Key Evolution of the 2026 Crypto Ecosystem: Paradigm Shift from Infrastructure to Applications

Cryptocurrency is experiencing a critical turning point from edge innovation to mainstream financial infrastructure. This article outlines the core development directions of the crypto industry by 2026, covering four major areas: stablecoins, smart proxies, privacy protection, and emerging applications.

Stablecoins and On-Chain Finance: From Edge Tools to Settlement Layer Infrastructure

Bridging the Gap Between Reality and Digital

Last year, stablecoin transaction volume reached $46 trillion, exceeding PayPal’s transaction volume by over 20 times, nearly three times that of Visa, and approaching the scale of the U.S. ACH network. On the blockchain, stablecoin transfers can be completed within 1 second, with fees below one cent.

The question is: how to seamlessly connect this highly efficient system with traditional financial infrastructure used daily? New-generation startups are filling this gap by using cryptographic verification technology, regional payment networks, QR code systems, and real-time payment features to connect stablecoins directly with local banking systems. These innovations will ultimately form a truly interoperable global digital wallet layer and card issuance platform.

As these entry and exit channels improve, a new business logic begins to emerge: cross-border workers can receive salaries in real time, merchants can accept global stablecoins without bank accounts, and payment apps can settle value instantly with global users. Stablecoins will evolve from niche financial tools to the foundational settlement layer of the internet.

The True Potential of RWA: Native Crypto Thinking, Not Just Tokenization

Traditional financial institutions are keen to migrate US stocks, commodities, and indices onto the blockchain. However, most asset tokenization schemes remain superficial and fail to fully leverage the native properties of crypto.

In contrast, synthetic products like perpetual contracts offer deeper liquidity and are easier to implement. Perpetual contracts have an easy-to-understand leverage mechanism and have proven to be the highest product-market fit among crypto-native derivatives. Emerging market stocks are especially suitable for perpetual contract formats (some stocks’ zero-option markets even surpass spot market liquidity).

This is essentially a choice between “perpetual contracts” and “asset tokenization.” Regardless, 2026 will see more RWA innovations rooted in crypto-native thinking rather than passive tokenization transplantation.

The stablecoin trend is similar: simple tokenization has limited significance. The real opportunity lies in native issuance. Although stablecoins lacking credit infrastructure resemble narrow banks (holding only ultra-safe, specific liquid assets), long-term they will not become the backbone of on-chain economy.

New asset managers and curation protocols are beginning to issue asset-backed loans on-chain. The key change is: loans should originate natively on-chain, rather than being tokenized after off-chain initiation. On-chain issuance can reduce loan management costs, backend operational expenses, and improve accessibility. Compliance and standardization are challenges, but builders are already advancing.

Bank Software Upgrades and Payment Innovation Cycles

Most traditional banking software systems are outdated. Core systems mostly run COBOL code on mainframes, communicating via batch files rather than APIs. Adding real-time payment features can take months or even years.

This is precisely where stablecoins add value. In recent years, stablecoins have found product-market fit; now, traditional financial institutions are adopting them at unprecedented levels. Stablecoins, tokenized deposits, on-chain government bonds, and bonds enable banks, fintechs, and financial institutions to develop new products and serve new customers without rewriting decades-old legacy systems. This opens new paths for institutional innovation.

Rebuilding the Economy and Infrastructure in the Era of Smart Proxies

From “Know Your Customer” to “Know Your Proxy”

As AI proxies emerge at scale, bottlenecks shift from intelligence to identity verification. In financial services, “non-human identities” are already 96 times the number of human employees, yet these identities remain intangible.

The missing critical infrastructure is KYA(Know Your Agent): proxies need cryptographic signatures as credentials to execute transactions, binding the proxy to its authorized entity, operational limits, and responsibilities. Until this mechanism is perfected, merchants will continue to block proxies at firewalls. Decades of KYC infrastructure now need to address KYA issues within months.

AI-Assisted Research and Nested Proxy Systems

From the perspective of mathematical economists, early 2025, it was difficult for AI to understand complex research workflows; but by November, it could interact like guiding a PhD student, sometimes even providing novel, accurate answers.

AI’s application in reasoning is especially remarkable—current models can directly assist scientific discovery and even autonomously solve Princeton math competition problems.

This requires a new AI workflow: not just interaction between individual proxies, but nested proxy models—using multi-layered models to help researchers evaluate early model answers and gradually refine valuable content. This approach has been used in paper writing, patent searches, art creation, and even (unfortunately) discovering new smart contract attack vectors.

Implementing such nested research systems requires better interoperability between models and mechanisms to identify and fairly compensate each model’s contribution. Cryptography can solve both core issues.

The “Invisible Tax” of Open Networks and Real-Time Compensation

The rise of AI proxies is imposing an invisible tax on open networks. AI proxies extract data from content-layer websites (content layer) to provide convenience to users, while systematically bypassing revenue channels that sustain content creation (like ads and subscriptions).

To prevent erosion of open networks and protect content diversity that fuels AI, large-scale deployment of technical and economic solutions is needed. Existing AI licensing agreements have proven to be temporary remedies, often compensating content providers only a small fraction of revenue lost due to AI-driven traffic declines.

The key shift is moving from static licensing to real-time, usage-based compensation. This will require testing and deploying related systems, possibly using blockchain-enabled nano-payments and precise traceability standards to automatically reward entities providing information for AI proxies.

From Step-by-Step Instructions to Automated Payment Flows

As AI proxies proliferate and more business activities occur automatically in the background rather than through user clicks, the way value flows must change.

In an intent-driven rather than step-driven world, AI proxies can identify needs, fulfill obligations, or trigger outcomes to mobilize funds. The flow of value must be as fast and free as today’s information.

Smart contracts can settle global USD payments within seconds. By 2026, new primitives like x/402 will make settlement programmable and reactive: proxies can perform instant permissionless payments for data, GPU compute, or API calls, without invoices, reconciliation, or batch processing.

Software updates from developers will include built-in payment rules, restrictions, and audits, without integrating with fiat currency, merchant onboarding, or financial institutions. Prediction markets can self-settle in real time as events unfold, with dynamic fee rates, free trading by proxies, and global payments settled within seconds—completely without custodians or exchanges.

Once value can flow this freely, the “payment flow” will no longer be a separate operational layer but part of network behavior: banks become internet infrastructure, assets become infrastructure. When funds become routable information packets on the internet, the network will not only support the financial system but become the financial system itself.

Democratization of Wealth Management and Intelligent Asset Allocation

Traditionally, customized wealth management has been limited to high-net-worth bank clients. Providing personalized advice and cross-asset allocation is complex and expensive.

But with more asset classes tokenized, accessible via crypto channels, combined with AI-driven personalized strategies and collaborative systems, these strategies can be executed instantly and rebalanced at low cost. This surpasses robo-advisors—now everyone can access proactive portfolio management rather than just passive management.

By 2025, traditional financial institutions will have increased their crypto exposure (via direct investments or ETPs). But this is just the beginning. By 2026, platforms designed for “wealth growth” rather than just “wealth preservation” will emerge.

Fintechs like Revolut, Robinhood, and centralized exchanges like Coinbase will leverage their tech stacks to compete for market share. Meanwhile, DeFi tools like Morpho Vaults can automatically allocate assets to the highest risk-adjusted yield lending markets.

Maintaining liquidity in stablecoins rather than fiat, investing in RWA money market funds instead of traditional funds, can further enhance yields. Finally, retail investors will find it easier to invest in less liquid private market assets like private credit, pre-IPO companies, and private equity. Tokenization helps unlock these markets’ potential while meeting compliance reporting requirements.

As the balance of asset classes in portfolios gradually tokenizes (risk shifting from bonds, stocks to private and alternative investments), portfolios can automatically rebalance without fund transfers.

Privacy and Security: From Defense to Proactive Design

Privacy will become the strongest moat of the crypto industry

Privacy is a key requirement for global blockchain financial operations, yet it is almost absent in existing blockchains. For most, privacy is an afterthought feature. But today, privacy itself can distinguish a blockchain.

More importantly, privacy creates on-chain lock-in effects—namely privacy network effects. When all information is public, cross-chain migration is easy; but when private information is involved, the situation changes completely: tokens are easy to bridge, secrets are hard to bridge. Moving in and out of private zones involves risks of identity discovery when monitoring blockchains, mempools, or network traffic. Cross-bridging between private and public chains, or even between two private chains, can leak transaction timing and size-related metadata, facilitating tracking.

Compared to indiscriminate new homogeneous chains (fees approaching zero due to competition), privacy blockchains tend to form stronger network effects. The fact is: “general-purpose” public chains lacking vitality, killer apps, or distribution advantages lack reasons for users or developers to use them. When using public chains, users can easily transact with others; chain choice is irrelevant. But when using private chains, chain choice is critical—joining one chain reduces migration options, increases privacy leakage risk, leading to a “winner-takes-all” scenario.

Because privacy is crucial for most real-world use cases, a few privacy chains can dominate the entire crypto market.

Future communications must be quantum-resistant and decentralized

As the world prepares for the quantum era, cryptography-based communication apps like Apple iMessage, Signal, WhatsApp are leading the way. But the problem is: all mainstream communication apps rely on trusted private servers operated by a single organization.

These servers are vulnerable targets for government shutdowns, backdoors, or secret data requests. If a country can shut down a person’s server, or a company controls private keys or even owns the server itself, what use is quantum cryptography?

Private servers require trust in “trust me”; no private servers mean “you don’t need to trust me.” Communications should not depend on corporate intermediaries. They should be based on open protocols, trustless by design. This is achieved through network decentralization: no private servers, no reliance on a single app, fully open-source, and incorporating the best cryptography(including quantum resistance).

In open networks, no individual, enterprise, nonprofit, or country can deprive us of communication. Even if a country or company shuts down an app, within a day, 500 new versions will appear. Even if nodes go offline, blockchain-based economic incentives will immediately promote new nodes. When people can own their information via private keys as they own money, everything changes. Apps can come and go; users always control their data and identities; end users can truly own their information even if they do not own the app itself.

This is not just about quantum-proofing and cryptography; it’s about ownership and decentralization. Without either, we are only building seemingly unbreakable cryptosystems that can still be shut down at any time.

Making privacy a service

Behind every model, proxy, and automation process is a simple element: data. But today, most data channels(in and out of models) are opaque, volatile, and hard to audit.

This may be acceptable for some consumer applications, but for finance, healthcare, and many other industries and users, enterprises must protect sensitive data privacy. This is also a major obstacle for many institutions tokenizing RWA assets.

How do we advance secure, compliant, autonomous, and globally interoperable innovation while protecting privacy? Many approaches exist, but the key is data access control: who controls sensitive data? How does it flow? Who(or what) can access it?

Without data access control mechanisms, users who want data confidentiality can only trust centralized platforms or build custom systems. This is costly, time-consuming, and hinders traditional financial institutions from fully leveraging on-chain data management advantages.

As intelligent proxy systems begin to autonomously navigate, trade, and make decisions, all users and institutions across industries will need cryptographic verification mechanisms rather than “trust-but-verify” models. This is the value of “privacy as a service”: providing programmable native data access rules, client-side encryption, and decentralized key management, precisely controlling who can decrypt what data, under what conditions, and within what timeframes—all executed on-chain.

Combined with verifiable data systems, privacy-preserving data management will become a core component of internet infrastructure, not just an application-layer patch, making privacy a true foundational infrastructure.

From “Code is Law” to “Rules are Law”

Recently, several verified DeFi protocols have been hacked despite having strong teams, rigorous audits, and years of stable operation. This highlights an uncomfortable reality: current industry security standards are still largely based on case-by-case and experiential judgment.

For DeFi security to mature, it must shift from vulnerability pattern approaches to design principles, from “do your best” to “principle-based.”

In the static pre-deployment phase (testing, auditing, formal verification), this means verifying global invariants rather than just manually chosen local invariants. Multiple teams are developing AI-assisted proof tools to help draft technical specifications, propose invariant hypotheses, and significantly reduce manual work that would otherwise make verification prohibitively costly.

In the dynamic post-deployment phase (runtime monitoring, runtime enforcement), these invariants become dynamic barriers—the last line of defense. These barriers are directly encoded as runtime assertions, and every transaction must satisfy them. This way, we no longer assume all vulnerabilities can be discovered; instead, enforce key security properties in code, with any violating transaction automatically reverted.

This is not just theoretical. In practice, almost all exploit attacks trigger one of these security checks during execution, potentially preventing the attack. Therefore, the popular “code is law” paradigm has evolved into “rules are law”: even new attack vectors must comply with security properties that maintain system integrity, making remaining attack methods trivial or difficult to execute.