that people actually use every day—namely, the on/off-ramp mechanisms for stablecoins.
A wave of new startups is entering this gap, attempting to connect stablecoins with local payment systems and fiat currencies. Some utilize cryptographic proofs to allow users to privately convert local balances into digital dollars; others integrate with regional payment networks, leveraging capabilities like QR codes and real-time payment rails to facilitate interbank payments… and some are building truly interoperable global wallet layers, as well as platforms that allow users to spend directly with stablecoins.
Overall, these paths collectively expand the range of people who can join the digital dollar economy and may drive stablecoins to be used more directly in mainstream payment scenarios.
As these on/off-ramp infrastructures mature, allowing digital dollars to connect directly with local payment systems and merchant tools, new behavioral patterns will emerge:
Cross-border workers can settle their salaries in real-time;
Merchants can accept global dollars without needing a bank account;
Applications can settle value with global users instantly.
Stablecoins will transition from a "niche financial tool" to a foundational settlement layer of the internet era.
——Jeremy Zhang, a16z crypto engineering team
Thinking About RWA Tokenization and Stablecoins in a More "Crypto-Native" Way
In recent years, banks, fintech companies, and asset managers have increasingly sought to bring U.S. stocks, commodities, indices, and other traditional assets on-chain. However, many current RWA tokenizations exhibit a clear "skeuomorphic" tendency: they are still based on traditional thinking about real-world assets and have not leveraged the advantages of being crypto-native.
Synthetic asset forms like perpetual contracts (perps) often provide deeper liquidity and are simpler to implement. The leverage structure of perpetual contracts is also easier to understand, which is why I believe they are the most product-market fit "crypto-native derivatives." Additionally, I think emerging market stocks are one of the asset classes most worthy of "perpetualization." For example, the 0-day to expiration (0DTE) options market for certain stocks often has more liquidity than the spot market, making it an ideal candidate for perp experimentation.
Ultimately, this raises a question: "Perpetualization vs. Tokenization." Regardless, we will see more crypto-native forms of RWA tokenization in the coming years.
Similarly, in the stablecoin space, in 2026 we will see "not just tokenization, but also on-chain origination." Stablecoins fully entered the mainstream in 2025, and their issuance scale continues to grow.
However, stablecoins without a robust credit infrastructure are essentially akin to "narrow banks"—they only hold a small portion of liquidity assets deemed extremely safe. Narrow banks are certainly an effective product, but I do not believe they will become the backbone of the on-chain economy in the long term.
We are currently seeing some new asset managers, asset curators, and protocols beginning to facilitate on-chain loans backed by off-chain assets. These loans are typically issued off-chain and then tokenized. However, I believe that aside from the convenience of distributing to on-chain users, there is not much advantage to the off-chain lending followed by tokenization.
This is why debt-type assets should be originated on-chain directly, rather than off-chain and then tokenized. On-chain origination can reduce the costs of loan servicing, backend structure, and enhance accessibility. The real challenge lies in compliance and standardization, but teams are already working on these issues.
——Guy Wuollet, a16z crypto general partner
Stablecoins Will Initiate a Technological Upgrade Cycle for Bank Ledgers and Foster New Payment Scenarios
Most banks still operate outdated software systems that modern developers can hardly recognize: in the 1960s and 70s, banks were early adopters of large software systems; the second generation of core banking systems emerged around the 1980s and 90s (such as Temenos's GLOBUS and InfoSys's Finacle). However, these systems have gradually aged, and the pace of upgrades has not kept up with the demands of the times.
Thus, the most critical core ledger in the banking system—the database that records deposits, collateral, and various financial obligations—often still runs on mainframes, written in COBOL, and relies on batch file interfaces rather than APIs.
The vast majority of global assets are also stored in these same "decades-old" core ledgers. Although these systems have been long-tested in practice, are recognized by regulators, and are deeply embedded in complex business processes, they also significantly limit the speed of innovation.
For example, adding features like real-time payments (RTP) often takes months or even years and must navigate layers of technical debt and regulatory hurdles.
This is where stablecoins can play a role. Over the past few years, stablecoins have found a true product-market fit and entered the mainstream, and this year, traditional financial institutions have reached a new level of acceptance of stablecoins.
Stablecoins, tokenized deposits, tokenized government bonds, and on-chain bonds enable banks, fintech companies, and institutions to build new products and serve new customers. More importantly, they do not require rewriting those core systems that, while outdated, have been reliably running for a long time. Thus, stablecoins have become a new path for institutional innovation.
——Sam Broner
The Internet Will Become the New "Bank"
As smart agents scale, more and more commercial activities will no longer rely on user clicks but will be completed automatically in the background, necessitating a change in how value moves.
In a world where systems act based on "intent" rather than step-by-step instruction execution, when AI agents automatically move funds due to recognizing needs, fulfilling obligations, or triggering outcomes, value must flow as quickly and freely as information. This is where blockchain, smart contracts, and new protocols come into play.
Smart contracts can already complete global dollar settlements in seconds. In 2026, new primitives like x402 will make such settlements programmable and responsive:
Agents can instantly and permissionlessly pay each other data, GPU time, or API fees—without invoices, reconciliations, or batch processing;
Payment rules, limits, and audit trails are directly included in software updates released by developers—without integrating fiat systems, merchant onboarding, or bank connections;
Prediction markets can self-settle in real-time during events—odds update, agent trades, and profits settle globally in seconds… without custodians or exchanges.
When value can move in this way, "payment flows" will no longer be an independent operational layer but a network behavior: banks become part of the underlying plumbing of the internet, and assets become infrastructure.
If currency becomes "packets" that can be routed by the internet, then the internet not only supports the financial system—it will itself become the financial system.
——Christian Crowley and Pyrs Carvolth, a16z crypto business implementation team
Wealth Management Will Become a "Universal" Service
For a long time, personalized wealth management services have only been available to high-net-worth clients, as providing customized advice and portfolio management for different asset classes is both expensive and complex. However, as more assets are tokenized, crypto networks enable these strategies to be executed and rebalanced instantly with AI-generated advice and assistance, at almost no cost.
This is not just "robo-advisory"; active management will become accessible to everyone, not just passive management.
In 2025, traditional financial institutions increased their allocation to crypto assets (directly or through ETPs), but that was just the beginning. In 2026, we will see more platforms focused on "wealth accumulation" (rather than just wealth preservation)—especially those fintech companies (like Revolut, Robinhood) and centralized exchanges (like Coinbase) that can leverage technological stack advantages.
Meanwhile, DeFi tools like Morpho Vaults can automatically allocate assets to the lending markets with the best risk-adjusted returns, becoming a foundational yield configuration in portfolios. Holding other liquid assets in stablecoins rather than fiat, or in tokenized money market funds rather than traditional MMFs, further expands yield possibilities.
Finally, retail investors now find it easier to access illiquid private market assets, such as private credit, pre-IPO companies, and private equity. Tokenization enhances accessibility while maintaining necessary compliance and reporting requirements.
As various asset classes in balanced portfolios (from bonds to stocks to private and alternative assets) gradually become tokenized, they can also achieve automatic, intelligent rebalancing without cross-bank wire transfers.
——Maggie Hsu, a16z crypto business implementation team
About Agents and AI
From "Know Your Customer" (KYC) to "Know Your Agent" (KYA)
The bottleneck of the agent economy is shifting from intelligence itself to identity.
In financial services, the number of "non-human identities" now exceeds human employees by a ratio of 96:1—but these identities remain unaccepted as "unbanked ghosts." The most lacking foundational capability is KYA: Know Your Agent.
Just as humans need credit scores to obtain loans, AI agents also require cryptographic signed credentials to conduct transactions—these credentials must bind the agent to their principals, behavioral constraints, and boundaries of responsibility. Until this infrastructure emerges, merchants will continue to block agent access at the firewall level.
The industry that has built KYC infrastructure for decades now has only a few months to solve KYA.
——Sean Neville, Co-founder of Circle, Architect of USDC; CEO of Catena Labs
We Will Use AI to Complete Substantive Research Tasks
As a mathematical economist, I found it difficult earlier this year to get consumer-grade AI models to understand my research process; by November, I was able to give abstract instructions to the model as if I were guiding a PhD student… and sometimes received novel and correctly executed answers.
More broadly, we are seeing AI begin to be used in genuine research activities—especially in reasoning fields, where models can not only assist in discovery but even autonomously solve mathematically challenging problems (one of the hardest university math competitions globally).
It remains unclear which disciplines will benefit the most and how exactly they will benefit. However, I believe AI will promote and reward a new "polymath" research style: one that can hypothesize between ideas and quickly extrapolate from more exploratory intermediate results.
These answers may not be entirely accurate, but they may still point in the right direction (at least in some topological sense).
To some extent, this resembles leveraging the model's "hallucination ability": when models are "smart" enough, their collisions in abstract space may generate meaningless content, but occasionally they will trigger genuine breakthroughs, much like humans do during nonlinear thinking.
Reasoning in this way requires a new style of AI workflow—not just collaboration between agents, but "agent-wrapping-agent": multi-layer models evaluating the attempts of earlier models and continuously refining the truly valuable parts. I am writing papers this way, while others use it for patent searches, creating new art forms, or (unfortunately) designing new types of smart contract attacks.
However, to make this "wrapped reasoning agent cluster" truly serve research, two issues must be resolved: interoperability between models and how to identify and reasonably compensate each model's contributions—both of which may be solvable through cryptographic technology.
——Scott Kominers, a16z crypto research team; Professor at Harvard Business School
The "Invisible Tax" Facing Open Networks
The rise of AI agents is imposing an invisible tax on open networks and fundamentally shaking their economic foundations.
This disruption stems from the misalignment between the "context layer" and the "execution layer" of the internet: currently, AI agents extract data from content sites that rely on advertising revenue (the context layer) to provide convenience to users, while systematically bypassing the revenue sources that support this content (advertising and subscriptions).
To prevent the erosion of open networks (and to prevent the content ecosystem that AI itself relies on from being weakened), we need to deploy technological and economic mechanisms on a large scale: this may include new generations of sponsored content models, micro-attribution systems, or other new funding distribution models.
Current AI authorization protocols have proven unsustainable—they often pay content providers amounts that are merely a fraction of the losses caused by AI's erosion of traffic.
Open networks need a new technological-economic framework that allows value to flow automatically. The most critical shift in the coming year is moving from static authorization to real-time, usage-based compensation models.
This means we need to test and expand systems—potentially based on blockchain-supported nanopayments and refined attribution standards—so that every entity contributing information successfully for agent tasks can automatically receive rewards.
——Liz Harkavy, a16z crypto investment team
About Privacy (and Security)
Privacy Will Become the Most Important "Moat" in the Crypto Space
Privacy is a key capability driving the global migration of finance onto the blockchain. It is also a characteristic that almost all existing blockchains lack. For most chains, privacy has long been merely a "nice-to-have" feature.
However, today, privacy alone is sufficient to differentiate one chain from all others. More importantly, privacy can create chain-level lock-in effects—a "privacy version of network effects," especially in an era where performance competition can no longer provide differentiation.
Due to the existence of cross-chain protocols, as long as everything is public, migrating from one chain to another is almost costless. But once privacy is introduced, the situation changes dramatically: transferring tokens across chains is easy, but transferring "secrets" across chains is difficult.
Any process of entering or exiting a public chain from a private chain will allow observers of the blockchain, mempool, or network traffic to infer your identity. Migration between different private chains can also leak various metadata, such as time correlations or amount correlations, making tracking easier.
In contrast, those new chains lacking differentiation, where costs will be driven to zero in competition (as blockspace becomes highly homogeneous), privacy chains can form stronger network effects.
The reality is that a "generic chain" without a thriving ecosystem, killer applications, or distribution advantages has little reason to attract users or developers, making it harder to foster loyalty.
When users are on public chains, as long as chains can interact freely, which chain to join is not important. But once users join a private chain, the choice of chain becomes very important—because once they join, they will be less willing to migrate and expose themselves to risks.
This will create a "winner takes most" dynamic.
And because privacy is extremely critical for most real-world applications, ultimately, only a few privacy chains may dominate the majority of the crypto economy.
——Ali Yahya, a16z crypto general partner
The (Near) Future of Messaging Communication: Not Only Quantum-Resistant but Also Decentralized
As we move toward the quantum computing era, many encryption-dependent communication applications (Apple, Signal, WhatsApp) have done a lot of cutting-edge work. But the problem is: today, all mainstream communication tools rely on privately operated servers by a single organization.
These servers are vulnerable points that governments can shut down, implant backdoors in, or demand data from.
If a country can directly shut down a server; if a company holds the server keys; or simply if there exists a "private server"… then what is the significance of quantum-level encryption?
Private servers require "trust me"; but without servers means "you don't have to trust me."
Communication does not need a centralized company in the middle. What we need is an open protocol that requires no trust in anyone.
To achieve this, the network must be decentralized: no private servers; no single app; all code open-source; top-tier encryption (including quantum resistance).
In an open network, no individual, company, nonprofit organization, or country can take away our communication capabilities. Even if a country or company shuts down an app, 500 new versions will appear the next day.
Even if one node is shut down, new nodes will immediately join to replace it due to the economic incentives of mechanisms like blockchain.
When people control information with their own keys just as they control their "money," everything will change. Apps can come and go, but users will always control messages and identities—users own the messages, not the apps.
This is not just a matter of quantum resistance or encryption; it is a matter of ownership and decentralization.
Without these two, we are merely building an encryption that is "unbreakable yet can still be shut down."
——Shane Mac, Co-founder and CEO of XMTP Labs
"Secrets-as-a-Service"
Behind every model, every agent, and every automation system lies one thing: data.
But today, most data pipelines—model inputs and outputs—are opaque, mutable, and un-auditable.
This may suffice for some consumer applications, but for industries that need to handle sensitive data (such as finance and healthcare), such mechanisms are far from adequate.
This is also a major obstacle preventing institutions from fully tokenizing real-world assets.
So, how can we achieve secure, compliant, autonomous, and globally interoperable innovation while maintaining privacy?
We need to start with data access control: who controls sensitive data? How does data move? Who (or what system) can access it?
In the absence of data access control, anyone wishing to protect privacy must rely on centralized services or build complex systems themselves—this is not only time-consuming and expensive but also hinders traditional financial institutions from fully leveraging the advantages of on-chain data management.
As smart agents begin to autonomously browse, trade, and make decisions, users and institutions need not "best-effort trust," but cryptographic-level guarantees.
Therefore, we need "Secrets-as-a-Service": new technologies that provide programmable, native data access rules; client-side encryption;
Decentralized key management—clearly defining who can decrypt what data under what conditions and for how long… all enforced on-chain.
Combined with verifiable data systems, "secrets" will become the underlying public infrastructure of the internet, rather than an "application-level patch" added afterward.
Privacy will become part of the infrastructure, not an ancillary feature.
——Adeniyi Abiodun, Co-founder and Chief Product Officer of Mysten Labs
From "Code is Law" to "Specifications are Law"
Recent DeFi attack incidents, even occurring in mature protocols with years of practical experience, strong teams, and rigorous audits, have exposed a disturbing reality: current security practices are essentially still empirical and "case-by-case."
To advance DeFi security into a mature stage, we must shift from bug patterns to design-level properties, from "best-effort" to a principled systematic approach:
Static/Pre-deployment security (testing, auditing, formal verification)
The future focus should be on systematically proving global invariants, rather than just verifying a few manually selected local properties.
Now, multiple teams are building AI-assisted proof tools that can help write specifications, propose invariants, and automatically handle a large amount of proof engineering work that previously required manual effort and was costly.
Dynamic / Post-deployment Security (Runtime Monitoring, Runtime Enforcement, etc.)
Once on-chain, these invariants can become the system's real-time guardrails: serving as the last line of defense.
These guardrails will be encoded as runtime assertions, requiring that every transaction must meet the relevant security conditions.
In other words, we no longer assume that "all vulnerabilities have been captured before deployment," but instead let the code itself enforce core security properties, automatically rolling back any transactions that violate these properties.
This is not just theoretical; it has practical significance.
In fact, almost every attack in the past could have triggered these checks during the execution phase, thereby halting the hacker's attack.
Thus, the once-popular idea of "code is law" is evolving into: "spec is law."
Even new types of attacks must satisfy the same set of security properties in the system design; thus, the space for attacks is compressed, leaving only very few or very difficult possibilities for execution.
——Daejun Park, a16z crypto engineering team
About Other Industries and Applications
Prediction Markets Will Become Larger, Broader, and Smarter
Prediction markets have entered the mainstream. In the coming year, they will become larger in scale, broader in coverage, and smarter with the intersection of crypto and AI, while also presenting new challenges that builders must collectively address.
First, there will be more types of contracts listed. This means that in the future, we will be able to obtain real-time odds not only for major elections or geopolitical events but also for various intricate outcomes and complex combinations of events. As these new contracts continuously disclose information and integrate into the news ecosystem (which is already happening), society will have to face a question: how do we balance the value of this information, and how do we design more transparent and auditable prediction systems?
Cryptographic technology can provide tools for this.
To cope with a larger volume of prediction contracts, we need new "truth alignment" mechanisms to advance contract settlement. The adjudication mechanisms of centralized platforms (Did a certain event happen? How to confirm?) are indeed important, but controversial cases like the Zelensky lawsuit market and the Venezuelan election market have exposed their limitations.
Therefore, to expand the scale and application value of prediction markets,
new decentralized governance mechanisms and LLM oracles will become important tools for resolving disputes and achieving truth.
The possibilities brought by AI are not limited to LLMs. AI agents can autonomously trade on prediction platforms, scan the world for signals, and seek short-term advantages. This helps us discover new ways of thinking and aids in predicting "what will happen next" (projects like Prophet Arena have already demonstrated early excitement in this area).
In addition to serving as queryable "senior political analysts," the emergence strategies of AI agents can even allow us to reverse-engineer the fundamental predictive factors of complex social events.
Will prediction markets replace polls? No, they will make polls better.
Poll data can even become input for prediction markets. As a political economist, I am most excited to see prediction markets and a healthy, diverse polling ecosystem operate together. But to achieve this, we need to leverage new technologies: AI can improve the survey experience; cryptographic technology can prove that respondents are real people rather than bots, leading to more innovation.
——Andy Hall, a16z crypto research advisor; Professor of Political Economy at Stanford University
The Rise of "Staked Media"
Traditional media models (especially the assumption of "objectivity") have shown cracks. The internet has allowed everyone to have a voice, and more and more industry players, practitioners, and builders are beginning to express their views directly to the public. Ironically, audiences often respect them not "despite their interests" but because they have interests.
The real change is not social media, but rather: cryptographic tools that enable people to make public, verifiable commitments.
As AI brings the barrier to content creation close to zero—any perspective, any identity (whether real or fictional) can be infinitely replicated—simply "saying something" is no longer sufficient to establish trust.
Tokenized assets, programmable lockups, prediction markets, and on-chain history provide a more solid foundation for trust:
Commentators can express opinions and prove they have "bet real money";
Podcast creators can lock up tokens to show they won't "pump and dump";
Analysts can tie predictions to publicly settled markets, thereby building auditable records.
This is what I refer to as the early form of "staked media": a new type of media that embraces the idea of "having skin in the game" and provides verifiable evidence.
In this model, credibility no longer comes from "pretending to be neutral," nor from "unsubstantiated claims," but from publicly verifiable stakes.
Staked media will not replace existing media but will complement the current ecosystem.
It provides a new signal: not "trust me, I am neutral," but "look at what risks I am willing to take, and you can verify whether I am telling the truth."
——Robert Hackett, a16z crypto editorial team
Crypto Provides New Primitives for the World Beyond Blockchain
For many years, SNARKs (succinct non-interactive arguments of knowledge) have been used almost exclusively in the blockchain space. The reason is simple: the cost of generating proofs is too high—potentially 1,000,000 times more expensive than executing the computation directly.
In scenarios where the overhead can be distributed among thousands of validators, this is worthwhile, but in other contexts, it is nearly impossible.
All of this is about to change.
By 2026, zkVM provers will reduce the overhead to about 10,000 times, with memory usage requiring only a few hundred MB: fast enough to run on mobile phones and cheap enough to deploy anywhere.
Why might 10,000x be a "magic number"? Because the parallel capabilities of high-end GPUs are about 10,000 times that of laptop CPUs.
By the end of 2026, a single GPU will be able to generate proofs in real-time that would otherwise require CPU execution.
This will unlock a long-standing vision in old papers: verifiable cloud computing.
If your workload is already running on cloud CPUs, due to low computational demands, lack of GPU capabilities, or historical reasons,
in the future, you will be able to obtain cryptographic proofs of computational correctness at reasonable costs.
The provers themselves are optimized for GPUs, and your code will not need to change.
——Justin Thaler, a16z crypto research team; Associate Professor of Computer Science at Georgetown University
About Future Building
Transactions Are Just "Waypoints," Not the Endpoint for Crypto Companies
Today, aside from stablecoins and a few core infrastructures, almost all well-run crypto projects have turned to trading businesses or are preparing to do so. If "all crypto companies eventually become trading platforms," what will the final landscape look like?
A large number of players doing the same thing will squeeze each other out, leaving only a few winners.
Those companies that pivoted to trading too early or too quickly may miss the opportunity to build more defensive and sustainable businesses.
I fully understand that founders are constantly exploring to make their financial models work, but chasing "seemingly immediate product-market fit (PMF)" also comes with costs.
Especially in the crypto space, the unique dynamics of token mechanisms and speculative culture can lead founders to more easily pursue "instant gratification," neglecting deeper product issues.
In a sense, this is a "marshmallow test." There is nothing wrong with trading; it is an important market function. But it does not have to be the endpoint.
Those founders who truly focus on the "product" part of PMF are often the ultimate winners.
——Arianna Simpson, a16z crypto general partner
When the Legal Framework Finally Aligns with the Technical Framework, Blockchain Can Unlock Its 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 have been extended and selectively enforced, forcing founders into a regulatory framework originally designed for "companies," not "networks."
For years, "reducing legal risk" has replaced "product strategy"; the position of engineers has been supplanted by lawyers.
This dynamic has led to many bizarre distortions:
Founders are told to avoid transparency;
Token distribution becomes legally arbitrary and unnatural;
Governance devolves into performance;
Organizational structures prioritize legal risk avoidance;
Tokens are forced to be designed without economic value and without business models;
Worse yet, projects that are less compliant with the rules often run faster.
But now, the legislative structure for the U.S. crypto market is closer to passing than ever, promising to eliminate these distortions next year.
Once passed, this legislation will: incentivize transparency; establish clear standards; replace today's "enforcement roulette" with clear, structured paths for fundraising, token issuance, and decentralization.
After the passage of the GENIUS Act, the growth of stablecoins will explode; and the changes brought by crypto market structure legislation will be even more profound—this time targeting the networks themselves.
In other words, this type of regulation will allow blockchain networks to operate as they were originally intended: open, autonomous, composable, trustlessly neutral, and decentralized.
——Miles Jennings, a16z crypto policy team; General Counsel
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