Written by: Aadharsh Pannirselvam, Tommy Hang, Eskender Abebe, Katie Chiou, Danny Sursock, Dmitriy Berenzon, Ash Egan, Archetype

Compiled by: JW, Techub News

Looking ahead to 2026, the Archetype team is focusing on trends, forces, and structural changes.

Building Application Chains Finally Makes Sense

The core judgment is quite clear: truly competitive blockchains will increasingly be created for "specific applications."

It is not about having a general-purpose chain first and then awkwardly adapting various applications; rather, it is about designing and building around the needs of the application itself from the very beginning, and continuously adjusting. Such chains will perform very strongly in the coming year.

The reason is that the new wave of developers, users, institutions, and funds entering the crypto world is fundamentally different from the early days. They have clear cultural preferences and very specific requirements for user experience, no longer prioritizing abstract value propositions. In reality, these needs can sometimes be met by existing infrastructure, but more often than not, they cannot.

Take applications like Blackbird and Farcaster, which significantly reduce the perception of crypto and target ordinary users. Some design choices that were considered "unacceptable" three years ago, such as centralized node deployment, single sequencers, and even fully customized data systems, have now become reasonable solutions for enhancing user experience.

This is even more true for trading or stablecoin-related applications like Hyperliquid and GTE. The competition among these systems essentially depends on latency, matching efficiency, and price quality. In scenarios where milliseconds can determine success or failure, many "principled issues" naturally give way to the experience itself.

Of course, not all applications are suited to this path.

An important counterbalancing factor that is forming is the noticeable rise in privacy demands from institutions and retail investors. The user groups, usage scenarios, and risk preferences faced by different applications vary greatly, and therefore, the infrastructure they rely on should also present different forms.

The good news is that today, customizing a chain for an application is no longer a high-barrier project. Compared to two years ago, this process now resembles assembling a custom computer.

You can choose to configure every component entirely on your own or make adjustments based on mature solutions. Models provided by companies like Digital Storm or Framework essentially allow for replacing or streamlining certain modules based on already validated combinations, ensuring performance while avoiding unnecessary complexity. This approach brings higher modularity and controllability. Applications can retain only the components they truly need while ensuring the overall system is stable and scalable.

When foundational modules like consensus mechanisms, execution layers, data storage, and liquidity become freely combinable and adjustable primitives, the applications themselves will naturally form highly differentiated "chain forms." These forms will continuously reflect their understanding of user experience and serve very specific target groups.

This differentiation is akin to different types of computing devices: ToughBooks, ThinkPads, desktops, or MacBooks. They may look very different, but they still share a lot of common logic at the underlying level. The key is that each component becomes an adjustable parameter rather than a limiting constraint. From Circle's acquisition of Informal Systems' Malachite, a trend can be clearly seen: the emphasis on sovereign control over dedicated blockchain space is becoming a consensus.

In the coming year, we are likely to see roles akin to "HashiCorp or Stripe Atlas in the blockchain space," with teams like Commonware and Delta providing standardized primitives and default configurations, allowing applications to more easily define and control their chain resources.

Ultimately, this model will enable applications to truly achieve one thing: to directly own their blockchain space and cash flow, turning the chain itself into a part of their long-term competitive advantage.

Prediction Markets Will Continue to Evolve

In this cycle, prediction markets are undoubtedly one of the most watched application categories.

As the weekly trading volume of all crypto prediction market platforms surpasses $2 billion, this sector has proven through data that it is no longer just a niche experiment.

With the rise in popularity, a large number of projects have emerged attempting to replicate, replace, or even directly challenge leading platforms like Polymarket and Kalshi. But beyond the hype, there is only one truly important question: which teams are solving core structural issues, and which are merely riding the wave.

From a market structure perspective, the most noteworthy focus remains on how to compress spreads and increase open interest. Even though market creation currently leans towards permissioned systems, the overall liquidity on both the market-making and trading sides of prediction markets remains thin.

Whether it’s better order routing mechanisms, more suitable liquidity models, or improving capital efficiency through lending, there is significant room for improvement in these areas, which will determine whether products can truly scale. The structure of trading categories will also directly impact platform competitiveness. For example, Kalshi saw over 90% of its trading volume in November come from sports markets, indicating a natural advantage in a specific liquidity structure. Meanwhile, Polymarket's trading volume in crypto and political-related markets is significantly ahead, reaching several times that of Kalshi. Even so, on-chain prediction markets still have a considerable gap to bridge before reaching true mainstream scale.

The 2025 Super Bowl serves as an intuitive comparison: in just one day, the trading volume of traditional off-chain betting platforms reached $23 billion, far exceeding the total daily volume of all on-chain prediction markets combined.

To close this gap, it will not be through marketing or narratives, but through teams that can genuinely solve structural issues. This is also the most worthwhile aspect to continue observing in the coming year.

Agent-Type Curators Will Scale DeFi

In the asset management layer of DeFi, there are two extreme models: pure algorithmic (hard-coded interest rate curves, fixed rebalancing rules) or purely manual (risk committees, active fund managers). Agent-type curators represent a third model: they do not simply execute preset rules but continuously assess risk, return, and strategy through AI Agents (LLM + tools + feedback mechanisms) and participate in parameter setting.

Taking the Morpho market as an example, to build a sustainable yield product, it is essential to clarify collateral policies, LTV limits, and risk parameters. Currently, this process heavily relies on human judgment, which naturally presents scalability bottlenecks. The introduction of Agents is essentially an attempt to address this issue.

In the near future, we are likely to see Agent-type curators competing directly with traditional algorithmic models and human managers in the same market.

Regarding the role of AI in trading and asset management, market opinions often swing to two extremes: either it will quickly replace human traders, or it cannot cope with the uncertainties of real markets at all.

However, the real change lies not in "replacement" itself, but in structural adjustments. Agents are more likely to take on roles in strategy design, constraint setting, and portfolio management, rather than directly participating in latency-sensitive underlying execution. As reasoning costs continue to decline, computational power itself will become a new competitive factor.

In this environment, the most advantageous DeFi products may not come from the smartest individuals but from teams capable of scaling intelligent decision-making systems.

Short Videos Are Becoming the New Trading Entry Point

Short videos are becoming the primary entry point for people to discover, understand, and ultimately purchase content.

TikTok Shop achieved over $20 billion GMV in the first half of 2025 and continues to grow rapidly, which itself indicates the strength of the trend.

Instagram is also gradually transforming Reels from a defensive feature into a core business engine. Whatnot's practices further demonstrate the advantages of real-time, personalized content in conversion efficiency, which is significantly higher than traditional e-commerce models.

The underlying logic is not complex. When watching real-time content, it is easier to make quick decisions. As the recommendation stream and settlement process gradually merge, the content itself becomes the trading interface, and creators naturally evolve into distribution nodes. The addition of AI accelerates this process further. The cost of content production continues to decline, testing frequency increases, and platforms begin to optimize conversion efficiency for every second of video.

In this environment, payment systems must be fast enough, cheap enough, and highly composable. Micropayments, automatic revenue sharing, and contribution attribution will all become foundational capabilities.

This is precisely the scenario that crypto systems are naturally suited for. In a business system where streaming is the native form, it is hard to imagine a lack of crypto as the underlying settlement and incentive tool.

Blockchain Is Driving New AI Expansion Paths

In the past few years, AI's attention has primarily focused on the competition between large cloud vendors and leading startups. However, at the same time, a number of crypto-native teams are making substantial progress in distributed training and inference.

These attempts have gradually moved from the theoretical stage to testing and even into production environments. Teams like Ritual, Pluralis, Exo, Odyn, Ambient, and Bagel are at the forefront of this wave of exploration. By training models in a globally distributed environment and combining asynchronous communication with parallel mechanisms, traditional scalability bottlenecks are being redefined.

Meanwhile, new consensus mechanisms and privacy technologies are making verifiable and confidential inference increasingly feasible. Furthermore, some new blockchain architectures are attempting to genuinely combine smart contracts with more general computing structures, providing a foundation for autonomous Agents to operate.

The foundational capabilities are already in place.

The key moving forward is whether it can scale to production-level sizes and prove that this path is not just a conceptual experiment but a genuine way to drive the evolution of AI capabilities.

RWA Is Moving Toward Real-World Scale

The industry has been discussing RWA for many years. However, with the proliferation of stablecoins, the maturation of deposit and withdrawal channels, and the gradual clarification of the regulatory environment, tokenization is finally beginning to enter a scaling phase.

According to data from RWA.xyz, the current on-chain issuance of tokenized assets exceeds $18 billion, while a year ago, this figure was less than $4 billion.

It is essential to clearly distinguish between two models.

Tokenization maps off-chain assets to on-chain; while Vault allows on-chain capital to directly participate in off-chain yields. In the future, the types of assets going on-chain will become increasingly diverse, ranging from commodities, private credit, to stocks, foreign exchange, and even some non-traditional assets.

But the focus is not just on "more types of assets."

The real significance lies in making the originally inefficient and opaque capital allocation process more programmable and liquid through blockchain.

Of course, this process will still face issues such as transfer restrictions, insufficient liquidity, and risk management, so the corresponding infrastructure is also worth paying attention to.

Agent-Driven Product Cycles Are Coming

The core of interaction in the next generation of the internet is shifting from "platform" to "Agent." Whether on-chain or off-chain, automated Agents are already handling a significant proportion of online activities. In the crypto space, they participate in trading, asset management, information filtering, contract auditing, and even content production.

The year 2026 is likely to become a clear turning point.

The design of crypto products will begin to prioritize Agents over human interfaces. The ideal form is not more buttons, but fewer operations. Users only need to issue goals through conversational interfaces, with Agents responsible for information filtering, strategy execution, and result feedback. The infrastructure supporting all of this already exists: open data, programmatic payments, on-chain identities, and cross-chain liquidity.

Compared to Web2, blockchain is more friendly to Agents because they face open interfaces rather than closed systems. This is not just an efficiency improvement but a transformation in the way interactions occur. As search, trading, and execution are gradually taken over by Agents, humans can focus their energy on higher-level judgments.

As more assets and activities go on-chain, this cycle will continue to amplify: opportunities increase, Agents multiply, and value is released.

The only real question left is: are the systems we are building now amplifying value or amplifying noise?

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。