Greenfield 2026 Crypto Outlook: Ten Key Issues and Opportunities

**Source**: Greenfield

**Compiled by**: Zhou, ChainCatcher

The digital asset ecosystem is evolving in unexpected ways: new fundamental elements, behavioral patterns, and coordination tools are emerging one after another. What was considered experimental just a year ago may now have become foundational components. As investors, our responsibility is to closely monitor these changes and identify which emerging concepts can develop into long - lasting infrastructure and truly gain market recognition.

Last year, we shared our predictions for the development trends in the coming year. This year, we will take a different approach. Instead of claiming to predict the future, we aim to share our vision: a wish list consisting of ten ideas, problems, and products that we hope founders will set out to address in 2026.

Through these reflections, we can gain a deeper understanding of where the next wave of significant opportunities may arise—in infrastructure, Decentralized Finance (DeFi), and the consumer sector—and how the ever - changing regulatory landscape will shape the foundation of these opportunities.

## 1. Infrastructure - BuilderNet for Solvers

### Problem

Over 50% of "toxic - free" (i.e., low - risk) retail order flows on the EVM are processed through intent aggregators that leverage the solver model. However, solvers often encounter delays when integrating new routes. This is because fully understanding the logic of new routes, preventing rollbacks, and maintaining low simulation latency require tremendous efforts.

This creates a "chicken - and - egg" dilemma for many new Automated Market Makers (AMMs) (such as Uniswap v4 hooks). Solvers need existing order flows to integrate new liquidity sources, yet they themselves are the main entities responsible for routing most order flows. This hinders the innovation of AMMs. Hooks usually have to lobby large solvers for integration and even engage in under - the - table deals. In particular, v4 hooks offer an extensive design space where every invariant can be broken. Currently, only 4% of v4 trading volume flows through pools with hooks.

### Opportunity

Flashbots' BuilderNet coordinates independent block builder instances within Trusted Execution Environments (TEEs) to share order flows and facilitate MEV - boost enhancements. A similar concept can be applied to the solver market. In this scenario, solvers can coordinate and share information in a trustless manner. Such information includes intent order flows, Request for Quote (RFQ) integrations, analytical/liquidity metrics, and route integrations. They can also engage in collaborative solving, such as selling intent auctions through wholesale methods.

## 2. Infrastructure - High - Performance and Private Computing DePIN Combining Hybrid Cryptography and Hardware Security

### Problem

TEEs promise to deliver "private AI in the cloud". But recent side - channel attacks have shown that they can still lead to data leaks, especially in decentralized and permissionless environments. On the other hand, pure cryptography (such as MPC and FHE) is highly secure, but it is too slow and complex for most practical AI workloads. Currently, no platform can simultaneously provide TEE - level speed, cryptographic security guarantees, and a clear usage - based model pricing mechanism.

### Opportunity

The product in question is a secure AI runtime environment. By default, it runs models in a high - speed terminal environment (TEE). However, it can automatically route the most sensitive steps to small MPC clusters, while recording verifiable proofs of correct execution and usage metrics. Customers can benefit from cloud - like performance, audit - compliant privacy protection, and a built - in profit model for model providers. This is crucial for regulated industries and the expanding target audience. As businesses and consumers grow more dependent on AI, the exposure of sensitive data threatens IP ownership, which in turn endangers profitability and operational autonomy.

## 3. Infrastructure - Unified Stablecoin Liquidity Layer

### Problem

A stablecoin liquidity layer provides shared infrastructure for stablecoin trading and settlement across multiple blockchains. Instead of maintaining separate liquidity pools on each network, liquidity providers pool their funds to establish a unified reserve that is accessible to all chains. A coordination mechanism tracks the total balance and instructs local contracts to disburse funds when transactions occur. Liquidity is dynamically rebalanced to meet demands, ensuring consistent depth and pricing efficiency across all connected networks.

### Opportunity

This kind of infrastructure addresses one of the core inefficiencies in DeFi—the fragmentation of stablecoin liquidity. By integrating liquidity, the transfer and exchange of stablecoins become more capital - efficient, cost - effective, and predictable. This architecture can reduce slippage for traders and improve capital utilization for liquidity providers. It also serves as a universal settlement layer for payments, vaults, and stablecoin - based applications. It represents a foundational step towards building a frictionless cross - network financial infrastructure.

## 4. DeFi - Risk Management and Smart Underwriting

### Problem

Risk management remains a massive and unresolved issue in the DeFi space. There is a wide array of risk management methods, ranging from internal governance mechanisms within protocols to outsourcing risk management to specialized institutions.

### Opportunity

In the highly competitive cryptocurrency sector, it is not surprising that some institutions are willing to push the boundaries of risk. This is especially true when there is a lack of clear safeguards or frameworks to make these risks transparent to the broader market. One way to tackle these risks is to segment them more clearly. For example, structured layering or other mechanisms can be introduced to allocate risk exposure more precisely among participants. Historically, effective risk pricing and allocation have been challenging due to limited historical data, weak trust frameworks, and inadequate risk monitoring infrastructure, resulting in high costs.

Nevertheless, tools are constantly improving, confidence in DeFi is growing, and on - chain risk assessment capabilities are becoming more robust. This is gradually narrowing the gap between yield - seekers and those willing to take on specific risks. We hope to see more experiments focused on building risk mitigation systems across DeFi ecosystems. Additionally, the absence of industry - wide risk scoring standards and the existence of inter - protocol dependencies (often hidden within complex code) are also problematic. This creates an opportunity for the emergence of native DeFi entities that provide real - time on - chain risk scoring.

## 5. DeFi - Transparent Market - Making Protocols

### Problem

Market Maker (MM) protocols are among the most opaque and obscure components in the industry, with few of their actual terms made public. Many token project teams lack understanding and control over these transactions. Consequently, they end up overpaying for market - making services due to insufficient market awareness. They also tend to distribute more tokens than necessary and spend a great deal of time figuring out how to secure optimal market - making deals. To some extent, this is a social coordination problem. Investors, exchanges, and regulators can demand greater disclosure, but coordination remains extremely difficult.

### Opportunity

We believe that innovation can enhance the efficiency of this market. A simple aggregated front - end platform would be highly valuable. On this platform, project teams and market makers can post trading quotes and the parameters they are willing to meet. Coinwatch has already improved the transparency of market - making activities by embedding API keys in TEEs, enabling project teams to track the actions of their market makers. Furthermore, the combination of zkTLS and staking mechanisms can enforce certain behaviors consistently, especially for market makers with weak brand influence. For instance, if the bid - ask spread (or any other metric) exceeds a specific threshold, the staked amount can be deducted.

## 6. DeFi - DeFi Robo - Advisor 2.0 (LVR Capture)

### Problem

Current automated investment tools are unable to capture on - chain microstructure alpha returns on a large scale.

### Opportunity

Leveraging LVR to seize opportunities in AMMs, such as batch auctions, solver rebalancing, and dynamic fees, can allow arbitrage to generate returns for investment portfolios while maintaining balanced asset allocation ratios. (Note: If you explicitly aim to rebalance your portfolio, impermanent loss is a feature rather than a flaw.) This could function like a DeFi robo - advisor that converts arbitrage into returns. Tokenized Real - World Asset (RWA) funds/ETFs, including AAA - rated fixed - income funds, money market funds, and S&P 500 index funds, are growing rapidly. They complement crypto - native investable assets like BTC and staked ETH.

Account abstraction enables a streamlined user experience. Strategies enforced by smart contracts provide transparent risk control, and compliant packaging offers regulated yield - bearing tokens. Time - tested infrastructure, coupled with optional insurance coverage, delivers state - of - the - art security. Asset allocators gain automatically rebalanced portfolios, and traders gain access to liquidity. Smart contracts enable a disintermediated win - win situation. All the necessary components are already in place; what is needed is someone to assemble them for large - scale implementation.

## 7. Consumer - Facing - LLM ⇋ Prediction Market Interface

### Problem

Prediction markets have been widely adopted, and new markets are emerging continuously. However, the problem of discovery persists. Currently, users either browse the front - end interfaces of these prediction markets to find suitable ones or use external aggregators. Most of these discovery processes rely on manual filtering, which is time - consuming and labor - intensive. There is no intuitive way for users to directly express their predictions (e.g., "Team A will win") and take corresponding actions based on them. As a result, most potential bettors never translate their opinions into actual on - chain bets.

### Opportunity

The discovery challenge in prediction markets can be solved through an LLM - based interface. We believe a chat - like interface that can parse users' predictions and route them to the optimal on - chain markets will greatly reduce user experience friction and significantly boost participation. As more predictions drive increased liquidity, prediction markets will become far more dominant than they are now.

## 8. Consumer - Facing - Scaling On - Chain Capital Formation

### Problem

On - chain fundraising tools (such as Echo.xyz, pump.fun, and Zora) have proven the effectiveness of community - driven on - chain fundraising models. Yet, current participants are mainly limited to crypto - native users. It is now time for these models to expand beyond the crypto - native user base and enter the mainstream market through various distribution channels.

### Opportunity

Coinbase's acquisition of Echo is a first step in this direction. Next, we will witness a major advancement in on - chain capital formation: the integration of these core functions into mass - market platforms. Imagine integrating on - chain token/equity issuance infrastructure into applications like Revolut, Nubank, or Kickstarter as a white - label solution. This would grant access to hundreds of millions of users worldwide. It would unlock massive new capital pools and extend the proven fundraising models beyond niche token buyers.

## 9. Consumer - Facing - Cryptocurrency Discovery Layer

### Problem

The cryptocurrency space still lacks a unified landing page or search engine. Existing tools have a narrow scope. This forces users to rely on Crypto Twitter and scattered forums for information. No platform integrates all relevant data—prices, on - chain metrics, news, social trends, yields, governance updates, popularity, and market sentiment—in one place. This fragmentation means that most participants today need to use a complex set of specialized tools to stay updated on the latest developments in the cryptocurrency sector.

### Opportunity

Aggregation in the cryptocurrency space has always been fragmented, and no one has yet solved the discovery problem. We see an opportunity to build a comprehensive AI - driven landing page—a true "Google for cryptocurrencies". This page would integrate on - chain data, news feeds, and social signals into a coherent search and discovery stream. Securing this position would lock in early adopters and new entrants. As cryptocurrency adoption grows, this would create a strong distribution moat.

## 10. Regulation - Clear Protocol Rules and Open Banking Access

Clearly, this is a challenge that no single protocol can address alone. It requires the coordinated efforts of the entire ecosystem. Given that regulatory clarity is crucial for everything we will build in the future, we have included this on our wish list as a common goal for the entire industry.

### Problem

Despite significant progress, regulatory frameworks still play a vital role in shaping the growth trajectory of the next phase of the cryptocurrency industry. Decentralized protocols still lack clear and applicable rules. The United States has not clearly defined when a token ceases to be a security. The European Union also has no clear decentralization standards under the MiCA framework. Frameworks designed for intermediaries impose unreasonable burdens on decentralized systems. They create legal uncertainties regarding protocol design, token structures, and ecosystem participation.

At the same time, due to the punitive 1250% risk weight assigned to most digital asset exposures under Basel III, regulated financial institutions, especially banks, are effectively excluded from the cryptocurrency space. This prevents banks from investing, providing liquidity, or supporting the development of the ecosystem. Ambiguous decentralization rules and restrictive prudential standards have collectively led to market fragmentation and reduced liquidity. They also make it difficult for both protocols and institutions to participate with confidence.

### Opportunity

Clear and globally consistent regulatory standards will unlock innovation and encourage institutional participation. For decentralized protocols, simple and transparent standards—such as the maturity test in the U.S. Clarity Act—will ultimately provide teams with the certainty they need. This allows them to design structures that align with their risk profiles and comply with relevant regulations. Europe could follow suit by adopting practical decentralization thresholds instead of vague or overly complex tests.

At the institutional level, the ongoing reassessment of Basel III and the U.S. proposal to differentiate the regulation of stablecoins reflect a growing recognition that existing rules do not match actual risks. Updating prudential standards will enable banks to hold digital assets, participate in DeFi, and provide new liquidity channels. Overall, these reforms will collectively establish a regulatory foundation. This foundation will support borderless decentralized innovation, attract institutional capital into the ecosystem, and expand access to global liquidity without compromising consumer protection.

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