2026 Web3 Landscape: a16z Releases 17 Cryptocurrency Development Trends to Watch

In the recently concluded annual review, a16z compiled a heavyweight report from its multiple research teams. This report covers 17 trends and technological directions that will have a profound impact on the cryptocurrency and Web3 ecosystems. Let’s explore these cutting-edge perspectives together.

Upgrading the Payment System

Enhancement of Stablecoin Infrastructure

Last year, stablecoin trading volume reached $46 trillion, exceeding PayPal’s transaction volume by more than 20 times, nearly three times that of Visa, and rapidly approaching the level of ACH (Automated Clearing House in the US). Although single stablecoin transfers now cost less than 1 cent, the key channels connecting “digital dollars” with traditional financial systems are still not fully established.

A group of innovative companies is filling this gap. They enable cross-border payroll, merchant global payments, and real-time settlement scenarios by integrating local payment systems, utilizing QR codes, and employing real-time payment rails. As these channels improve, stablecoins will evolve from niche financial tools into the foundational layer of internet settlement infrastructure.

From Asset Tokenization to “Crypto Native” Direction

Traditional financial institutions are bringing US stocks, commodities, indices, and other assets on-chain. However, current tokenization often “looks like” traditional assets but lacks true essence—merely copying traditional asset logic without leveraging the unique advantages of the crypto ecosystem.

Perpetual contracts (Perps), as a synthetic form, offer deeper liquidity and more convenient leverage mechanisms. Especially, the “perpification” of emerging market stocks is expected to become a new trend. Meanwhile, in the stablecoin ecosystem, more projects will adopt “on-chain native issuance” rather than simple tokenization, which requires supporting on-chain credit infrastructure. The true development path is to enable debt assets to be issued natively on-chain, rather than being generated off-chain and then tokenized.

Modernization Dilemma and Breakthrough of Banking Ledgers

Traditional banks still operate on systems from decades ago—COBOL programming, batch file interfaces, mainframe architectures. While these systems have been market-tested, they hinder financial innovation. Upgrading these legacy systems can take months or even years, facing technical debt and regulatory complexities.

Stablecoins and on-chain asset tokenization provide bypass solutions. Financial institutions can create new products and serve new clients without rewriting core systems, using stablecoins, tokenized deposits, and bonds. This is a practical path to innovate under existing infrastructure constraints.

The Future of Value Flows

Evolution of “Internet as a Bank”

With the widespread adoption of AI agents and deeper transaction automation, the way value flows must keep pace. In a world driven by “intent” rather than “step-by-step operations,” capital must move as quickly as information.

Smart contracts can now complete global $1 transfers within seconds, but by 2026, new primitives (like x402) will make settlement programmable and reactive: agents can pay for data, GPU time, API calls in real-time, without invoices or batch processing. Prediction markets will settle in sync with event progress. When value can flow so freely, the payment layer will become a behavioral characteristic of the network, not just an independent operational layer. Financial infrastructure will integrate into the core of the internet, ultimately making the internet itself the financial system.

Democratization of Wealth Management

Personalized wealth management was once exclusive to high-net-worth clients. But with asset tokenization and AI-driven recommendations, low-cost active management is no longer a luxury.

By 2026, fintech platforms like Revolut, Robinhood, and centralized exchanges like Coinbase will leverage technological advantages to expand their markets. Meanwhile, DeFi tools like Morpho Vaults will automatically allocate assets to the most risk-adjusted, yield-optimized lending markets. Retail investors will replace fiat with stablecoins, and tokenized money market funds will substitute traditional financial products, gaining access to more private assets—including private credit, Pre-IPO companies, private equity. Tokenization makes these long-locked markets accessible while maintaining compliance.

AI and Agent Era

From “Know Your Customer” to “Know Your Agent”

In the AI agent economy, the bottleneck is no longer intelligence but identity. Currently, the number of “non-human identities” is 96 times that of human employees, yet these agents remain “ghosts”—lacking essential trust infrastructure.

KYA (Know Your Agent) emerges as a solution. Just as humans need credit scores to obtain loans, agents need cryptographic signatures as credentials to transact—linking agents with their operators, permissions, and responsibilities. Without this, merchants might block agents via firewalls. An industry that took decades to build KYC infrastructure now has only a few months to develop KYA.

AI-Enabled Academic Research

From the beginning to the end of the year, AI models have made significant leaps in supporting complex research. When models become “smart enough,” abstract commands can generate accurate answers, even independently solving the world’s most difficult math competitions.

This work style rewards interdisciplinary thinking and rapid reasoning—even if intermediate answers are full of “hallucinations.” A new workflow (agent-wrapping-agent) allows researchers to evaluate methodologies of previous-generation models and gradually filter out the best. However, this requires better model interoperability and attribution mechanisms—cryptocurrency can solve both, ensuring each model’s contribution is properly rewarded.

The “Invisible Tax” Impact on Open Networks

AI agents fetch data from ad-funded pages but systematically bypass these revenue streams, imposing an “invisible tax” on open networks. Existing licensing agreements for AI compensate content creators with “small patches,” but the income is far insufficient to offset traffic losses.

Solutions include next-generation sponsored content models, micro-attribution systems, or other innovative financing methods. The key is transitioning from static licenses to real-time compensation based on actual usage. This may involve blockchain-based nanosecond payments and complex attribution standards—automatically rewarding every information source that contributes to an agent’s success.

Privacy and Security

Privacy as a Competitive Edge for Cryptocurrencies

Privacy is a key feature driving the migration of global finance to blockchain, yet almost all existing chains lack it. Currently, most chains treat privacy as an add-on rather than a core design.

Privacy creates a unique network lock-in effect. In the era of cross-chain bridges, when all content is public, migrating assets between chains is easy; but private information is hard to bridge. Users face de-anonymization risks when entering or leaving privacy zones. For many new chains lacking differentiation, fee competition often results in zero-cost transfers, but privacy chains can build strong network effects. If a universal chain lacks mature ecosystems or killer apps, users have no reason to use or develop it—only privacy can dominate the entire market, forming a “winner-takes-all” dynamic.

The Future of Communication: Not Just Quantum-Resistant, But Decentralized

While Apple, Signal, WhatsApp have adopted quantum-resistant cryptography, they rely on private servers managed by single organizations—these servers are vulnerable to government shutdowns, backdoors, or forced data leaks.

The real solution is open communication protocols—trust no one. Through decentralized networks: no private servers, no single application, fully open-source code, state-of-the-art cryptography. In an open network, no individual, company, NGO, or government can seize communication capabilities. Even if an app is shut down, 500 new versions will appear the next day. When users own their information via private keys—like owning money—everything changes.

New Models for Data Access Control

Every AI model and automation system depends on data. But most data channels today are opaque and hard to audit. This is manageable for consumer apps but a major obstacle for finance and healthcare industries that require strict privacy protections—also the main barrier to tokenizing real-world assets.

The solution is “Secrets as a Service”: programmable, local data access rules; client-side encryption; decentralized key management. Executed on-chain, these ensure who can access data, under what conditions, and for how long. Coupled with data verification systems, “secrets” can become part of the public internet infrastructure, elevating privacy from application-layer patches to core infrastructure.

Cutting-Edge Technology and Governance

From “Code is Law” to “Norms are Law”

Recent DeFi security incidents involving audited, reputable protocols reveal a problem: current security standards are mainly heuristic, case-by-case assessments. For DeFi to mature, it must shift from a “patching flaws” approach to a design-layer attribute, upgrading from “best effort” to “fundamental.”

At the static/deployment layer, this means systematically proving global invariants rather than hand-selecting local invariants. AI-assisted proof tools are emerging to help write specifications, propose invariants, and handle much of the manual proof work. At the dynamic/deployment layer, these invariants can serve as “real-time guardrails”—the last line of defense. Guardrails are encoded as runtime assertions, requiring each transaction to satisfy them. This means we no longer assume all vulnerabilities will be discovered; instead, we enforce critical security properties, automatically rolling back violations. In practice, almost every past attack would trigger these checks. Thus, “code is law” evolves into “norms are law.”

Expansion and Intelligence of Prediction Markets

Prediction markets are now mainstream, but by 2026, their intersection with crypto and AI will drive larger, broader, and smarter markets—posing new challenges for creators.

First, the explosion in contract numbers means real-time prices will appear not only for elections or geopolitical events but also for diverse, complex, interconnected events. As these contracts integrate into news ecosystems, important social issues emerge: how to balance the value of this information, how to design them more transparently—cryptocurrency makes this possible. Handling more contracts requires new consensus mechanisms to verify authenticity. While centralized platforms are crucial, controversial cases like “Zelensky lawsuit market” and “Venezuela election market” expose their limitations. To resolve edge cases and help prediction markets expand into more useful applications, decentralized governance and LLM-based oracle systems can assist dispute resolution. AI opens new possibilities—automated agents betting based on real-time data, integrating new contracts, dynamically adjusting markets to agent behaviors. This makes prediction markets smarter, more responsive, enabling real-time risk assessment, automatic hedging, and AI-driven forecasting. But as scale grows, creators must address challenges like manipulation prevention, complex dispute resolution, and balancing transparency with privacy.

Cryptography Beyond Blockchain Applications

For years, SNARKs (Zero-Knowledge Proofs) mainly served blockchain because their computational cost was astronomical—proving a computation could require 1,000,000 times more work than executing it. By 2026, zkVM proof overhead will drop to about 10,000 times, with memory consumption down to a few hundred MB—sufficient to run on smartphones.

This 10,000x might be the magic number: high-end GPUs have parallel throughput roughly 10,000 times that of laptop CPUs. By the end of 2026, a single GPU will be able to generate proofs for CPU computations in real-time. This could unlock “verifiable cloud computing”: if you need to run CPU loads in the cloud (due to computational needs or legacy reasons), you can obtain cryptographic correctness proofs at reasonable costs. Proofs are optimized for GPUs; your code doesn’t need modification.

Business and Regulatory Outlook

Rise of “Staking Media”

The cracks in traditional media are evident. The internet empowers everyone to speak, and more operators, practitioners, and creators directly reach the public. Their views reflect their stakes, and ironically, audiences often respect them because of these stakes, not despite them.

The new is not just growth in social media but the cryptographic tools enabling people to make public, verifiable commitments. When AI makes generating infinite content (true or false, any viewpoint or persona) cheap and easy, mere rhetoric (human or bot) is insufficient. Tokenized assets, programmable locks, prediction markets, and on-chain history provide a more solid trust foundation. Commentators can present arguments and prove consistency (putting money where their mouth is). Podcasters can lock tokens to prove they won’t manipulate or “pump and dump.” Analysts can link predictions to publicly scored markets, creating auditable records. This early form of “staking media” won’t replace other media but will complement them, providing new signals: “Trust me not only because I claim neutrality but also because I bear the risk and you can verify my authenticity.”

Cryptocurrencies Must Evolve Toward a Truly Networked Nature

Over the past decade, the biggest challenge in building blockchain networks in the US has been legal uncertainty. Overly broad and selectively enforced securities laws have forced founders to operate within frameworks designed for “corporate” entities. For a long time, minimizing legal risk replaced product strategy; engineers had to yield to lawyers. This led to strange distortions: advice to hide transparency; token distribution becoming arbitrary; governance turning into performance; organizational structures optimized for legal protection. Tokens were designed to lack economic value to evade regulation. Ironically, crypto projects that ignore these principles often outperform honest actors.

But new regulatory frameworks for crypto markets—likely through government legislation—may eliminate these distortions within the next year. This would encourage transparency, establish clear standards, and replace “regulatory roulette” with structured, compliant fundraising, token issuance, and decentralized pathways. Since the post-GENIUS law, stablecoin adoption has exploded; the crypto market structure law will bring even bigger changes—this time for the network. In other words, such regulation will enable blockchain networks to operate as networks—open, autonomous, composable, trustworthy, neutral, and decentralized.

Core Insights

These 17 directions encompass comprehensive Web3 evolution—from payment infrastructure, asset tokenization, AI agent integration, privacy, to improved regulation. Notably, privacy as a competitive moat, stablecoins completing payment loops, attribution issues driven by AI agents, and more, are especially worth attention. Whether for developers, investors, or observers, the crypto ecosystem in 2026 will face unprecedented changes. This report reflects a16z’s deep thinking on industry development and hints at innovative directions that may emerge in the next phase.