Kaito's Dilemma: When Airdrop Allocation Is Ultimately Controlled by Project Teams, How Can Trust Be Maintained?
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Kaito's Dilemma: When Airdrop Allocation Is Ultimately Controlled by Project Teams, How Can Trust Be Maintained?
Eclipse's "Death Note" and self-built leaderboard, Humanity's mandatory palm print verification, Kaito ecosystem trust cracks deepen.
Navigating Web3 tides with focused insightsBy KarenZ, Foresight News
Kaito, an InfoFi platform, leverages its AI-driven Yap points mechanism to incentivize high-quality content creation and build a sustainable ecosystem of content and attention. However, recent controversies surrounding airdrops for partner projects Eclipse and Humanity—combined with deeper issues around transparency, fairness, and community trust—have placed Kaito under intense scrutiny. These disputes not only challenge the perceived legitimacy of Kaito’s mechanisms but also reflect broader tensions within the cryptocurrency space regarding user incentives and community building.
Airdrop Controversies and Responses from Kaito's Partner Projects
Eclipse’s “Death Note” and Custom Leaderboards
The airdrop from Eclipse, an Ethereum SVM L2 network, has sparked backlash from KOLs and the broader community. Many active, outspoken community members reported receiving no allocation, raising questions about the validity and reliability of Kaito’s data in reflecting genuine engagement.
In response to the controversy, Alucard, Eclipse’s community lead, clarified on July 8 the underlying logic behind their distribution: Eclipse used Kaito data to create a private X leaderboard. "Other projects should follow our example," he stated. "We hope more teams will manually remove haters, multi-project farmers, and airdrop hunters from their lists. Every project should adopt our Death Note model."
Yu Hu, founder of Kaito, added that each project receives comprehensive social analytics from Kaito at the time of snapshot—including contributions, sentiment analysis, influence metrics, historical behavior, reputation, geographic data, and loyalty scores over customizable timeframes. "Each project then makes final allocations based on this data, their own preferences, and Kaito’s recommendations. Some may reward early users, others emphasize loyalty or geography, while some might tolerate trolls. It’s highly customizable—Eclipse was no exception."
This means Kaito’s data serves only as a reference; ultimate allocation decisions rest entirely with the project teams.
Prior to the airdrop, Eclipse OG @Yangsolana revealed that Eclipse had created a “Death Note” blacklist excluding approximately 50,000 wallets. Additionally, the top 1,000 wallets were subject to manual review by the Eclipse team.
Eclipse team members had previously signaled their intent to reward authentic contributors. For instance, Alucard made several pointed remarks:
“Kaito is just a tool—it can’t detect belief or loyalty.”
“Real community members participate actively, contribute meaningfully, hold conviction, and grow with the ecosystem. They want everyone to win together. If you’re farming 30 projects simultaneously, planning to dump tokens and vanish, you’re not part of any community.”
“We’re cooking for the community, not for KOLs.”
“If all you care about is farming and dumping, you’re a parasite killing crypto. We need believers, not mercenaries.”
While these views resonated with long-term supporters, the use of subjective manual curation ignited debates over fairness. Critics questioned: if Kaito’s data is merely advisory, can users’ efforts be arbitrarily dismissed by project teams?
Humanity Adds Palmprint Verification Requirements
Similarly, identity network Humanity faced accusations of “backstabbing users” and implementing extreme anti-farming measures. The project introduced palmprint biometrics on top of existing Kaito points, disqualifying many users from claiming their airdrops.
Yu Hu explained that Humanity had initially announced requirements for fingerprint collection during rewards rollout, but due to lack of ongoing reminders and short timelines, many failed to complete the steps. Certain accounts—even recognized Yappers or Stakers—received nothing because:
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All participants must have completed palmprint verification on the Humanity website before the airdrop checker went live.
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Stakers must also possess a wallet linked to sKAITO/YT-sKAITO holdings.
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Yappers needed to input their claim wallet between the release of the airdrop checker and the start of claims.
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Humanity applied strict anti-Sybil filters in final allocations, primarily based on referral quality.
Prior to distribution, Humanity stated: “Airdrops are meant to reward early adopters and build strong communities. But in practice, they’ve been hijacked by bots, Sybils, and bounty farmers—failing both real users and the projects themselves. That’s why Humanity uses Fairdrop to verify authentic humans, assessing factors like the number of social credentials tied to human identity, whether someone has used the app or scanned their palm at global events, and whether they’ve contributed meaningfully as real individuals within the community.”
Underlying Contradictions in Kaito’s Model
Lack of Transparency and the Farming Vicious Cycle
Kaito has long faced criticism over opacity in data processing, weighting algorithms, and token distribution.
Whether it’s Kaito’s official leaderboard or custom lists built by partner projects, transparency remains insufficient. As a result, point allocation feels like a “black box.”
Today, X is flooded with AI-generated, homogeneous content, pushing genuine creators to the margins. Worse still, this environment fuels a vicious cycle: speculators game the system for profit; authentic users leave when effort no longer matches reward; projects respond with manual reviews and additional verification hurdles, increasing barriers for average participants. Yet full algorithmic transparency risks enabling even more exploitation. Balancing openness with anti-abuse measures remains a key challenge. The “high-quality content ecosystem” Kaito aims to build risks becoming a playground for farm bots instead.
The Identity Crisis of a Data Provider
Kaito founder Yu Hu’s responses to the controversies reveal a core dilemma: although Kaito does not control final airdrop decisions, it bears the brunt of community backlash. Users invest time and energy based on Kaito’s rankings and scoring system, only to potentially receive nothing due to project-specific filters or subjective judgments.
To address this, Yu Hu noted: “Kaito is only six months old and currently operates in a single vertical, but we’ll soon expand into capital formation and other domains. Our influence and binding power will continue to grow.”
Beneath the Surface: Shared Challenges in Crypto Community Building
Kaito’s struggles mirror systemic challenges across the crypto industry. In a volatile market dominated by short-term speculation, projects want airdrops to attract users but fear being exploited and abandoned by mercenary actors. This tension drives increasingly rigid eligibility criteria.
Yet human intervention brings its own risks. Eclipse’s “Death Note” may weed out opportunists but could also silence legitimate critics. Humanity’s palmprint requirement blocks bots but excludes privacy-conscious users. These attempts to enforce fairness end up undermining it—highlighting the industry’s technical and structural limitations in identifying “real contribution” and “long-term conviction.”
Kaito’s Achievements and Roadmap
According to Dune analytics, Kaito AI has distributed $106 million worth of tokens to communities (excluding Kaito’s own airdrop), with over 200,000 monthly active Yappers.
Yu Hu emphasized: “Over the past six months, the platform has helped distribute $100 million in rewards. Most projects have honored their commitments—some even exceeded them—reflecting the Web3 ethos of shared prosperity between projects and users.”
This track record underscores the value of the InfoFi model. However, recurring controversies warn that unresolved issues around transparency and trust could erode user confidence in Kaito.
Recent plans and proposals from Yu Hu and the Kaito team include:
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Distribution responsibility: Kaito strongly recommends that all teams allow Kaito to manage final allocations for Yappers and the Kaito ecosystem directly.
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Signal > Noise: Focus on high-quality content, improve detection of authentic valuable contributions, and enhance ecological sustainability.
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Algorithm refinement: Prioritize real, meaningful discussions in ranking systems.
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Reputation systems: Exploring integration of on-chain reputation to filter AI spam and reward high-quality “authentic” users.
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Real usage integration: Reward not just posting (Yapping), but actual product usage and ownership.
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Culture shift: Move the community away from “point farming” toward long-term co-creation of value.
Additionally, Yu Hu announced earlier this month that Kaito will launch its capital launchpad and gKaito in Q3, along with a new mechanism called Kaito Connect.
Conclusion
The recent controversies reflect the complex relationship between data platforms and projects in the Web3 ecosystem. Eclipse’s “Death Note” and Humanity’s added verification steps expose limitations in Kaito’s current framework, while historical opacity amplifies community frustration. While Kaito’s leadership has clarified misunderstandings and highlighted the platform’s successes in reward distribution, the tension between autonomy and transparency in allocation processes remains unresolved.
In terms of collaboration models, Kaito may need to establish clearer boundaries of responsibility. A standardized data filtering framework could define which metrics are objectively assessed by the platform versus customizable by individual projects. Third-party audit mechanisms could further ensure fairness in distributions.
For project teams, user screening methods should become more user-friendly. Striking a balance between anti-Sybil defenses and protecting legitimate users is crucial—overly strict rules risk alienating potential community members.
Kaito’s current crisis is also an opportunity—to rebuild trust through accountability and innovation. Only by confronting these challenges head-on can the InfoFi model return to its original mission: genuinely incentivizing valuable content creation and community building, and fueling the long-term growth of the crypto industry.
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