A brief history of the future of crypto: Seven trends to reshape the industry narrative in 2026

# Translating the Future: 2026 Crypto & Tech Trends to Watch  

By @archetypevc  

Compiled by Dingdang  

**Editor’s Note**: As we step into 2026, the focus of industry narratives is quietly shifting. Structural adjustments are underway in capital flows, infrastructure, user demand, and content distribution. Drawing insights from multiple industry researchers, Archetype has identified several emerging trends that may evolve into key investment windows in the coming year.  

This article, compiled by Odaily Planet Daily, aims to present Archetype’s perspective on the underlying driving forces of next-generation crypto applications and the most critical structural inflection points to monitor in 2026.  

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## When "Chains Built for Apps" Finally Make Sense: The Perfect Timing for Appchains  

By Aadharsh Pannirselvam  

**One-Sentence Summary**: Blockchains deliberately designed, refined, and optimized around specific use cases—built on core primitives—will truly explode in the next 1-2 years.  

The developers, users, institutions, and capital flooding into the blockchain space today are vastly different from those in previous cycles. They have distinct cultures and preferences (i.e., their definition of "user experience"), which often outweigh abstract concepts like "decentralization" and "censorship resistance." Sometimes these needs align with existing infrastructure; other times, they demand entirely different chain architectures.  

For crypto applications targeting non-professional users with abstracted complexity—such as Blackbird and Farcaster—user experience is paramount. Designs once considered heretical three years ago (e.g., node deployment, single sequencers, custom databases) are now the most rational solutions. The same holds for stablecoin chains or trading scenarios hyper-dependent on low latency and price precision (e.g., Hyperliquid, GTE).  

But not all new applications fit this mold.  

Today, a significant countervailing force is growing: demand for "privacy" from institutions and mainstream users. Experience requirements vary drastically across applications, so their underlying chain architectures should not be one-size-fits-all.  

The good news? Assembling a chain tailored to an application’s needs is far simpler than it was two years ago. It now resembles "building a custom PC."  

You could handpick every hard drive, fan, and power cable—but in most cases, this isn’t necessary. Just like choosing Digital Storm or Framework, you can select from a range of highly compatible, customizable presets. If you need a degree of personalization, you can integrate your own components into their pre-tested configurations—balancing stability with flexibility.  

Similarly, when applications can freely assemble and adjust primitives like consensus mechanisms, execution layers, data storage, and liquidity structures, they can create chains with distinct cultural characteristics. This natively supports the application’s own "experience definition," fostering differentiated competitiveness. The difference is akin to that between ToughBooks, ThinkPads, desktop towers, and MacBooks—distinct yet sharing core underlying traits.  

More importantly, each component becomes a tweakable "knob," eliminating the risk of ripple effects and freeing applications from the upgrade cycles of parent protocols.  

With Circle’s acquisition of Informal Systems’ Malachite, the importance of independently controlling "custom block space" has become an industry trend. In the coming year, I expect to see more applications leveraging "default templates" and core modules from providers like Commonware and Delta to quickly launch their own chains and block spaces—similar to using HashiCorp or Stripe Atlas.  

Ultimately, this will allow applications to truly control their cash flow and build moats through chain architectures aligned with user experience.  

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## Prediction Markets Will Keep Innovating (But Only Some Players Will Break Through)  

By Tommy Hang  

Prediction markets are undoubtedly one of the standout application categories in this cycle. Total on-chain trading volume for prediction markets has repeatedly hit new highs, exceeding $2 billion weekly—clearly indicating that this category has taken a critical step toward becoming a mass consumer product.  

Amid the hype, a flood of new projects has emerged to challenge Polymarket and Kalshi. However, identifying "genuine innovation" amid the noise is key to determining which projects deserve focus in 2026.  

From a market structure perspective, I’m most interested in solutions that reduce spreads and boost open interest. While market creation remains permissioned and curated, liquidity in prediction markets is still thin for both market makers and traders. The best paths forward include optimizing routing systems, introducing alternative liquidity models, and improving collateral efficiency through products like lending.  

Categorical trading volume will be a decisive factor for platform success. For example, over 90% of Kalshi’s November volume came from sports markets—proving that certain platforms are naturally better suited to capture specific liquidity pools. In contrast, Polymarket’s volume in crypto and political markets is 5–10 times higher than Kalshi’s.  

Of course, on-chain prediction markets are still far from true "mass adoption." For instance, single-day off-chain betting volume for the 2025 Super Bowl reached $23 billion—more than 10 times the combined daily volume of all on-chain markets.  

Closing this gap will require teams that can truly solve the fundamental challenges of prediction markets. I’ll be closely monitoring these players next year.  

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## Agentic Curators: AI Agents Will Expand DeFi’s Next Layer  

By Eskender Abebe  

Today’s DeFi "curation layer" (asset selection and risk allocation) leans toward two extremes: either fully algorithmic (fixed interest rate curves, preset rebalancing rules) or fully manual (risk committees, active managers).  

Agentic curators represent a third path: AI agents (LLMs + tools + cyclic scheduling) managing the risk and strategies of vaults, lending markets, and structured products—not just executing fixed rules, but "reasoning"—logical deduction about risk, returns, and position strategies.  

Take Morpho’s markets as an example: designing an attractive yield product requires defining collateral rules, LTV limits, and various risk parameters. This remains a human bottleneck today, but AI agents can scale this process. Soon, we’ll see agentic curators competing head-on with algorithmic models and human managers.  

So, when will DeFi’s "Move 37" arrive?  

Many fund managers hold extreme views on AI: either believing LLMs will automate every trading desk or that they’ll collapse immediately in real-world markets. Both overlook the true structural shift: AI agents combine emotionless execution, systematic strategies, consistent policy constraints, and reasoning capabilities—addressing human noise and algorithmic fragility. In the future, LLMs will act as "architects," designing risk frameworks, strategy constraints, and portfolio structures, while high-frequency and sensitive computations will still be executed by deterministic code.  

When the cost of deep reasoning drops to "a few cents," the strongest vaults will no longer be managed by the smartest humans, but by the most powerful computing.  

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## Short Videos Will Become the New "Traffic Gateway"  

By Katie Chiou  

Short videos are becoming the default interface for "global users to discover and purchase content." TikTok Shop’s GMV exceeded $20 billion in H1 2025, nearly doubling year-on-year, acclimating global users to "shopping while watching"—where entertainment doubles as a storefront.  

Instagram has transformed Reels from a defensive product into a core revenue driver. This format delivers greater exposure and accounts for an increasing share of Meta’s projected 2025 ad revenue. Whatnot has proven that real-time, personalized selling can drive conversions at speeds traditional e-commerce cannot match.  

The logic is simple: real-time viewing accelerates decision-making. Every swipe is a potential purchase point. Platforms are thus rapidly blurring the line between "recommendation feeds" and "payment flows"—feeds themselves are the new point of sale, and every content creator is a distribution channel.  

AI will accelerate this trend: reducing video production costs, increasing content volume, and allowing creators and brands to test ideas in real time. More content means more touchpoints, and platforms will have stronger incentives to optimize conversion efficiency every second.  

Crypto aligns perfectly with this shift: faster content demands faster, cheaper, programmable payment rails. As shopping becomes frictionless and embedded directly into content, we need a system that can settle microtransactions, programmatically allocate revenue, and track contributions across complex influence chains. Crypto was built for such processes—it’s hard to imagine the era of hyper-scaled streaming-native commerce without it.  

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## Blockchains Will Drive New AI Scaling Laws  

By Danny Sursock  

In recent years, the AI narrative has been dominated by giants and unicorns, with decentralized innovators long overlooked. Yet behind the spotlight, multiple crypto-native teams have made remarkable progress in "decentralized training and inference"—moving from whiteboard demos to real-world testing and production environments.  

Today, teams like Ritual, Pluralis, Exo, Odyn, Ambient, and Bagel are ready to "take center stage" and embrace their golden age. This new generation of competitors has the potential to exert explosive, orthogonal influence on AI’s foundational trajectory.  

Distributed training environments are breaking existing scaling limits, with asynchronous communication and parallelization proven viable in real-scale training tasks.  

New consensus mechanisms and privacy technologies are making "verifiable" and "confidential" inference a reality.  

Next-gen chain architectures combine "truly intelligent contract systems" with more general computing models, enabling AI agents to use crypto assets as a unified medium of exchange—forming complete autonomous computing loops.  

The groundwork is done.  

The next challenge is scaling these infrastructures to mass production and proving that blockchains can drive fundamental AI innovation—not just serve as buzzwords or fundraising stories.  

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## RWA: Real-World Assets Will Finally Land in the Real World  

By Dmitriy Berenzon  

After years of discussion, RWA (Real-World Assets) is finally seeing large-scale adoption—enabled by the mass popularity of stablecoins, seamless on/off-ramps, and clearer regulatory frameworks. According to RWA.xyz, over $18 billion in various assets have been issued on-chain, up from just $3.7 billion a year ago. This trend will accelerate in 2026.  

It’s important to note that "Tokenization" and "Vaults" are two distinct RWA design patterns: the former digitizes real-world assets, while the latter channels on-chain capital into off-chain yield opportunities.  

In the future, I expect asset tokenization to expand into broader categories: from gold and rare metals to short-term corporate credit, public and private equity, and more global fiat currencies. We can even be "bolder"—eggs, GPUs, energy derivatives, salary advances, Brazilian Treasury bonds, Japanese yen… all can be tokenized.  

At its core, RWA is not about "putting more things on-chain," but upgrading global capital allocation. The high barriers, low transparency, and fragmentation of traditional markets can be redefined on public blockchains—combined with DeFi primitives to enable composability.  

Of course, many assets will still face challenges such as transfer restrictions, insufficient transparency, illiquidity, risk management, and distribution efficiency. Thus, infrastructure solving these issues will be equally critical.  

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## An Agent-Driven Product Renaissance Is Coming  

By Ash Egan  

The core of the next-generation internet will no longer be the apps we scroll through, but the "intelligent agents" we converse with.  

We all know that bots and agents are rapidly growing as a share of all online activity—roughly 50% today, including both on-chain and off-chain interactions. In crypto, bots are increasingly participating in trading, management, assistance, contract scanning, and executing various operations on our behalf—from token swaps and fund management to smart contract audits and game development.  

This is the dawn of the "programmable, agentic internet." And 2026 will be the first year crypto product design is truly "agent-centric" (in a positive, non-dystopian way).  

The future form is still taking shape, but for me, I want to spend less time clicking between pages and more time managing on-chain agents through chat-like interfaces—similar to Telegram, but with "app-specific/task-specific agents" as conversation partners. They will be able to develop and execute complex strategies, automatically gather the most relevant information from the network, and present it as trade results, risks and opportunities to watch, and curated insights. I’ll assign tasks, and they’ll track opportunities, filter out irrelevant noise, and execute at the optimal moment.  

The infrastructure for this vision is already in place on-chain. Combining open-by-default data graphs, programmable microtransactions, on-chain social graphs, and cross-chain liquidity rails, we have everything needed to support a dynamic agent ecosystem. Crypto’s "plug-and-play" nature means agents will face far fewer cumbersome processes and barriers. It’s hard to overstate how much better prepared blockchains are for this agent revolution compared to Web2 infrastructure.  

This may be the key point: this is not just about automation, but true liberation from Web2’s data silos, friction, and unnecessary waiting. We’re already witnessing this transformation in search: roughly 20% of Google searches now include direct AI overviews, and data shows that once users see these overviews, they’re far less likely to click on traditional search results. Manually sifting through pages is becoming obsolete. A programmable, agent-driven web will extend this experience to all the apps we use daily—and I think that’s a wonderful thing.  

In this new era, we will: scroll less mindlessly, make fewer emotional panic trades, and eliminate time zone differences (no more saying "wait for Asia to wake up"). Both developers and ordinary users will interact with the on-chain world more simply and expressively.  

As more assets, systems, and users enter the chain, this cycle will self-reinforce and accelerate. More on-chain opportunities → more deployed AI agents → more unlocked value, and so on. However, what we build now—and how we build it—will determine whether this "agent-driven web" becomes a thin layer of noise and automation, or truly ignites an empowering, vibrant, and innovative product renaissance.  

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The views expressed in this article are solely those of the authors and do not constitute investment advice from this platform. This platform makes no guarantees regarding the accuracy, completeness, originality, or timeliness of the information contained herein, nor shall it be liable for any losses arising from the use or reliance on such information.