Finally, building application chains (Appchains) makes sense

Author: Aadharsh Pannirselvam

Translated by: Blockchain in Plain Language

It's simple: Chains designed, built, and tuned for applications will shine brightly. The best application chains of next year will be carefully assembled based on primitives and first principles.

The recent influx of developers, users, institutions, and capital into the chain is different from before: they possess a specific culture (understandable as: the definition of user experience), and they value this culture more than abstract ideals like decentralization and censorship resistance. In practice, this sometimes aligns with our existing infrastructure, and sometimes it does not.

For crypto abstractions and applications aimed at non-experts, such as Blackbird or Farcaster, particularly important aspects of user experience—those centralized design decisions that seemed heretical even three years ago—such as colocated nodes, single sequencers, and custom databases—actually make a lot of sense. This is also true for stablecoin chains and trading venues like Hyperliquid* and GTE that rely on milliseconds, minimal price fluctuations (ticks), and optimal pricing.

But this does not apply to every new application.

For instance, balancing this comfort with centralization is the growing interest in privacy from institutions and retail. The demand and expected experience for crypto applications can be vastly different, and thus their infrastructure should be as well.

Fortunately, assembling chains from scratch that cater to these specific user experience definitions is far less complex than it was two years ago. Nowadays, it is actually not much different from assembling a custom PC.

Of course, you can pick every single 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 pre-built custom PCs tailored to different needs. If you fall somewhere in between, you can add your own parts to the components they have already selected and know work well together. This provides you with greater modularity, flexibility, and the ability to eliminate components you don’t actually need, while ensuring the final product operates 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 (understandable as: the concept of user experience), catering to their unique target audiences, and ultimately retaining value. These forms can look as different as ToughBooks, ThinkPads, desktop tower PCs, or MacBooks, but they also tend to converge and coexist to some extent—not every such computer has its own unique operating system. More importantly, each necessary component becomes a “knob” that applications can iterate and adjust as needed without worrying about making destructive changes to the parent protocol.

Given Circle's acquisition of Malachite under Informal Systems, having custom block space sovereignty is clearly a broader priority at present. In the coming year, I look forward to seeing applications and teams define and own their chain resources around primitives and reasonable defaults provided by companies like Commonware and Delta, somewhat like the HashiCorp or Stripe Atlas of blockchain and block space.

Ultimately, this will enable applications to directly own their cash flow and leverage the unique forms they build, providing the best user experience as a lasting moat in their own way.

Prediction markets will continue to innovate

One of the most acclaimed applications of this cycle is prediction markets. With weekly trading volumes across all crypto venues reaching a record $2 billion, it is clear that this category has made meaningful strides toward becoming a mainstream consumer product.

This momentum creates a tailwind for adjacent projects aimed at supplementing or replacing current market leaders like Polymarket and Kalshi. But amidst the hype, distinguishing true innovation from noise will ultimately be key to deciding what deserves attention in 2026.

From a market structure perspective, I am particularly excited about those solutions that reduce spreads and deepen open interest. While market creation remains permissioned and selective, the liquidity of prediction markets is still relatively thin for makers and takers. There is a real opportunity to improve optimal routing systems, different liquidity models, and collateral efficiency through products like borrowing.

Volume by category is also a major driver of some venues outperforming others. For example, Kalshi saw over 90% of its trading volume come from sports markets in November, highlighting that certain venues are naturally better positioned to compete for favorable liquidity. In contrast, Polymarket's trading volume in crypto-related and political markets is 5 to 10 times that of Kalshi.

Nevertheless, on-chain prediction markets have a long way to go to achieve true mass adoption. A good reference point is the Super Bowl in 2025; this single event generated $23 billion in trading volume in the off-chain betting market, which is more than 10 times the total daily trading volume of all on-chain markets currently.

Narrowing this gap will require sharp, inspired teams to tackle the core issues of prediction markets, and I will be closely watching these participants in the coming year.

Agentic Curators will expand DeFi

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

Think of the curator role in Morpho markets, where someone must define collateral policies, loan-to-value (LTV) limits, and risk parameters to generate yield products. Today, this is a human bottleneck. Agents can scale it. Soon, you will see agentic curators competing head-to-head with algorithmic models and human managers.

When will we see DeFi's "Move 37" (referring to the unexpected brilliant move made by the Go AI AlphaGo against Lee Sedol)?

When I talk to crypto fund managers about AI, I get one of two answers: either LLMs are about to automate every trading desk, or they are “hallucination toys” that will never withstand the test of real markets. Both views miss the architectural shift. Agents will bring emotionless execution, systematic strategy adherence, and flexible reasoning into areas where humans easily create noise and pure algorithms are too fragile. They are likely to supervise and/or compose lower-level algorithms rather than replace them. LLMs act as architects for designing safe shells, while deterministic code remains on the hot latency path.

As the cost of deep reasoning drops to a few cents, the most profitable treasury will not be the one with the smartest humans but the one with the most computational resources.

Short videos are 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 in gross merchandise volume (GMV) in the first half of 2025, nearly doubling year-over-year, and is quietly training global audiences to view entertainment as a storefront.

In response, Instagram has transformed Reels from a defensive feature into a revenue engine. This format has brought more impressions and is taking an increasingly larger share of Meta's projected advertising revenue for 2025. Whatnot has already proven that live, personalized sales conversion rates are unmatched by traditional e-commerce.

The underlying thread is simple: when people watch content in real-time, they make decisions faster. Every swipe becomes a decision point. Platforms are well aware of this, which is why the boundary between recommendation feeds and checkout processes is disappearing. The feed is the new point of sale, and every creator is a distribution channel.

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

Cryptocurrency fits perfectly with this shift. Faster content requires faster, more cost-effective payment rails. As shopping becomes frictionless and directly embedded into the content itself, you need a system that can settle micro-payments, programmatically allocate and split revenue, and track chaotic impact contributions on-chain. Cryptocurrency is built for such processes, making it hard to imagine a massively scaled streaming-native commerce era without it.

Blockchain will drive new AI scaling laws

In recent years, the focus of AI has been on the billion-dollar arms race between mega-corporations and startup giants, while decentralized innovators have been groping in the shadows.

But as attention shifts elsewhere, some crypto-native teams have made significant strides in decentralized training and inference, and the forefront of this quiet revolution has slowly moved from whiteboards to testing and production environments.

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

By training models in globally distributed settings and leveraging new methods of asynchronous communication and parallelism validated in production-scale operations, we can break scaling constraints.

The combination of new consensus mechanisms and privacy primitives makes verifiable and confidential inference a very realistic option in the toolkit of on-chain builders.

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

The foundational work is done.

The current challenge is to scale these infrastructures to production environments and demonstrate why blockchain can drive foundational AI innovations that transcend philosophy, ideology, or gimmicky fundraising experiments.

Real World Assets (RWAs) will see real-world adoption

We have been hearing about tokenization for years, but with the mainstream adoption of stablecoins, the emergence of smooth and robust deposit and withdrawal channels, and clearer regulations and support globally, we are finally seeing the large-scale adoption of RWAs. According to data from RWA.xyz*, as of the time of writing, the issued tokenized assets have exceeded $18 billion, compared to just $3.7 billion a year ago, and I expect this momentum to accelerate in 2026.

It is important to note that tokenization and vaults are different design patterns for RWAs: tokenization creates an on-chain representation of off-chain assets, while vaults create a bridge between on-chain capital and off-chain yields.

I am excited to see tokenization and vaults providing access to a wide range of physical and financial assets, from commodities like gold and rare metals to secured credit for working capital and payment financing, as well as equity crowdfunding and public equity, and more global currencies. We should also unleash our imagination. I want to see eggs, GPUs, energy derivatives, earned-wage access, Brazilian government bonds, yen, all on-chain!

It needs to be clear that this is not just about putting more things on-chain. It is about upgrading how the world allocates capital through public blockchains, making opaque, slow, and isolated markets accessible, programmable, and liquid. Once they are on-chain, we will enjoy the benefits of composability with the DeFi primitives we have already built.

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

An agent-driven product renaissance is coming

The next generation of the web will be less influenced by the platforms we scroll through and more by the agents we converse with.

We all know that the contribution of bots and agents to all network activity is rapidly increasing. Roughly speaking, including both on-chain and off-chain activities, they account for about 50% today. In the crypto space, bots are increasingly representing us in trading, curating, assisting, scanning contracts, and taking action, covering everything from trading tokens and managing vaults to auditing smart contracts and developing games.

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

What this looks like is still taking shape, but personally, I hope to spend less time clicking through websites and more time interacting with a simple chat interface where I manage on-chain bots. Imagine Telegram, but the conversation partners are specific agents for applications/tasks. They will be able to formulate and execute complex strategies, search the web for the information and data most relevant to me, and report back on trade results, risks and opportunities to watch, and curated information. I will give them a task, and they will track opportunities, filter out all the noise, and execute at the optimal moment.

The infrastructure to achieve this already exists on-chain. By combining default open data graphs and programmatic micropayments with on-chain social graphs and cross-chain liquidity tracks, we have everything needed to support a dynamic agent ecosystem. The plug-and-play nature of cryptocurrency means there are fewer bureaucratic hurdles and dead ends for agents to navigate. The blockchain's readiness for this, compared to Web2 infrastructure, cannot be overstated.

And this may be the most important point here. This is not just about automation; it is about liberation from the Web2 silos, liberation from friction. Liberation from waiting. We are all seeing this shift happening in search: about 20% of Google searches now yield an AI Overview, and data shows that when people see this overview, they are significantly less likely to click on traditional search result links. Manually sifting through pages is becoming unnecessary. The programmable, agent-driven web will extend this further into the applications we use, which I think is a good thing.

This era will help us 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 their way 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 becomes merely a layer of noise and automation or ignites a renaissance of empowerment and dynamic products.

Article link: https://www.hellobtc.com/kp/du/12/6162.html

Source: https://x.com/archetypevc/article/1998814808209240565/media/1998777085293142016

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