Zcash is Just the Beginning, How Will a16z Redefine the Privacy Narrative in 2026?

Privacy becomes a foundational competitive moat in crypto, with privacy chains creating strong network effects and high migration costs, reshaping value distribution.

Decentralized messaging must eliminate private servers to ensure ownership and resilience, transcending encryption to prioritize open protocols and user-controlled identity.

“Secrets-as-a-service” is proposed as core infrastructure, offering programmable data access, client-side encryption, and decentralized key governance for secure, compliant innovation.

he surge of Zcash in 2025 has reignited the privacy narrative within the crypto industry. Often, we only see rising sentiment and capital inflows, with many likely believing this is just a temporary wave of emotion, lacking conviction in the sustainability of the narrative itself. a16z crypto’s latest report, “Privacy trends for 2026,” attempts to reframe the privacy discussion within the context of infrastructure and long-term evolutionary logic. By gathering collective observations from several seasoned crypto industry practitioners, the article outlines their judgments on “how privacy will shape the next phase of the crypto ecosystem” across multiple dimensions, from decentralized communication and data access control to security engineering methodologies.

1. Privacy Will Become the Most Important “Moat” in Crypto This Year

Privacy is one of the key functions for the global financial system’s transition on-chain; simultaneously, it is a function severely lacking in almost all blockchains today. For most chains, privacy has long been an afterthought. But now, “privacy” alone is enough to create a substantial distinction between one chain and all others.

Privacy brings an even more important point: chain-level lock-in effects—or, if you prefer, the “privacy network effect.” Especially in a world where competing solely on performance is no longer sufficient to win.

Thanks to cross-chain bridge protocols, migrating between different chains is almost costless as long as all data is public. But once privacy is involved, the situation changes completely: Cross-chain token transfers are easy; cross-chain “secret” transfers are extremely difficult. Operating outside the privacy zone always carries the risk of identity inference by monitors through on-chain data, mempool, or network traffic. Whether switching from a privacy chain to a public chain, or between two privacy chains, a large amount of metadata is leaked, such as transaction timing, size correlations, etc., making users easier to track.

Compared to new public chains that lack differentiation and whose fees are likely to be compressed to near zero in competition (block space is essentially becoming a commodity), blockchains with privacy capabilities can form stronger network effects. The reality is: If a “general-purpose” blockchain lacks a thriving ecosystem, killer applications, or asymmetric distribution advantages, there is almost no reason for users to use it, let alone build on it and remain loyal.

In a public chain environment, users can interact very easily with users on other chains—it doesn’t matter which chain they join. But on a privacy chain, the user’s choice becomes crucial because once they enter a privacy chain, they are less willing to migrate and risk identity exposure. This mechanism creates a winner-takes-all (or at least winner-takes-most) dynamic. And since privacy is necessary for most real-world application scenarios, ultimately, a handful of privacy chains may control the majority of value activity in the crypto world.

— Ali Yahya (@alive_eth), General Partner, a16z crypto

2. The Key Question for Messaging Apps This Year Isn’t Just Quantum Resistance, But Decentralization

As the world prepares for the era of quantum computing, many messaging apps built on encryption (like Apple, Signal, WhatsApp) are already ahead and doing quite well. But the problem is, all mainstream communication tools still rely on private servers run by a single organization. And these servers are the easiest targets for governments to shut down, implant backdoors, or compel to hand over private data.

If a country can directly shut down the server; if a company holds the keys to the private server; or simply because a company owns the private server—then what’s the point of even the strongest quantum encryption?

Private servers inherently require users to “trust me”; the absence of private servers means “you don’t have to trust me.” Communication doesn’t need a single company in the middle. Messaging systems need open protocols that let us trust no one.

The way to achieve this is to decentralize the network entirely: no private servers, no single app, completely open-source code, and top-tier encryption—including encryption resistant to quantum threats. In an open network, no single individual, company, non-profit, or country can deprive us of the ability to communicate. Even if a country or company shuts down one app, 500 new versions will appear the next day. Even if one node is shut down, new nodes will immediately replace it—mechanisms like blockchains provide clear economic incentives.

When people control their messages—through private keys—just like they control their money, everything changes. Apps can come and go, but users always hold their messages and identity; even without the app itself, end-users can still own their messages.

This goes beyond “quantum resistance” and “encryption”; it’s about ownership and decentralization. Without either, what we’re building is an encryption system that “cannot be cracked, but can still be shut down with one click.”

— Shane Mac (@ShaneMac), Co-founder and CEO, XMTP Labs

3. “Secrets-as-a-Service” Will Become Core Privacy Infrastructure

Behind every model, agent, and automated system lies a fundamental dependency: data. But most current data pipelines—whether data fed into models or data output by models—are opaque, mutable, and unauditable.

This might be acceptable for some consumer applications, but in industries like finance and healthcare, users and institutions often have strong privacy requirements. This is also becoming a major obstacle for institutions currently advancing the tokenization of real-world assets.

So, how do we enable secure, compliant, autonomous, and globally interoperable innovation while protecting privacy?

There are many solution paths, but I want to focus on data access control: Who controls sensitive data? How does data flow? And who (or what system) can access this data under what conditions?

In the absence of data access control, any entity wishing to maintain data confidentiality currently must rely on centralized services or build custom systems themselves—which is time-consuming, expensive, and severely hinders entities like traditional financial institutions from fully unlocking the potential of on-chain data management. And as autonomous agent systems begin to browse, trade, and make decisions independently, users and institutions across industries need cryptographic-level deterministic guarantees, not “best-effort trust.”

This is precisely why I believe we need “secrets-as-a-service”: A new type of technical architecture that provides programmable, native data access rules; client-side encryption; and decentralized key management mechanisms that enforce on-chain “who can decrypt what data, under what conditions, and for how long.”

When these mechanisms are combined with verifiable data systems, “secrets” themselves can become part of the internet’s foundational public infrastructure, no longer just an afterthought patched onto the application layer—making privacy truly underlying infrastructure.

— Adeniyi Abiodun (@EmanAbio), Co-founder and Chief Product Officer, Mysten Labs

4. Security Testing Will Evolve from “Code Is Law” to “Specification Is Law”

The multiple DeFi hacks last year did not target new projects, but rather protocols with established teams, multiple rounds of audits, and years of operation. These incidents highlight a troubling reality: Current mainstream security practices still heavily rely on rules of thumb and case-by-case judgment.

To achieve true maturity this year, DeFi security must shift from “vulnerability pattern recognition” to “design-level property guarantees,” and from “best-effort” to “principled methodology”:

In the static / pre-deployment phase (testing, auditing, formal verification), this means no longer verifying only a few selected local properties, but systematically proving global invariants. Currently, multiple teams are building AI-assisted proof tools that can help write specifications, propose invariant hypotheses, and take on the historically extremely expensive manual proof engineering work.

In the dynamic / post-deployment phase (runtime monitoring, runtime constraints, etc.), these invariants can be transformed into real-time guardrails, serving as a last line of defense. These guardrails will be directly encoded as runtime assertions that every transaction must satisfy.

This way, we no longer assume “all vulnerabilities have been found,” but instead enforce critical security properties at the code level, with any transaction violating these properties being automatically rolled back.

This is not just theoretical. In fact, almost all attacks to date would have triggered one of these checks during execution, potentially directly aborting the attack. Therefore, the once-popular “code is law” philosophy is evolving into “specification is law”: even novel attack vectors must satisfy the security properties that maintain system integrity, and the final viable attack surface is compressed to a very small or extremely difficult-to-execute space.

— Daejun Park (@daejunpark), Engineering Team, a16z

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〈Zcash is Just the Beginning, How Will a16z Redefine the Privacy Narrative in 2026?〉這篇文章最早發佈於《CoinRank》。