Looking for the main investment themes in 2026: Which trends are worth paying attention to?

Compilation: Plain Blockchain

It’s very simple: Chains designed, built, and tuned for applications will shine brightly. Next year’s best application chains will be carefully assembled from primitives and first principles.

The recent wave of developers, users, institutions, and capital entering on-chain is different from before: they possess specific cultures (understood as the definition of user experience), and they value these cultures more than abstract ideals like decentralization and censorship resistance. In practice, sometimes this aligns with our existing infrastructure, sometimes it does not.

For cryptographic abstractions like Blackbird or Farcaster, aimed at non-professionals, the especially important aspects of user experience—those decentralized design decisions that even three years ago seemed radical—such as colocated nodes, single sequencers, and custom databases—are actually very reasonable. The same applies to stablecoin chains and trading venues like Hyperliquid* and GTE that depend on millisecond precision, minimal price fluctuations (ticks), and optimal prices.

But this does not apply to every new application.

For example, balancing this comfort with centralization is growing institutional and retail interest in privacy. The demands and expected experiences of cryptographic applications can be entirely different, and their infrastructure should reflect that.

Fortunately, assembling chains from scratch that cater to these specific user experience definitions is much less complex than two years ago. Today, it’s really no different than assembling a custom PC.

Of course, you can pick each drive, fan, and cable yourself. But if you don’t need that level of granularity (which is likely the case), you can use services like Digital Storm or Framework, which offer a range of prebuilt, customizable PCs for different needs. If you’re somewhere in between, you can add your own parts to their already selected, compatible components. This provides you with greater modularity, flexibility, and the ability to remove components you don’t need, while ensuring the final product runs at a high level.

By assembling and tuning primitives like consensus mechanisms, execution layers, data storage, and liquidity, applications create culturally unique forms that continuously reflect different needs (conceptually: user experience), catering to their target audiences and ultimately preserving value. These forms may look different like ToughBooks, ThinkPads, desktop tower PCs, or MacBooks, but they also tend to converge and coexist—not every such computer has its own unique operating system. More importantly, each essential component becomes a “knob” that applications can iterate and adjust as needed, without worrying about making disruptive changes to the parent protocol.

Given Circle’s acquisition of Malachite under Informal Systems, owning a customized blockchain space and sovereignty are clearly broader priorities. Over the next year, I look forward to seeing applications and teams define and own their chain resources around primitives and sensible defaults provided by companies like Commonware and Delta—a bit like how HashiCorp or Stripe Atlas serve blockchain and native chain space.

Ultimately, this will enable applications to directly own their cash flows and, in their own way, provide the best user experience as a lasting moat.

Prediction Markets Will Continue to Innovate

One of the most acclaimed applications this cycle is prediction markets. As weekly trading volume across all crypto venues hits a record $20 billion, it’s clear this category has made significant strides toward becoming a mainstream consumer product.

This momentum creates a tailwind for adjacent projects aiming to supplement or replace current market leaders like Polymarket and Kalshi. But amid hype, distinguishing genuine innovation from noise will ultimately be the key to determining what’s worth paying attention to in 2026.

From a market structure perspective, I am especially excited about solutions that reduce spreads and deepen open interest. While market creation still requires permissioning and selectivity, liquidity in prediction markets remains relatively thin for makers and takers. There are real opportunities in improving optimal routing systems, different liquidity models, and collateral efficiency through products like borrowing derivatives.

Category-specific trading volume is also a major driver of why some venues outperform others. For example, Kalshi over 90% of November’s trading volume came from sports markets, highlighting that some venues are naturally better positioned to compete for favorable liquidity. In contrast, Polymarket’s trading volume in crypto-related and political markets is more than 5 to 10 times that of Kalshi.

Nevertheless, on-chain prediction markets still have a long way to go before achieving true mass adoption. A good benchmark is the Super Bowl 2025; just this event alone generated $23 billion in off-chain betting volume, which is over 10 times the total daily trading volume of all on-chain markets today.

Bridging this gap will require sharp, inspired teams to solve core prediction market issues. I will be closely watching these participants over the coming year.

Agentic Curators Will Expand DeFi

The curation layer of DeFi sits at two extremes: purely algorithmic (hard-coded interest curves, fixed rebalancing rules) or purely human (risk committees, active managers). Agentic curators represent a third system: AI agents (LLMs + tools + loops) that manage curation and risk strategies in treasuries, borrowing markets, and structured products. They do not just execute fixed rules but reason about risk, reward, and strategy.

Think of the curator role in Morpho markets—someone must define collateral policies, Loan-to-Value (LTV) limits, and risk parameters to generate yield products. Today, that’s a human bottleneck. Agents can extend this. Soon, you’ll see agentic curators competing head-to-head with algorithmic models and human managers.

When will we see the “Move 37” moment in DeFi (referring to the surprising move by AlphaGo against Lee Sedol)?

When I talk to crypto fund managers about AI, I get two answers: either LLMs will soon automate every trading desk, or they’re just “illusion toys” that will never withstand real markets. Both are missing the shift in architecture. Agents will bring emotionless execution, systematic strategy adherence, and flexible reasoning into domains where humans tend to produce noise and pure algorithms are too fragile. They will likely supervise and/or compose lower-level algorithms rather than replace them. LLMs will act as architects designing safety shells, while deterministic code remains in the high-speed (hot latency) path.

As deep reasoning costs drop to a few cents, the most profitable treasuries will not be those with the smartest humans, but those with the most computational resources.

Short-form Video Is the New Storefront

Short videos are rapidly becoming the default interface for discovering (and ultimately purchasing) content people love. TikTok Shop achieved over $20 billion GMV in the first half of 2025, nearly doubling year-over-year, and quietly training global audiences to see entertainment as a storefront.

In response, Instagram has turned Reels from a defensive feature into a revenue engine. This format has generated more impressions and is taking an increasingly larger share of Meta’s advertising revenue expected in 2025. Whatnot has demonstrated that live, personalized sales conversion rates are unmatched by traditional e-commerce.

The overarching principle is simple: when people watch content in real-time, they make decisions faster. Every swipe becomes a decision point. Platforms understand this, which is why the boundary between recommendation feeds and checkout is disappearing. Feeds are the new sales channels, with each creator serving as a distribution node.

AI further accelerates this transformation. It reduces the cost of video production, increases content volume, and makes it easier for creators and brands to test ideas in real-time. More content means more surface area for conversions, and platforms respond by optimizing every second of video to trigger purchase intent.

Cryptocurrency aligns perfectly with this shift. Faster content requires faster, more cost-effective payment rails. As shopping becomes frictionless and embedded directly into content, you need a system capable of settling small payments, programmatically allocating and splitting revenue, and tracking contributions across the chaotic on-chain ecosystem. Cryptocurrency is built for this purpose, and it’s hard to imagine an era of massively scalable, native streaming commerce without it.

Blockchain Will Drive a New AI Scaling Law

Over the past few years, AI has been centered on a multi-billion-dollar arms race among mega-corporations and startups, while decentralized innovators have been lurking in the shadows.

But as attention shifts elsewhere, some crypto-native teams have made significant progress in decentralized training and inference, with the quiet revolution slowly moving from whiteboards to testing and production environments.

Now, teams like Ritual*, Pluralis, Exo*, Odyn, Ambient, Bagel are ready for prime time. This new generation of competitors is expected to unleash explosive orthogonal impacts on the fundamental trajectory of AI.

By training models in globally distributed setups and leveraging new approaches to asynchronous communication and parallelism validated at scale, we can break through scaling constraints.

Combining new consensus mechanisms and privacy primitives makes verifiable and confidential inference a very real option in the on-chain toolkit.

And revolutionary blockchain architectures will combine (true) smart contracts with expressive computational structures, simplifying the use of cryptocurrency as a medium of exchange for autonomous AI agents.

The groundwork has been laid.

The current challenge is scaling these infrastructures into production and demonstrating why blockchains can drive foundational AI innovation beyond philosophy, ideology, or tokenized fundraising experiments.

Real-World Assets (RWAs) Will Achieve Real-World Adoption

We’ve been hearing about tokenization for years, but with mainstream adoption of stablecoins, seamless and powerful on/off ramps, and clearer regulation and support worldwide, we are finally witnessing large-scale adoption of RWAs. According to data from RWA.xyz*, as of writing, tokenized assets issued exceed $18 billion, up from just $3.7 billion a year ago. I expect this momentum to accelerate into 2026.

It’s important to note that tokenization and vaults are different design patterns for RWAs: tokenization creates on-chain representations of off-chain assets, while vaults bridge on-chain capital with off-chain yields.

I’m excited to see tokenization and vaults provide access to a broad range of physical and financial assets—from commodities like gold and rare metals to collateralized credit for working capital and payment financing, to fundraising and public equity, and more global currencies. We should also expand our imagination. I want to see eggs, GPUs, energy derivatives, earned wages, Brazilian bonds, Japanese yen, all on-chain!

It’s crucial to clarify that this is not just about putting more things on-chain. It’s about upgrading how the world allocates capital through public blockchains, making opaque, slow, and siloed markets accessible, programmable, and liquid. Once on-chain, we will enjoy the composability of DeFi primitives we have already built.

Finally, many of these assets will undoubtedly face challenges in transferability, transparency, liquidity, risk management, and distribution, so infrastructure to mitigate these challenges will be equally important and exciting!

An Agentic Product Renaissance Is Coming

The next-generation network will be less influenced by our scrolling platforms and more by the intelligent agents we converse with.

We all know that robots and agents are rapidly increasing their contribution to all network activity. Rough estimates, including on- and off-chain activity, suggest about 50% today. In crypto, robots are increasingly trading for us, curating, assisting, scanning contracts, and taking action—from token trading and treasury management to auditing smart contracts and developing games.

This is the era of programmable, agent-driven networks. While we’ve been in it for some time, 2026 will be the year when crypto product design begins to cater more to robots than humans (in a positive, liberating, non-dystopian way).

What this looks like is still taking shape, but I personally want to spend less time clicking websites and more time interacting via simple chat interfaces where I manage on-chain bots. Imagine Telegram, but with conversations with specific intelligent agents for applications/tasks. They will be able to form and execute complex strategies, search the web for the most relevant info and data, and report trading outcomes, risks, opportunities, and curated insights. I’ll give them a task, and they will track opportunities, filter out noise, and execute at the optimal moment.

The infrastructure for this already exists on-chain. By combining open data graphs and programmable micro-payments with on-chain social graphs and cross-chain liquidity tracks, we have everything needed to support a dynamic ecosystem of intelligent agents. The plug-and-play nature of crypto means less bureaucratic hassle and dead ends for agents. Compared to Web2 infrastructure, the blockchain is more prepared than ever.

And perhaps that’s the most important point: this is not just about automation, but about breaking free from Web2 silos, friction, and waiting. We see this shift in search: about 20% of Google searches now produce an AI overview, and data shows that when people see this overview, their likelihood of clicking traditional search results drops significantly. Manually filtering pages is becoming unnecessary. Programmable, agent-driven networks will extend this further into the apps we use, and I think that’s a good thing.

This era will reduce doomscrolling. Reduce panic trading. Time zone differences will be eliminated (no more “waiting for Asia to wake up”). Interacting with the on-chain world will become easier and more expressive for every developer and user.

As more assets, systems, and users find ways onto the chain, this cycle will compound.

More on-chain opportunities → Deploy more agents → Unlock more value. Repeat.

But what we build now, and how we build it, will determine whether this agent-driven network is merely a layer of noise and automation or a catalyst for a renaissance of empowered, dynamic products.

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