Seventeen visions of the future of Web3: a16z Report for 2026

Leading venture capital firm a16z published this week its annual overview of key trends in the cryptocurrency ecosystem. Experts from various departments of the firm prepared an analysis of emerging solutions, technologies, and scenarios that will shape the blockchain landscape and decentralized finance in the coming year. Here are 17 observations worth the attention of every industry participant.

New Entry and Exit Channels for Digital Stablecoins

The stablecoin market has experienced an explosion: last year, transaction volume was estimated at $46 trillion. In comparison, this is over 20 times more than PayPal’s throughput or nearly 3 times more than the entire Visa system. We are rapidly approaching traditional clearing network volumes.

The issue lies in integration. Although sending stablecoins costs less than one cent and takes less than a second, connecting digital dollars with everyday financial channels remains a challenge. A new generation of startups is filling this gap — integrating stablecoins with local payment systems, using QR codes, real currencies, and international infrastructure. Simultaneously, global wallet layers and card-issuing platforms are developing, enabling stablecoin issuance at regular merchants.

These changes will open new opportunities: workers will receive cross-border wages in real-time; merchants — accept global dollars without a bank account; applications — settle value almost instantly with any user worldwide.

Cryptographically Native Tokenization of Real Assets

Traditional financial institutions are actively testing the transfer of stocks, commodities, and indices onto blockchains. The problem: current tokenization often imitates old structures instead of leveraging the capabilities inherent to the cryptographic ecosystem.

A more promising approach is using perpetual futures contracts. These contracts offer deep liquidity, intuitive leverage, and — according to experts — the best product-market fit among native derivative instruments. Especially interesting are emerging market stocks, where short-term options can offer greater liquidity than the spot market.

Meanwhile, as stablecoins enter mainstream use, more native debt issuance will appear instead of just tokenizing existing assets. Institutions will issue debt instruments directly on-chain — reducing operational costs, decreasing technical debt, and increasing accessibility for global participants.

Digital Dollars Drive Banking Modernization

The software used by traditional banks is a relic from decades ago. Mainframes programmed in COBOL, batch interfaces instead of APIs — this is the reality for most global financial institutions. Modernization is slow; adding features like real-time payments can take months or years.

Stablecoins offer a workaround. Instead of rebuilding outdated systems, institutions can build new products on blockchain — with stablecoins, tokenized deposits, and bonds. This allows them to innovate without dealing with multi-decade technical debt and regulatory complexity.

The result? New behaviors in the financial sector: traditional institutions can offer instant settlements and 24/7 markets without rewriting fundamental systems.

When AI Agents Watch: The Internet as Financial Infrastructure

As autonomous agents take on more functions without explicit user commands, value flows must adapt. Money must flow as quickly and flexibly as information.

Smart contracts can already settle dollars worldwide in a few seconds. By 2026, primitives like x402 will make agent-to-agent payments programmable and betozmashing: agents can instantly trade data, GPU time, or API calls — without invoices, reconciliation, or batch processing.

Predictive markets will settle in real-time. Prices will update, agents will trade, and settlement will occur globally within seconds — without intermediaries or centralized exchanges. When value can be pushed so flexibly, the banking system will become a layer of fundamental internet infrastructure. The internet will not just support the financial system — it will become the financial system itself.

Asset Management Available to Everyone

Personalized investment services have traditionally been reserved for wealthy clients. The cost? Prohibitive. But with tokenization of various asset classes and AI support, anyone can access active portfolio management — not just passive indexing.

By 2025, traditional finance increased exposure to cryptocurrencies. Now, platforms built specifically for “wealth accumulation” will emerge — not just “wealth preservation.” Fintechs and centralized exchanges will compete, leveraging their advanced infrastructure.

At the same time, DeFi tools such as advanced currencies and automated asset allocation will direct assets to the highest-yielding, risk-adjusted lending markets. Holding surplus in stablecoins instead of traditional currencies broadens earning opportunities. Retail investors gain access to previously unavailable assets — private loans, pre-IPO companies, private equity — through tokenization.

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

In an economy full of autonomous agents, the bottleneck is not intelligence but identity. In financial services, the number of “non-human identities” already exceeds human workers at a ratio of 96:1 — yet they remain unverified “ghosts.”

A key element is missing: KYA (Know Your Agent) — “know your agent.” Just as humans need credit scoring, agents will need cryptographically signed attestations to trade — linking the agent to its guardian, restrictions, and accountability.

Without this, vendors will block agents on firewalls. An industry that has built KYC infrastructure over decades now has only a few months to face the KYA challenge.

AI in Natural Scientific Discovery

Changes in AI model capabilities are dramatic. In January of this year, advanced models could not understand abstract workflows of scientists. By November, they could perform complex commands — often with correct results.

We increasingly see AI supporting real discoveries — especially in reasoning, where models directly assist in solving problems or even solve them themselves. However, this work is characterized by a new, polymathic style: the ability to speculate on relationships between ideas and quickly draw conclusions even from uncertain answers.

Paradoxically, using the model’s “hallucinations” — when the model is “sufficiently intelligent” — can lead to attribution errors but also open doors to discoveries. This requires a new approach: where a model layer helps researchers evaluate previous methods and gradually separate valuable insights from noise.

Such advanced collaborative systems will require better interoperability of models and mechanisms for recognizing and fairly rewarding each model’s contribution — here, cryptocurrencies can play a key role.

The Intangible Tax of Open Networks

The growth of AI agents imposes hidden costs on open networks, undermining their economic foundations. The problem: agents collect data from ad-funded sites — deriving users and convenience but neglecting revenue streams supporting content creation.

To prevent erosion of diversity that drives AI, we must implement technical and economic solutions. Current licensing agreements are inadequate — compensating creators only a fraction of the lost value.

A key change will be shifting from static licenses to real-time, usage-based compensation. This involves testing systems — perhaps using blockchain for nano-payments and complex attribution standards — that automatically reward everyone contributing to the success of an agent’s task.

Privacy as the Ultimate Competitive Advantage

Privacy is a key feature in the transition of global finance to blockchain — and is almost absent in existing networks. For most chains, privacy is an add-on; now, it can be sufficient to distinguish one blockchain from all others.

Privacy creates a network effect: bridging tokens between chains is trivial when everything is public. But bridging secrets? That’s a different matter. Moving from private to public zones always risks metadata exposure — time, transaction size, correlations.

Unlike many new, indistinguishable chains, privacy blockchains can have strong network effects. Without clear differentiation, almost no one has a reason to use them. When users are on a private chain, the cost of switching increases — they don’t want to risk exposure. This creates a “winner takes all” dynamic — and since privacy is essential for most real-world applications, a small number of private chains could dominate the entire market.

Communication: Quantum-Resistant Plus Decentralized

As the world prepares for quantum computers, major communication apps (Apple, Signal, WhatsApp) are ahead of others. The problem: each relies on private servers of a single organization — easy targets for governments wanting to shut them down, install backdoors, or compel data.

What if we have quantum cryptography but the state can shut down the server? Or the company holds the key? Or simply owns it?

Solution: open communication protocols without a trusted intermediary. Decentralized networks — without private servers, without a single app, fully open source, with the best cryptography.

In an open network, no single person, organization, or state can take away the ability to communicate. Shut down one app — 500 new ones will appear. Turn off one node — the blockchain and economic mechanisms will launch another. When people hold messages as they do money — with a private key — everything changes.

Secret as an Infrastructure Service

Behind every model, agent, and automation lies a dependency on data. Today, most channels — inputs and outputs for models — are opaque, variable, and unauditable. For some applications, this is acceptable, but finance, medicine, and asset tokenization require privacy of sensitive information.

The key question: who controls the data? How is it transferred? Who (or what) can see it?

Without access control, anyone wanting confidentiality must rely on centralized services — costly, difficult, and limiting. With autonomous agents, users and institutions need not “best efforts” but cryptographic guarantees.

Solution: “secret as a service” — a new technology offering programmable access rules for data; client-side encryption; decentralized key management. All enforced on-chain. Coupled with data verification systems, “secrets” become part of the fundamental infrastructure of the public internet — not just an app-level patch.

From “Code is Law” to “Specification is Law”

Recent hacks on DeFi protocols have targeted well-established protocols with strong teams and audits. This highlights a troubling reality: today’s security standards are mainly heuristic and considered on a case-by-case basis.

For DeFi to mature, security must shift from bug fixing to design properties. This means:

Statically (pre-deployment): systematic proof of global invariants instead of manual checks of selected ones. Teams will build AI tools to support proofing — helping write specifications, suggest invariants, taking over costly proof work.

Dynamically (post-deployment): invariants become actual “guardrails” — assertions during execution. Every transaction must satisfy them. If not — the system automatically reverts.

In practice, almost every historical attack would be stopped by such controls. Thus, “code is law” evolves into “specification is law”: new attacks must satisfy the same security properties — others are trivial or extremely difficult.

Predictive Markets: Bigger, Broader, Smarter

Predictive markets have entered the mainstream. In the coming year, combined with AI, they will develop on new levels — posing new challenges for creators.

More contracts will appear — access to prices not only for elections or geopolitical events but for complex, interconnected scenarios. This raises societal questions: how to balance information value? How to design more transparent markets?

To handle scale, new consensus methods for “truth” are needed. Centralized platforms are important but have limitations, as controversial cases show. Decentralized governance mechanisms and oracle systems based on large models can help.

AI opens new possibilities: agents automatically betting, synthesizing new contracts, dynamically adjusting to behaviors. Markets will become smarter, more reactive — unlocking applications like risk assessment, automatic hedging, AI-driven forecasts.

Growth of Media with “Skin in the Game”

Cracks in the traditional media model have been visible for some time. The internet gave everyone a voice — and more and more hosts speak directly to the public. Their opinions reflect their interests, and audiences often respect them for it.

The novelty is not the rise of social media but the emergence of cryptographic tools enabling public, verifiable commitments. As AI makes generating endless content cheap, relying solely on human words seems insufficient.

Tokenized assets, programmable locks, predictive markets, and on-chain history offer a more solid foundation of trust. Commentators can lock tokens, proving consistency. Analysts can link forecasts to publicly settled markets, creating auditable records.

This is “Staked Media”: media that not only adopts the “skin in the game” principle but provides proof. Credibility does not come from pretending to be impartial — it stems from holding a real stake, with transparent commitments.

Cryptography Surpasses Blockchain: SNARKs for Everyday Computations

For years, SNARKs — proofs that verify computations without re-executing them — were mainly a blockchain technology. The overhead was too high: proving could require a million times more work.

That is changing. By 2026, overhead will drop to about 10,000 times — a magic number, because high-end GPU parallel throughput is ~10,000 times higher than a laptop CPU. When GPUs can generate proofs for CPUs in real-time, it opens the vision from earlier works: verifiable cloud processing.

If you still need to run computations in the cloud, you will be able to get cryptographic proof of correctness at a reasonable cost. Proof generation is already optimized — your code does not need to be.

Trading Is Not the Goal — It’s a Stopover

Today, almost every successful crypto company (besides stablecoins and key infrastructure) has become or is becoming a trading platform. But when everyone does the same, attention shifts to a few big winners.

Companies rushing into trading too quickly lose the chance to build a more defensive business. While I sympathize with founders improving margins, chasing immediate product-market fit has its price.

This problem is especially visible in crypto, where the unique dynamics of tokens and speculation push founders toward rapid market saturation. Founders focusing on the “product” part of PMF may ultimately find greater success — a more resilient, durable business than just trading.

Unlocking the Full Potential of Blockchain Networks

Over the past decade, the biggest challenge for creators in the US was legal uncertainty. Securities law was extended selectively, forcing founders to operate within regulations designed for “companies,” not “networks.”

As a result, minimizing legal risk replaced product strategy. Engineers deferred to lawyers. The outcome? Strange distortions: founders were advised to avoid transparency; token distribution was arbitrary; governance was a show; organizational structures optimized for law.

Projects ignoring principles often outperformed honest ones. But new regulations on crypto market structure — with a higher chance of passing by government than ever before — could eliminate these distortions.

If adopted, the law will encourage transparency, establish clear standards, and replace “lottery enforcement” with structured financing, token issuance, and decentralization pathways. After the stablecoin law, its adoption exploded; market structure legislation will be an even greater change for networks.

Regulation will enable blockchain networks to operate like networks — open, autonomous, composable, reliably neutral, decentralized.