The idea of a universal blockchain is not a recent development. On the contrary, it is a constant reminder that while blockchain technology is transformative, it is not complete until fragmentation becomes a thing of the past, and until it hits critical mass.
It lives rent-free in my head—alongside terms like multichain and cross-chain—not just because it refers to a unified infrastructure that enables smart contracts to access and manage assets and data on any connected chain from a single point of logic, but because it represents the only viable path to seamless, universal blockchain interoperability.
What, then, does funding the future of this unified ecosystem really look like? To understand the significant roles incubation and investment play in transforming cross-chain complexity into omnichain simplicity, Olayimika Oyebanji recently sat down with Jessie Zhang, Head of Investment and Incubation at ZetaChain.
It’s nice to chat with you, Jessie. Can you briefly tell us about yourself and your professional background?
It’s great to chat with you too. My path into Web3 wasn’t linear. I started my career in venture capital and private equity, working across the U.S. and Asia, investing in consumer tech, internet platforms, AI and robotics, and early-stage infrastructure.
Before moving into my current role - incubation & investment at ZetaChain, I actually led global marketing for the company for 2 years, spanning pre-TGE, TGE, and post-TGE. That meant shaping our early narrative and go-to-market strategy, while working hands-on with creators, developers, exchanges, and media across the U.S., Asia, UAE and Europe.
Having worked across both capital markets and global execution gave me a unique vantage point. I’ve seen how ideas scale in theory - and how they collide with reality in practice. That combination ultimately led me to my current role, where I focus on investment and incubation at the intersection of Web3 infrastructure and emerging AI use cases.
Where specifically do you see the greatest cost of fragmentation today—is it in capital inefficiency, developer complexity, or security risk?
I think all three are deeply interconnected, but if you trace the problem back to its root, the greatest cost of fragmentation today is capital inefficiency — and that inefficiency is largely created by developer complexity.
When liquidity is split across dozens of chains, what you get isn’t more opportunity, but thinner markets everywhere. Slippage goes up, yields go down, and a lot of capital just sits idle because it’s too costly or too risky to move. For users, that shows up as friction. For builders, it shows up as impossible trade-offs.
From day one, we weren’t just thinking about connecting chains — we were thinking about how to unify liquidity and user experience at the same time. Because without unified liquidity, interoperability is mostly theoretical.
What often gets overlooked is how hard this is for smaller teams. If you’re a startup trying to launch a product across multiple chains, you’re forced to manage liquidity in parallel pools.
To deliver a seamless, low-slippage experience, you need meaningful capital on each chain — which is expensive, operationally complex, and risky. There’s always the threat of impermanent loss, bridge risk, or sudden liquidity shocks. For most teams, that’s simply not sustainable.
So developers end up making compromises: limited markets, higher fees, worse UX. And users pay the price.
Security risk is real, and developer complexity is real — but in many ways, they’re downstream effects. When capital is fragmented, developers have to duplicate logic, stitch together bridges, and maintain multiple deployments.
That increases attack surface and stretches audit resources thin. When capital is more concentrated and flows through a unified system, development becomes simpler and security becomes more focused.
So to me, fragmentation isn’t just a technical inconvenience — it’s an economic tax on the entire ecosystem. Capital inefficiency is the most visible cost, but it’s really a symptom of a deeper structural problem. Fix that structure, and a lot of the other issues start to resolve themselves naturally.
We've seen significant capital poured into basic cross-chain bridges. What single technical or economic factor differentiates an omnichain application from a basic multichain dApp deployed across five different networks?
The difference is where execution and state live. A multichain dApp usually means deploying the same contract across multiple chains and using bridges to move assets between them. Each deployment is still isolated. You’re coordinating copies.
A truly omnichain application has a single execution model. The application logic runs once, and it can natively access assets and data across chains without wrapping or external trust assumptions.
A concrete example is in a multichain setup, liquidity on Ethereum and Solana are separate pools. In an omnichain setup, liquidity is unified at the application level, even though assets remain on their native chains. That difference is massive- technically, economically, and from a UX perspective.
The goal of Omnichain is seamlessness. How does your incubation program mentor projects on designing their user experience and tokenomics to completely abstract away the complexities of cross-chain transactions?
Three signals matter most to us: One, complexity reduction. We try to understand whether this product meaningfully simplify cross-chain behavior for users and developers? Two, cross-chain user retention. Are users engaging with the app as a single experience, or treating chains as silos?
And three, ecosystem composability. We are interested in knowing whther this application become more valuable as more omnichain apps exist. These indicators are far more predictive than short-term TVL.
Our incubation program is intensely focused on abstracting away the underlying complexity. We operate on a philosophy of "Simple UX, Powerful Primitives."
For our UX, we push teams to benchmark against the best non-crypto web experiences. This means eliminating concepts like "switching networks," "wrapping assets," or manual gas management across chains.
For example, we mentor teams on implementing smart contract wallets that can pay gas in any token a user holds, regardless of the native chain, using ZetaChain’s messaging and asset transfer capabilities. The user sees a single transaction, not two or three coordinated steps.
Our tokenomics is based on unified utility. The token should represent value capture across the entire omnichain economy, not just a single chain's liquidity pool. We guide projects to design fee-capture mechanisms that accrue value from all connected chains and integrate governance rights that span the entire application state.
This prevents liquidity and governance from fragmenting, which is a common pitfall for multichain protocols.
When deciding how to allocate capital—between direct equity/token investments in established teams, versus non-dilutive grants for early-stage builders—what is the primary criterion for which funding mechanism is deployed?
It’s more about stage and clarity. Grants work best for early experimentation and new primitives. Direct investment makes sense when a team has product clarity, execution velocity, and long-term alignment with the ecosystem. As we shift our focus to traditional AI companies, we primarily allocate capital through direct equity investments.
How do you balance the need for short-term growth (e.g., TVL spikes) with investing in projects that demonstrate long-term protocol sustainability through fee generation and governance decentralization?
That tension is very real, and honestly, I don’t think there’s a simple formula for it. Short-term metrics like TVL spikes are useful, but we’re very careful not to confuse movement with value.
A sudden jump in TVL can mean incentives are working, or that a new idea has captured attention — and that’s worth paying attention to. But by itself, it doesn’t tell you much about whether the protocol can actually stand on its own.
So one question we always come back to is: what happens when the incentives fade?
When a project is built for the long term, you usually start to see certain behaviors pretty early. Users are willing to pay fees because the product solves a real problem, not just because they’re being subsidized. Governance slowly opens up instead of staying tightly controlled by the core team. And usage doesn’t completely collapse the moment rewards are reduced.
In practice, we’re not against short-term growth at all. We’re happy to support it if it’s clearly being used to bootstrap liquidity, test assumptions, or find real PMF. What we try to avoid is growth that exists purely to make the numbers look good for a moment.
Can you share your experience working across marketing, investment, and incubation at ZetaChain?
Working across marketing, investment, and incubation has given me a very practical, full-stack view of ecosystem building.
Marketing shows you what actually resonates with users. Investment shows you what’s scarce and worth betting on. Incubation shows you what’s genuinely hard to build. When you put those three together, you start to see patterns that aren’t visible from any single function.
As ZetaChain matured as infrastructure, my role naturally shifted toward ecosystem building. I often use this analogy: you don’t see ads for the App Store — you see apps advertising within it. Once the base layer is established, the real question becomes how you enable great applications on top. And there are really two ways to do that: you either co-build alongside teams, or you invest in others who are building.
From an investment perspective, we’re deliberately looking beyond traditional crypto-native teams. A large part of our focus is on Web2 AI companies - teams with real products and real users — where blockchain can meaningfully enhance trust, interoperability, or ownership, rather than being added as an afterthought.
We’ve reviewed deals globally, including teams in the U.S., Southeast Asia, Turkey, and the UAE. Many of these founders aren’t coming from crypto originally, but they’re genuinely open to exploring how blockchain can add real value. Seeing that level of curiosity and openness outside the traditional crypto bubble has given me a lot of confidence in where the industry is headed.
On the incubation side, our focus is much earlier and more exploratory. Incubation at ZetaChain is about new ideas and new applications we believe should exist on top of the protocol, especially ones that are user-first and grounded in real-world use cases.
We care deeply about how people actually use products, not just whether something is technically impressive. A big part of our evaluation is asking whether an application has the potential to spread organically - whether it’s something users would genuinely want to share or return to, rather than something that only works inside a crypto-native audience.
As AI has become increasingly mainstream, our incubation efforts have naturally shifted in that direction. Nearly all of the applications we’re incubating today sit at the intersection of AI and Web3, where blockchain quietly provides trust, ownership, or interoperability under the hood, and AI delivers immediate, tangible value to users.
Over time, this approach is helping us gradually build an AI + Web3 ecosystem- one that’s driven by real usage rather than speculation.
The regulatory environment is evolving. How does your investment strategy assess and mitigate the regulatory risks for omnichain protocols that touch assets and transactions across multiple international jurisdictions?
Right now, most of the projects we evaluate and invest in are Web2 companies, and we invest through cash equity rather than tokens.This significantly reduces regulatory complexity, particularly when compared with Web3 investments across multiple jurisdictions.
As you’ve spent more time investing in AI companies, how has that changed your perspective on where blockchain fits into the broader technology landscape?
Spending more time investing in AI companies genuinely changed how I think about the role blockchain should play going forward. One of the clearest signals for me has been the shift in talent. If you were in San Francisco between 2018 and 2022, Web3 was everywhere.
Many of the most ambitious builders were starting crypto companies, joining protocols, or experimenting with new on-chain primitives. It felt like that was where the frontier was.
But if you come to Silicon Valley today, the conversation has clearly changed. You don’t hear people talking about Web3 nearly as much. The energy, the meetups, the late-night discussions — they’re overwhelmingly around AI.
Most of the strongest engineers, product designers, and researchers are building AI-native companies, focused on shipping at scale and solving real user problems, often without any interest in crypto as an identity or category.
Seeing that shift up close really reset my perspective. It made me realize that Web3 and AI aren’t separate worlds — they’re competing in the same global talent market. And in that market, talent is the real moat. The companies that win are the ones that attract the best people and give them problems that actually matter.
That forced me to rethink something fundamental about blockchain. For a long time, the industry has mostly funded teams that already “speak crypto.” But if blockchain wants to be relevant in the next wave of innovation, it can’t stay inside that loop. It has to become infrastructure that people adopt naturally — sometimes without even thinking of themselves as blockchain companies.
The most impactful applications in the future will likely come from Web2 and AI teams that adopt blockchain because it solves concrete problems — interoperability, ownership, payments — not because they set out to build something “crypto-native.”
So AI didn’t just broaden our investment focus. It clarified the stakes. Blockchain’s future depends on whether it can compete for talent by offering real impact, real scale, and real relevance in the broader technology ecosystem.
You’ve mentioned that many of the teams you evaluate are Web2 AI companies. What signals tell you that a Web2 AI product is a good fit for blockchain infrastructure?
Most Web2 AI products don’t need blockchain, so we’re very selective. The signal usually appears when a product starts accumulating a long-term state — like user context, memory, or assets — that needs to persist across systems rather than live inside a single platform.
On a practical level, we’ve seen that crypto-native incentive mechanisms can be very effective for driving viral growth, and in some cases, they can help platforms quickly bootstrap either the supply or demand side.
We want to avoid making AI “crypto-native.” It’s about recognizing when blockchain solves a real structural problem - interoperability, ownership, trust - and when it can unlock new growth dynamics through incentives. When those conditions are present, infrastructure like ours becomes an enabler rather than a constraint.
Looking ahead, what does success look like for you personally and for the ecosystem you’re trying to build?
For me, success means seeing builders choose blockchain because it makes their product better, not because it’s trendy. If, in a few years, talented Web2 and AI teams naturally reach for universal infrastructure the way they reach for cloud services today, that’s success.
Personally, I want to help build an ecosystem where blockchain is invisible but essential, where AI is powerful but accountable and where users retain ownership over the systems they rely on daily.
That’s the future I’m investing my time and energy in.