2026 Seven Major Future Trends: From Application Chain Revival to AI-Driven Crypto Networks

Author: Archetype

Translation: Tim, PANews

As we approach 2026, the Archetype team is focusing on future technology trends.

Application chains are viable

—Aadharsh Pannirselvam

The reasoning is simple: chains that are carefully designed, built, and optimized for applications will deliver astonishing experiences. The most outstanding application chains next year will innovate from foundational modules and first principles.

Recently emerging developers, users, institutions, and capital differ significantly from previous groups entering the on-chain ecosystem: they pay more attention to practical experience rather than abstract concepts like decentralization and censorship resistance. In practice, this cultural demand sometimes aligns with existing infrastructure and sometimes conflicts with it.

For applications like Blackbird or Farcaster, which target everyday users and hide technical details of encryption, certain aspects of user experience are especially important. Even some centralized design decisions that three years ago were considered rebellious—such as node co-location, single sequencers, and customized databases—are now seen as reasonable choices. The same applies to projects like Hyperliquid and GTE, whose success often depends on millisecond speeds, minimal price fluctuation units, and optimal pricing.

But not all new applications are suitable.

For example, while people find centralized solutions reassuring, there is a balancing force: increasing numbers of institutions and individuals are paying attention to privacy. The demand and user experience of encryption apps can be entirely different, necessitating different underlying infrastructure.

Fortunately, creating specific chains from scratch to meet user needs has become far less complex than two years ago. In fact, today the process is similar to assembling a custom PC.

Of course, you can select each hard drive, fan, and cable yourself. But if you don’t need such detailed customization (which is often the case), you can choose service providers like Digital Storm or Framework, which offer various pre-configured custom PC options tailored to different needs. If you want a compromise, you can add components yourself on top of the pre-selected setup, with all parts tested for compatibility to ensure high performance. This approach increases modularity and flexibility while eliminating unnecessary components.

When integrating core components such as consensus mechanisms, execution layers, data storage, and liquidity, applications will craft solutions reflecting different cultural traits—these always represent diverse needs (i.e., different definitions of user experience), serving various audiences, and ultimately preserving value. The degree of differentiation can be compared to the difference between a sturdy laptop, a business notebook, a desktop, and a MacBook, but these also blend and coexist to some extent, since these computers do not run entirely independent operating systems. More importantly, each essential component becomes a freely adjustable knob for applications, allowing developers to iterate and adapt without risking disruptive changes to underlying protocols.

The acquisition of Malachite by Circle from Informal Systems indicates that controlling sovereignty over customized blockchain space is clearly a current strategic focus. In the coming year, I look forward to various applications and development teams defining and owning their on-chain components based on foundational modules and default configurations provided by companies like Commonware and Delta. This is akin to creating HashiCorp or Stripe Atlas for blockchain and on-chain space.

Ultimately, this will enable applications to directly control their cash flows and leverage the unique advantages of their constructed modes, providing the best user experience in their own way, and building lasting competitive moats.

Prediction markets will continue to innovate (though only some will succeed)

—Tommy Hang

In this cycle, prediction markets are among the most prominent applications. With daily trading volumes soaring to a record $20 billion across major platforms, prediction markets are clearly making substantial strides toward mainstream adoption.

This momentum has driven many related projects, aiming either to address shortcomings of current market leaders like Polymarket and Kalshi, or to challenge their dominance. But amidst market buzz, only by discerning genuine innovation from market noise can we clearly identify the trends worth watching in 2026.

From a market structure perspective, I pay particular attention to solutions that reduce spreads and increase open interest. Although market creation remains permissioned and selective, liquidity in prediction markets is still relatively weak for market makers and traders. There are real opportunities in improving routing systems through lending products, innovating liquidity models, and enhancing collateral efficiency.

Trading volume across different segments is also a key factor in the competitiveness of platforms. For example, over 90% of Kalshi’s trading volume in November came from sports prediction markets, highlighting its natural advantage in gaining liquidity in certain niches. In contrast, Polymarket’s trading volume in crypto-related and political markets reaches five to ten times that of Kalshi.

However, on-chain prediction markets still have a long way to go before achieving widespread adoption. A highly illustrative example is the 2025 Super Bowl: the event alone generated $23 billion in on-chain betting volume in a single day, exceeding the total daily trading volume of all existing on-chain markets by more than ten times.

Bridging this gap requires sharp, insightful teams to solve core issues in prediction markets. I will closely follow the development of such teams over the next year.

Autonomous curators will expand the DeFi market size

—Eskender Abebe

The curation layer of DeFi currently exists at two extremes: purely algorithmic (hardcoded interest rate curves, fixed rebalancing rules) or purely manual (risk committees, active managers). Autonomous curators represent a third mode: managed by AI agents (large language models + toolchains + decision loops) overseeing vaults, lending markets, and structured products, incorporating not only fixed rules but also reasoning about risk, return, and strategies.

Take curators in the Morpho market as an example: they need to define collateral policies, loan-to-value caps, and risk parameters to design yield-bearing products. Currently, this is still bottlenecked by reliance on human input, but AI agents can enable scalable expansion. Soon, autonomous curators will compete directly with algorithmic models and human managers.

When will we see “god-level” moves in DeFi?

When I talk to crypto fund managers about AI, the answers usually fall into two camps: either AI language models will soon take over all trading desks, or they are just hallucinating toys incapable of surviving in real markets. Both overlook the paradigm shift at the architecture level. Intelligent agents, executing emotionless, systematic strategies with flexible reasoning, are entering realms where human interference is disruptive and pure algorithms are fragile. They are likely to supervise or integrate underlying algorithms rather than simply replace them. Large language models will act as chief architects designing safety barriers, while deterministic code remains in the core areas requiring low latency.

When deep reasoning costs drop to a few cents, the most profitable crypto vaults will no longer depend on the smartest humans but on who has the strongest computational power.

Short videos become the new marketplace

—Katie Chiou

Short videos are rapidly becoming the primary channel through which people discover (and ultimately purchase) content they love. In the first half of 2025, TikTok Shop generated over $20 billion in gross merchandise volume, nearly doubling from previous periods, subtly cultivating a global consumer habit of viewing entertainment content as a new shopping mall.

In response, Instagram has transformed Reels from a defensive feature into a revenue engine. This format not only boosts exposure but also significantly contributes to Meta’s advertising revenue expectations for 2025. Live shopping platforms like Whatnot have long demonstrated that live sales driven by charismatic hosts have conversion rates far surpassing traditional e-commerce.

The core logic is simple: when people watch content in real-time, decision speed accelerates markedly. Every swipe becomes a decision point. Major platforms understand this well, leading to rapid blurring of boundaries between recommendation feeds and checkout flows. The feed becomes a new shelf, with each creator acting as a sales channel.

Artificial intelligence takes this trend further. It lowers video production costs, increases content volume, and enables creators and brands to test ideas more easily and in real-time. More content means more opportunities for conversion, and platforms optimize every second of video to maximize users’ purchase intent.

Encryption technology is born for this paradigm shift. Faster content pacing demands quicker, cheaper payment channels. When shopping becomes seamless and embedded directly into content, a system capable of settling micro-payments, programmatically distributing revenues, and tracking contributions across complex collaboration chains is essential. Encryption technology was designed for this mode of capital flow; it’s hard to imagine achieving a truly scalable, deeply integrated e-commerce era without it.

Blockchain will drive a new AI arms race

—Danny Sursock

In recent years, the spotlight in AI has focused on multi-arm races among large enterprises and startups, with DeAI entrepreneurs operating in the shadows.

However, as external attention shifts elsewhere, several native crypto teams have made significant progress in decentralized training and inference, moving from theoretical design to testing and production environments.

Today, teams like Ritual, Pluralis, Exo, Odyn, Ambient, Bagel, and others are entering a golden age of development. A new wave of competitors is poised to unleash explosive multi-dimensional impacts on the foundational trajectory of artificial intelligence.

Models trained in globally distributed environments can break scalability bottlenecks. These models utilize innovative asynchronous communication and parallel processing methods, which have proven effective in production-scale testing.

The integration of emerging consensus mechanisms and privacy-preserving computation components makes verifiable confidential inference a practical option for on-chain developer toolkits.

Revolutionary blockchain architectures that combine smart contracts with flexible computing structures provide efficient environments for autonomous AI agents, using encrypted assets as exchange mediums.

Foundational work has been completed.

The current challenge is scaling these infrastructure layers to production levels and demonstrating why blockchain technology can drive fundamental AI innovation, rather than remaining at the philosophical, ideological, or metaphysical fundraising experiment stage.

RWA will see real adoption

—Dmitriy Berenzon

Today, RWA tokenization is experiencing scaled applications. Although tokenization has been a hot topic for years, breakthroughs are now happening as stablecoins are broadly accepted in mainstream markets, convenient and stable fiat onramps are improving, and global regulatory frameworks are becoming clearer and supportive. According to the latest data from RWA.xyz, total issuance of tokenized assets across categories has exceeded $18 billion, up from only $3.7 billion a year ago. It’s expected that growth will accelerate further by 2026.

It’s important to distinguish between tokenization and asset pool models: tokenization creates on-chain representations of off-chain assets, whereas asset pools build bridges between on-chain capital and off-chain yields.

I am excited to see that tokenization and vault tech enable access to various physical and financial assets—from commodities like gold and rare metals, to private credit used for operational funding and payments, to private and public equity, and even more global currencies. Let’s brainstorm further. I want to see eggs, GPUs, energy derivatives, salary advances, Brazilian bonds, Japanese Yen, and more—all on-chain.

It’s critical to clarify that this is not merely about putting more assets on-chain. The core is upgrading global capital allocation paradigms via public chain technology, transforming opaque, inefficient, and fragmented markets into open, transparent, programmable, and highly liquid new paradigms. Once these assets are on-chain, we will benefit from their composability with existing DeFi systems.

Finally, these assets will inevitably face challenges related to transferability, transparency, liquidity, risk management, and distribution. Infrastructure capable of alleviating these challenges will be equally important and exciting.

The product renaissance driven by intelligent agents is imminent

—Ash Egan

The influence of the next-generation internet will no longer be determined mainly by the platforms we swipe on, but increasingly by intelligent agents that converse with us.

We all know that bots and agents are rapidly increasing their share in all network activities. Rough estimates suggest they now account for about 50%, including on-chain and off-chain activities. In crypto, bots are trading, strategizing, assisting, scanning contracts, and representing us in everything from token trading and fund management to auditing smart contracts and developing games.

This is the era of programmable, agent-based networks. While we have long been part of it, 2026 will bring a turning point: crypto product design (done in an active, open, non-dystopian way) will more and more be oriented toward robots rather than humans.

Although this vision is still emerging, personally I look forward to reducing the time spent toggling between websites, engaging instead with a simple, chat-like interface to manage on-chain bots. Imagine an experience like Telegram, but with the conversational partner being AI agents specialized for applications or tasks. These agents can formulate and execute complex strategies, gather the most relevant info and data across networks, and report on trades, risks, opportunities, and curated insights. I only need to give commands, and they will lock in opportunities, filter out all distractions, and execute precisely at the optimal moment.

The infrastructure supporting this vision already exists on blockchain. Combining openly accessible data graphs, programmable micro-payments, social graphs, and cross-chain liquidity channels provides everything needed to support a dynamic ecosystem of intelligent agents. The plug-and-play nature of crypto means fewer bureaucratic hurdles, and fewer dead ends for agent operations. Compared to Web2 infrastructure, blockchain is more prepared for this transition than any other.

This may be the most critical point. It’s not just about automation; it’s about liberation from closed Web2 ecosystems, friction, and waiting. We are witnessing this shift in search: now about 20% of Google searches generate AI overviews, which significantly reduce the willingness to click on traditional links once users see these summaries. Manual page filtering is becoming unnecessary. Programmable, autonomous networks will extend this revolution into the apps we use, and I see this as a positive development.

In this era, we will reduce anxiety and frantic trading. Time zones will flatten (no more “waiting for Asian markets to open”). Interacting with the on-chain world will become more convenient and expressive for every developer and user.

As more assets, systems, and users go on-chain, this process will snowball.

More on-chain opportunities → increased deployment of agents → higher value release, in cycles.

But the way we build today will determine whether this intelligent network turns into superficial noise and automation stacking or sparks a renaissance of empowering, dynamic products.