Exclusive Interview with Jessie, Head of Investment and Incubation at ZetaChain: In the AI × Web3 Era, What Is Truly Underestimated Is Execution Power

Original | Odaily Planet Daily (@OdailyChina)

Author | Asher (@Asher_0210)

As AI becomes an inevitable trend, Web3 infrastructure is entering a new watershed: Should we continue to stay within the industry’s internal technical narratives, or move toward real users and practical use cases?

In the last cycle, many infrastructure projects accumulated a large number of developers but struggled to produce applications that gained widespread adoption. “AI × Web3” is not short of narratives; what is truly scarce is transforming these narratives into products and enabling enough users to actually use them. Entering the AI era, whether applications have real utility has become even more critical. This question has been amplified and is forcing projects to re-examine the relationship between product, growth, and execution.

On January 27, ZetaChain announced the official launch of ZetaChain 2.0, along with the release of its first consumer-facing application—Anuma, an AI interface centered on privacy. This product has entered testing and is open for public waitlist.

Odaily Planet Daily took this opportunity to have an in-depth conversation with Jessie, head of investment and incubation at ZetaChain. The discussion covered topics such as the development path of AI × Web3, the strategic direction of ZetaChain 2.0, and how the first consumer application Anuma embodies its product and growth logic. Below are the highlights of the Q&A:

Q1 Could you briefly introduce your background? What experiences led you to focus on Web3?

I completed my high school and undergraduate studies in the U.S. After graduation, I returned to China and worked in venture capital for three years. The real turning point for me to dive into Web3 was in 2021. On one hand, the traditional VC industry was entering a relatively stagnant phase with limited structural opportunities; on the other hand, the crypto industry was rapidly developing, but for me, the more important aspect was not price appreciation but the industry’s clear move toward mainstream acceptance.

I saw traditional institutions—including large banks and consumer brands—begin to engage with crypto assets, NFTs, and on-chain collaborations with Web3 companies, which was hard to imagine before.

Although I had been exposed to crypto since 2015–2016, it wasn’t until 2021 that I truly realized a qualitative change had occurred in the industry. It was at that point I decided to officially enter the space.

Q2 As head of investment and incubation at ZetaChain, what are the core objectives of your department?

From the very beginning, ZetaChain’s most core metric is the number of users, not TVL or other capital-focused indicators. Whether I joined at the start or discussed the company’s mission and vision with the founders, the consensus was very clear: ZetaChain aims to build large-scale, application-level products truly oriented toward C-end users. Therefore, “users” has always been the most important criterion.

At different stages of development, the market focus shifts. In the early phase, from product market entry to token launch and the period afterward, we mainly focused on building brand awareness and laying the foundational ecosystem. During this phase, we organized around 150 to 200 offline events worldwide and pushed the token onto nearly all major exchanges to ensure users in different countries and regions could learn about ZetaChain. The core goal was to open up the “entry points” and “awareness” for users comprehensively.

Over the past two years, this phase has largely been completed. Since last year, with the development and gradual deployment of AI-related products, our market goals have shifted—moving from “making more people know us” to “truly retaining and serving real users.”

This year, we have a very clear goal: to achieve at least 500,000 monthly active users within the ZetaChain ecosystem. This is a challenging target, so our current focus is more clearly divided into two parts: one, continue to promote brand building; two, result-oriented user growth marketing, centered on acquiring and engaging real users.

Q3 ZetaChain has already reached over ten million users. From a market perspective, which data indicators best reflect whether your “product and ecosystem are heading in the right direction”?

In my view, ZetaChain 2.0 is truly the phase where we start to accelerate. Judging whether the product and ecosystem are on the right track, the most critical aspect is not the overall on-chain data volume but whether 2.0 products are being genuinely used and accepted by more Web2 users.

In the past two years, as a public chain, our ecosystem development was relatively “multi-directional”—supporting any kind of development as long as someone was building something. This was normal in the early stage of a public chain. But with the arrival of 2.0, we made a clearer choice: to focus on AI-related applications.

Therefore, the key indicator for us now is the real usage by Web2 users—such as the number of actual users, activity levels, and whether sustained usage behaviors emerge. From this perspective, we are still in the “initial validation” phase, and these real user data are crucial for judging whether this strategic direction is correct.

Q4 Behind these key data points, what do you think ZetaChain is currently most underestimated for? Is it user scale, technological maturity, or what developers are building?

That’s a very good question. My answer might sound somewhat “abstract,” but I believe it’s very critical—what’s most underestimated about ZetaChain is the long-term mindset and continuous execution capability.

In today’s market environment, information is highly transparent. Both users and investors are very aware that most projects tend to stagnate shortly after token launch. Many teams maintain some activity before unlocking tokens, but once unlocked, regardless of project size, innovation and iteration tend to slow down or even stop altogether.

ZetaChain is somewhat different in that we constantly think about and experiment with what directions can truly bring real usage and what innovations can generate long-term user value. Over the past year, we haven’t guaranteed success in every attempt, but one thing is certain—we have never stopped product iteration and strategic exploration.

In my view, this ability to keep trying, quickly adjusting, and pushing forward in a complex and even adverse market environment is a rare and valuable competitive advantage. And this is precisely what the market most tends to underestimate about ZetaChain.

Q5 ZetaChain initially stood out by simplifying and generalizing interoperability across L1s, and 2.0 clearly extends this capability into AI. How do you judge that now is the right time to incorporate AI into your core strategy?

Looking at the entire crypto industry, the most successful achievement so far is building a highly open, permissionless value and asset flow system. This has been fully validated and has become the industry’s most fundamental infrastructure capability. Moving forward, whether it’s stablecoins, cross-border payments, or more complex data and application forms, they are essentially extensions built on this foundation.

The rapid proliferation of AI is another uncontestable variable. Over the past year, AI has entered the daily lives of ordinary users at an unprecedented speed, creating extremely high usage frequency and stickiness. This means data generation, usage, and centralization are being amplified dramatically.

In this context, we believe “now” is a very critical moment. On one hand, AI’s reliance on data is deepening; on the other hand, data centralization raises issues of privacy, security, and control. The market is beginning to genuinely feel these contradictions, and this is where decentralized infrastructure can demonstrate its value.

From ZetaChain’s perspective, 2.0 is not just about “chasing the AI hype,” but a natural extension of our design philosophy. Previously, we addressed multi-chain interoperability; today, we face the challenges of multi-model data collaboration and privacy. Essentially, we are building a cross-system coordination layer—just expanding from chain-to-chain to model-to-model.

In our view, AI has become an inevitable trend, but its underlying data ownership and privacy issues remain unresolved systematically. When models become new infrastructure, data and memory become core assets, and privacy is no longer an add-on but a structural requirement. Therefore, integrating AI into our core strategy and building capabilities around data and privacy is a natural evolution of our architecture, not a directional shift.

This judgment also stems from our team’s DNA. ZetaChain’s core contributor Ankur Nandwani is also co-creator of Brave and $BAT. Brave, with privacy at its core, offers users fast, secure, and tracker-free browsing. As of October last year, it had over 101 million monthly active users. Our long-term commitment to privacy reinforces our belief: in the multi-model era, true infrastructure must address both interoperability and data sovereignty.

Q6 ZetaChain 2.0 launched Anuma, its first consumer-facing app, which can run across multiple AI models and retain user memory. How do you want the outside world to view Anuma? Is it a growth product or a “window to understand ZetaChain 2.0”?

For us, Anuma is first and foremost an independent consumer product, not just a showcase to “explain ZetaChain 2.0.”

From a product and market perspective, we initially targeted Web2 users, not just Web3 users. Our marketing, product design, and user communication are all aligned with Web2 standards—aimed at users who are willing to use the product long-term and genuinely need it, rather than just showcasing technology.

ZetaChain 2.0 is more like the underlying infrastructure, solving issues of data, privacy, and collaboration; while Anuma provides a straightforward, usable product interface on top of that foundation. They are related as foundational capability and application, but in execution, we prioritized building a solid product first.

In this sense, Anuma is not a “face for explaining 2.0,” but a fully Web2-standard product. We believe that, in the current environment, using blockchain to protect data and privacy is the best technical choice to achieve this goal.

Q7 From a market and growth perspective, which type of developers does ZetaChain 2.0 most want to attract now? Web3-native builders, independent AI developers, or traditional teams in transition?

Currently, our top priority is independent AI developers and teams with some product capability in AI, rather than traditional Web3-native builders.

Our developer strategy is not limited to Web3. The reason we chose blockchain as the underlying architecture is because, in terms of data collaboration, privacy, and openness, it is the most suitable technology today—not because we want to restrict developers within the crypto space.

In practice, most of our efforts are focused on collaborating with the AI developer ecosystem, including independent developers and AI startups. Our investment in pure Web3 scenarios is relatively limited.

We want ZetaChain 2.0 to be understood as a foundational infrastructure for the AI era: developers can focus on building products and applications, rather than on tokenomics or short-term narratives. This aligns better with the long-term direction of AI developers and ZetaChain 2.0.

Q8 In this cycle, many infrastructure projects face a common problem: many developers, few applications. What do you see as the most important way to avoid path dependency at ZetaChain 2.0?

I think the most important thing is to avoid “serving only the Web3 internal cycle” from the start.

In the 1.0 phase, the common approach was to attract developers and users through hackathons, token airdrops, etc. But the results show that this tends to attract short-term profit-seekers rather than teams committed to long-term product refinement and user focus. That’s why many infrastructure projects have many developers but few applications.

In 2.0, we made a very clear strategic shift—to focus on Web2 backgrounds, AI builders. From ecosystem scale, product capability, to understanding user needs, Web2 and AI developers are more mature and more likely to produce truly used products.

Meanwhile, in terms of user and application growth, we deliberately avoid the “incentive-driven” methods common in the previous cycle. Since our goal is to build products for Web2 users, growth must return to Web2 principles—relying on real product strength and genuine user acquisition, not airdrops or short-term incentives.

Ultimately, we care more about whether developers are motivated by short-term gains or are willing to leverage ZetaChain 2.0’s underlying capabilities to build applications with real user value for the long term. This choice itself is our most important “de-path-dependency” move in the 2.0 phase.

Q9 Looking at the current moment, how do you view the various narratives in the AI × Web3 space? Compared to “which directions are over- or under-estimated,” do you focus more on a different layer of issues?

If I had to label them as “over- or under-estimated,” I’d say the issue isn’t so much the narratives themselves, but the determination to execute them.

Over the past two years, I’ve seen many ideas related to AI × Web3. The directions are very promising, and many have been validated in Web2 contexts. From a technical perspective, Web3 is indeed a more suitable solution in many scenarios. When these projects first appeared, I thought “this is a great idea.”

But what’s disappointing is that many projects, after going live, did not sustain resource investment to complete what they initially promised. The stories are well told, but after token issuance, the execution slowed significantly or even halted.

So if anything is overestimated, I’d say it’s the expectation of “long-term execution capability.” Conversely, what’s underestimated is the ability to keep investing, trial-and-error, and actually turn ideas into real, long-term user value.

This isn’t limited to AI × Web3 but is a common issue across the entire Web3 industry. Many teams start with idealism, but once they achieve some success, fewer are willing to bear long-term risks and re-invest in more difficult, long-term projects.

From an industry development perspective, this short-sightedness is quite unfortunate. Because what truly pushes Web3 toward mainstream adoption isn’t any single narrative, but teams willing to commit to a good direction and work steadily over the long haul.