Interview with Jessie, Head of Investment and Incubation at ZetaChain: In the AI × Web3 Era, What's Truly Undervalued is Execution

Original | Odaily (@OdailyChina)

Author | Asher (@Asher_ 0210)

As AI becomes a definitive trend, Web3 infrastructure is facing a new watershed moment: should it remain confined within the industry's internal technical narratives, or move towards real users and actual use cases?

In the past cycle, many infrastructure projects attracted a large number of developers but consistently struggled to produce widely adopted applications. "AI × Web3" is not short on narratives; what is truly scarce is transforming those narratives into products and getting enough users to actually use them. Entering the AI era, whether an application possesses real utility has become even more critical. This issue is further amplified, forcing projects to re-examine the relationship between product, growth, and execution.

On January 27, ZetaChain announced the official launch of ZetaChain 2.0, simultaneously introducing its first consumer-facing application—Anuma, a privacy-centric AI interface. The product is now in the testing phase, with a public waitlist open.

Odaily took this opportunity to have an in-depth conversation with Jessie, Head of Investment and Incubation at ZetaChain. The discussion centered on the development path of AI × Web3, the strategic direction of ZetaChain 2.0, and how its first consumer-facing application, Anuma, embodies its product and growth logic. The following are the key takeaways from the interview:

Q1: Could you briefly introduce your background? What experiences led you to choose to deeply engage in the Web3 industry?

I completed my high school and undergraduate studies in the United States. After graduation, I returned to China and worked in the VC industry for three years. What truly prompted my shift to Web3 happened in 2021. On one hand, the traditional VC industry entered a period of relative stagnation with few new structural opportunities. On the other hand, the crypto industry was developing rapidly in 2021. For me, the more important factor wasn't the price increase, but the industry's clear move towards mainstream adoption.

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

Although I had been exposed to the crypto industry as early as 2015-2016, it wasn't until 2021 that I first clearly realized the industry had undergone a qualitative change. It was precisely at that point that I made the decision to formally enter the space.

Q2: As the Head of Investment and Incubation at ZetaChain, what are the core objectives of your department?

From the very beginning, ZetaChain's most core metric has been user count, not capital-centric metrics like TVL. Whether it was when I first joined or during discussions with the founders about the company's mission and vision, the consensus was very clear: ZetaChain aims to build truly consumer-facing, large-scale application-level products. Therefore, "users" have always been the most important criterion.

The focus of market efforts varies at different development stages. Early on, from product launch to token listing and the period thereafter, we primarily focused on building brand awareness and laying the foundational framework. During this phase, we organized a cumulative total of 150 to 200 various offline events globally and facilitated the listing of the token on almost all major exchanges to ensure users in different countries and regions could learn about ZetaChain. The core goal of this stage was to fully open up user "access" and "awareness."

Over the past two years, this phased goal has been largely achieved. Starting last year, with the R&D and gradual rollout of AI-related products, the market objective has also shifted significantly—from "getting more people to know about us" to "truly retaining and serving real users."

This year, we have a very clear goal: to drive at least 500,000 monthly active users for applications within the ZetaChain ecosystem. This is not easy, so the team's current focus is more clearly divided into two parts: one is continuing to advance brand building, and the other is results-oriented, user-growth marketing centered on acquiring and activating real users.

Q3: ZetaChain currently covers over 10 million users. From a market perspective, which data metrics best reflect your judgment that "the product and ecosystem are heading in the right direction"?

In my view, ZetaChain 2.0 is the stage where we truly begin to gain momentum. The most critical point in judging whether the product and ecosystem are on the right track is not the scale of overall on-chain data, but whether the 2.0 products are starting to be genuinely used and accepted by more Web2 users.

In the first two years, as a public chain, our ecosystem development was relatively in a "multi-directional parallel" state—we supported anyone building, regardless of direction. This is a normal stage in the early life of a public chain. But entering 2.0, we made a more definitive choice to focus our efforts on AI-related application directions.

Therefore, the most important metric we now look at to judge direction is the real usage by Web2 users, such as the scale and activity of users actually using the products, and whether sustained usage behavior emerges. From this perspective, the current stage is still a "just beginning to validate" process for us, and these real user data points are key to judging whether this directional choice is correct.

Q4: Behind these key metrics, what do you think is the most underestimated aspect of ZetaChain currently? Is it user scale, technological maturity, or what developers are building?

That's a great question. My answer might sound somewhat "abstract," but I believe it's crucial—the most underestimated aspect of ZetaChain is actually the mindset for long-term building and the capability for sustained execution.

In the current market environment, information is highly transparent. Both users and investors are well aware that the vast majority of projects enter a state of stagnation very quickly after their token launch. Many teams maintain some activity before token unlocks, but after unlocks are complete, regardless of the project's size, innovation and iteration often slow down rapidly or even stop entirely.

Where ZetaChain is relatively different is that we are constantly thinking and experimenting: what directions can truly bring real usage, what innovations can generate long-term user value. Over the past year, we don't guarantee every attempt was successful, but we can say with certainty—we have never stopped product iteration and directional exploration.

In my view, this ability to continuously experiment, rapidly adjust, and keep pushing forward in a complex, even unfavorable market environment is itself a very scarce and valuable competitive advantage. And this is precisely the part most easily underestimated in the market's current perception of ZetaChain.

Q5: ZetaChain initially stood out among interoperable L1s through a more simplified and universal approach, and 2.0 clearly extends this capability to AI. How did you determine that now is the right time to incorporate AI into the core strategy?

Looking at the development of the entire crypto industry, the most successful aspect of Crypto so far has been building a highly open, permissionless system for value and asset circulation. This has been fully validated and has become the industry's most important foundational capability. What follows, whether it's stablecoins, cross-border payments, or more complex data and application forms, is essentially an extension built upon this foundation.

The rapid proliferation of AI is another variable that can no longer be ignored. Over the past year, AI has entered the daily lives of ordinary users at an unprecedented speed, forming extremely high usage frequency and stickiness. This means the generation, use, and concentration of data are being dramatically amplified.

It is precisely against this backdrop that we believe "now" is a very critical juncture. On one hand, AI's dependence on data is deepening; on the other, data centralization brings issues of privacy, security, and control. The market has begun to tangibly feel these contradictions, and this is precisely where decentralized infrastructure can deliver value.

From ZetaChain's perspective, 2.0 is not simply "chasing the AI hype" but an extension of the design philosophy. In the past, we solved interoperability problems in a multi-chain world; today, we face the challenges of data collaboration and privacy in a multi-model era. Essentially, we are always building a cross-system coordination layer—just expanding from between chains to between models.

In our view, AI has become a definitive trend, but the underlying issues of data ownership and privacy remain systematically unresolved. When models become the new infrastructure and data & memory become core assets, privacy is no longer an add-on feature but a structural necessity. Therefore, incorporating AI into the core strategy and building capabilities around data and privacy is a natural extension of the architectural logic, not a directional shift.

This judgment also stems from our team's DNA. ZetaChain core contributor Ankur Nandwani is also the co-creator of Brave and $BAT. Brave, with privacy as its core philosophy, offers users a fast, secure, and tracker-free browsing experience. As of last October, its monthly active users reached 101 million. This long-term commitment to privacy makes us even more confident that in the multi-model era, true infrastructure must simultaneously solve interoperability and data sovereignty issues.

Q6: ZetaChain 2.0 launched its first consumer-facing application, Anuma. As a product that can operate across multiple AI models while preserving user memory, how do you prefer the outside world to view Anuma? Is it a growth product or a window to "instantly understand ZetaChain 2.0"?

For us, Anuma is first and foremost an independent consumer-grade product, not just a showcase window that exists to "explain ZetaChain 2.0."

From product and market perspectives, we made it clear from the start that Anuma's target users are Web2 users, not just Web3 users. Our marketing, product design, and user communication are almost all done according to Web2 product logic—targeting users who are willing to use it long-term and genuinely need the product, not to showcase a technical concept.

ZetaChain 2.0 is more like the underlying infrastructure, solving data, privacy, and collaboration problems; Anuma is the intuitive, usable product form built on top of that for ordinary users. The relationship is one of underlying capability and upper-layer application, but in terms of execution order, we chose to perfect the product itself first.

In this sense, Anuma is not a "façade to explain 2.0" but a product polished entirely to Web2 standards. It's just that we believe, 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 developer is ZetaChain 2.0 currently most prioritizing to attract? Web3-native builders, independent AI developers, or traditional teams in transition?

Currently, we are most focused on independent developers in the AI field and AI teams that already possess certain product capabilities, rather than traditional Web3-native builders.

Our developer strategy itself is not confined to Web3. The reason we chose blockchain as the underlying architecture is that, in terms of data collaboration, privacy protection, and openness, it is currently a more suitable technical choice, not because we want to limit developers to within the crypto industry.

From an execution standpoint, the team is currently dedicating significant effort to collaborating with the AI developer ecosystem, including independent developers and AI startup teams, while investing relatively less in purely Web3 scenarios.

We prefer ZetaChain 2.0 to be understood as a type of underlying technical infrastructure for the AI era: developers can focus on making their products and applications excellent, rather than building around tokens or short-term narratives. This is also why we judge that the AI developer community is a better long-term fit for ZetaChain 2.0's direction.

Q8: In this cycle, many infrastructure projects face a problem: many developers, but few truly successful applications. What do you think is the most important way to avoid path dependency in the ZetaChain 2.0 stage?

I think the most important point is to avoid from the outset the path dependency of "serving only the Web3 internal loop."

In the 1.0 stage, common industry practices involved attracting developers and users through hackathons, token airdrops, etc. However, the results show this model tends to attract short-term, profit-seeking participants rather than teams focused on long-term product refinement and truly serving users. This is why many infrastructures have "many developers, but few successful applications."

Entering 2.0, we made a very clear adjustment to our developer strategy—shifting focus to AI builders with Web2 backgrounds. Whether in terms of ecosystem scale, product capability, or understanding of user needs, the developer base in Web2 and AI fields is more mature and more likely to create products that are genuinely used.

Simultaneously, in terms of user and application growth, we deliberately avoided the "incentive-driven" methods common in the last cycle. Since the goal is to build products for Web2 users, the growth logic must return to Web2—through genuine product strength and user growth methods, not relying on airdrops or short-term incentives.

Ultimately, we place more value on whether developers are motivated by short-term gains or are willing to build applications with real user value based on ZetaChain 2.0's underlying capabilities over the long term. This choice itself is the most important "de-path-dependency" move we've made in the 2.0 stage.

Q9: Standing at this point in time, how do you view the various narratives within the AI × Web3 space? Compared to "which directions are overvalued or undervalued," are you more concerned with another layer of questions?

If I must use "overvalued or undervalued" to describe it, I'd say the problem isn't with the narratives themselves, but with the determination to execute on those narratives.

Over the past two years, I've actually seen many ideas related to AI × Web3. The directions themselves are very good, and many have even been validated in the Web2 world. From a technical perspective, Web3 is indeed a more suitable solution in many scenarios. When these projects first emerged, I would think, "This is a great idea."

But what I find regrettable is that many projects, after actually launching, did not continue to invest resources to truly complete what they initially proposed. The story was told very well, but execution noticeably slowed down or even stalled after the token launch.

So, if there's something overvalued, I think it's the expectation of "long-term execution capability"; and what's undervalued is precisely the willingness to continuously invest, experiment, and truly get things done amidst uncertainty.

This doesn't just happen in AI × Web3; it's a common issue across the entire Web3 industry. Many teams are full of idealism in the early stages, but after achieving some success, fewer are willing to take on long-term risks and reinvest resources to do something even harder.

From an industry development perspective, this short-sightedness is quite unfortunate. Because what truly pushes Web3 towards mainstream adoption is never a particular narrative, but teams willing to take a good direction and pursue it diligently and steadfastly over the long term.