Kaito Marketing Guide 2026: Turning "Attention" into a Tradable Asset

Over the past year, Web3 projects have increasingly resembled doing one thing in terms of "growth":

While most Web3 growth tools still operate on a task-driven model of "spending-forwarding-airdropping," user growth in practice is often simplified into a rapidly scaling process: first, spend money on advertising to generate exposure; then, increase engagement through forwarding and task completion; and finally, use airdrops or points to complete conversions. This approach may generate impressive data feedback in the short term, but it essentially revolves around one-off actions , and its growth effect is highly dependent on continuous investment , making it difficult to achieve long-term accumulation.

Unlike other approaches, @KaitoAI doesn't simply optimize existing task systems for efficiency; instead, it evolves into a highly structured user growth operating system . It doesn't just rate or award points for content; rather, it reorganizes user expressions and interactions, originally scattered across Twitter(X), into a sustainable growth system through a quantifiable, competitive, and reciprocal attention allocation mechanism.

This article will start with Kaito's internal mechanisms , systematically breaking down how it helps the project achieve user growth, and then use two excellent case studies , @Calderaxyz and @berachain, to verify how these mechanisms are used in the project itself.

I. The essence of Kaito: not a marketing tool, but an "attention allocation system"

The first step to understanding Kaito is to move beyond the perspective of a "marketing platform." Kaito's true positioning is: an InfoFi system that transforms "attention, content contributions, and user behavior" into computable assets.

In traditional growth models, projects typically focus on three core metrics: impressions, clicks , and conversion rates . There's nothing inherently wrong with these metrics, but they implicitly assume that growth has occurred as long as users complete a specified action.

In Web3 scenarios, this premise often doesn't hold true. Growth mechanisms based on task completion can only confirm "whether a behavior occurred," but it's difficult to determine why users acted or whether they have a long-term commitment. This makes growth data easily amplified by the lowest-cost actions, appearing impressive but often showing limited retention and genuine engagement. Furthermore, such mechanisms tend to attract efficiency-driven participants , such as airdrop farmers or bots . To combat Sybil attacks, projects can only continuously increase task complexity and participation barriers, resulting in ever-rising growth costs while potentially excluding truly valuable users due to higher barriers to entry.

It is against this backdrop that Kaito redefined its growth metrics. In the Kaito system, the focus shifts from immediate data generated by a single action to a more long-term and structural quality of engagement . For example, whether a project is repeatedly mentioned in the long-term information flow and forms stable awareness ( Mindshare ), whether it can continuously reinforce the same core narrative instead of being diluted by fragmented voices ( Narrative Control ), and whether users are willing to consistently generate informative content around the same project over a longer period ( Consistent Contribution ).

This also means that Kaito's goal is not to help the project create short-term data peaks, but to ensure that the project occupies a stable and cumulative position in the long-term information flow of Crypto Twitter .

II. How Kaito's growth system works: a three-tiered core mechanism

Kaito's first key design element is Yaps/Yapper Points. Before Kaito, a high-quality tweet had a very short lifespan, rarely generating any long-term value beyond likes and retweets. With Kaito, every piece of content is entered into a user's long-term contribution record, continuously influencing their future earnings through points, ranking, and historical weight. This long-term accounting mechanism directly changes creators' objective function: they no longer solely pursue a single viral tweet, but instead begin cultivating a content identity that can be verified over time.

At the same time, Kaito's algorithm doesn't treat all interactions the same. Yap scoring comprehensively assesses whether content truly adds value to the project, considering semantic depth and originality, relevance to the project's narrative, and whether the interaction comes from a genuinely influential encrypted user. This step represents a crucial correction at the growth level—prioritizing traffic quality over traffic volume, thereby systematically reducing the space for inflated views, fake accounts, and ineffective interactions. Content in Kaito is no longer a one-off expression but gradually evolves into a growth asset that can be valued over the long term.

If Yaps is responsible for "assetizing" content, then Yapper Leaderboard is responsible for transforming that asset into a growth engine . Its value lies not in the ranking itself, but in guiding user behavior towards long-term, high-quality, and highly consistent goals through continuous competition and clear rules.

Rankings heavily rely on the continuity of posts, consistency of narrative, and long-term contribution accumulation. This makes it difficult for short-term attempts to climb the rankings to maintain a long-term advantage, while those who truly understand the project and are willing to invest continuously will naturally rise in the rankings. Meanwhile, Kaito, through algorithmic weighting and incentive design, releases the power of dissemination from centralized operation to the community, allowing positive narratives and in-depth interpretations to be systematically amplified without spiraling out of control . Over time, this mechanism will also gradually organize scattered tweets into an identifiable content pool, enabling new users to quickly identify the core voices, thus providing a foundation for Mindshare's continuous accumulation.

Finally, Kaito pushes growth into a closed loop through Yapper Launchpad and Capital Launchpad . The core logic is simple: to give real weight to those who "speak out for the project" in resource allocation . Content contributions are converted into quotas and airdrops through Leaderboard, ultimately resulting in tokens and participation rights, thus turning attention into real benefits and making high-quality users long-term stakeholders.

III. Case Study: When Kaito is Used as a "Growth System"

Among all of Kaito's success stories, Caldera and Berachain are highly representative not because of their size or popularity, but because they share a highly consistent systemic coupling between their growth goals, content structure, incentive design, and platform mechanisms . This makes Kaito more than just a "traffic amplifier," but rather something embedded in the project's own growth logic.

The following sections will break down these two projects from three perspectives: mechanism adaptation, user behavior shaping, and growth results .

1. Caldera: In the Pre-TGE stage, Kaito is used to filter and retain high-quality users.

Caldera's case is particularly useful for understanding how Kaito helps projects with complex technical narratives achieve high-quality user growth, rather than simply increasing exposure .

Prior understanding and utilization of Kaito algorithm preferences: Before entering the Kaito system, Caldera clearly recognized that Kaito's Yap Points and Leaderboard mechanisms do not naturally favor "spreading content," but rather tend to reward content with high semantic density, strong narrative consistency, and long-term cumulative value .

Based on this understanding, Caldera did not encourage the community to produce "project introduction-style" or "emotionally charged" tweets. Instead, it consciously encouraged the community to create content around a series of highly structured topics, such as the architectural principles of Rollup-as-a-Service, its position in the modular Rollup ecosystem, and its technical relationship with EigenLayer, DA layer, and execution layer. These topics are not only information-dense but also require creators to have a strong understanding of the concepts, naturally reducing the possibility of spam or simplistic content.

From a growth perspective, the core of this step lies in proactively guiding community creative behavior into an "algorithm-friendly zone," rather than letting users exhaust their enthusiasm through trial and error.

By leveraging Leaderboard, Caldera systematically filters high-investment users: Caldera's use of the Kaito Yapper Leaderboard is not merely as a results-displaying tool, but rather as a mechanism for shaping user behavior . During the Pre-TGE phase, Caldera deliberately extends the Leaderboard's lifecycle, making it difficult for any user attempting "short-term arbitrage" to establish a stable position on the charts. Conversely, only creators willing to consistently produce content over weeks or even months, and gradually deepen their understanding, can steadily accumulate an advantage.

This has created a clear filtering effect at the user level: users with low patience and low awareness are naturally eliminated; users with high awareness and high investment gradually concentrate at the top of the list. From the perspective of the growth system, Caldera has actually completed a "community quality filter" by using Kaito's Leaderboard , concentrating limited incentive resources on the group most likely to become long-term users and ecosystem participants.

Structurally linking content contribution with real-world usage: Unlike many projects that merely focus on content incentives, Caldera consciously avoids turning Kaito into a pure "voice-calling arena." During the Leaderboard's operation, Caldera continuously incorporates Testnet deployment, developer tool usage, and real-world interactions with ecosystem DApps into the core of community discussions and content creation, binding "participation in the product" and "participation in the narrative" within the same incentive logic.

These behaviors are not always directly counted in Yap Points, but they are constantly cited, analyzed, and reviewed at the content level, forming an implicit bonus mechanism: users who have actually used the product are more likely to produce content with high semantic density, and this type of content is more likely to be rewarded by the algorithm.

This ultimately creates a highly positive feedback loop: using the product → developing understanding → producing high-quality content → gaining higher weight on Kaito → acquiring more resources and attention → further deepening engagement. This allowed Caldera to cultivate a core user group that both understood the technology and possessed the ability to disseminate it, even before TGE.

2. Berachain: How to use Kaito to maintain long-term Mindshare, rather than a one-off surge in popularity.

If Caldera demonstrates Kaito's capabilities in "Pre-TGE growth of technology-driven projects," then Berachain's case illustrates even better how Kaito can be used to maintain long-term mindshare, rather than a one-off narrative burst.

Treating Kaito as a long-term narrative infrastructure, not a tool for short-term activities: Berachain treats Kaito as a long-term, operational narrative infrastructure. From the outset, the project embraces the natural fluctuations of the leaderboard, rather than attempting to create ranking surges through short-term incentives. This design allows the community content to gradually develop a division of labor: some creators focus on in-depth analysis of the Proof-of-Liquidity (PoL) mechanism, some continuously track ecosystem projects and incentive changes, and others are responsible for translating technical narratives into more communicative cultural and meme-based content. Kaito's algorithm does not enforce a uniform content format but rather accumulates weights over time, ensuring that different types of content that are equally "continuous and relevant" can find their proper place within the system.

Leveraging Smart Followers weighting amplifies the advantages of the core community structure: The Berachain community already possesses a network of highly interconnected and frequently interacting core accounts. Kaito's Smart Followers mechanism effectively amplifies this structural advantage. Interactions from core crypto users and high-reputation accounts provide additional weight to content, thus continuously pushing Berachain discussions to a more influential social network layer. Ultimately, this transforms the previously implicit "core community structure" into an algorithmically identifiable and rewardable growth resource. This is one of the key reasons why Berachain has been able to consistently maintain high Mindshare across multiple timeframes.

By stabilizing incentive expectations, Berachain fosters long-term rather than speculative participation: Instead of promising explicit material rewards at every node, Berachain uses a long-term, predictable Kaito incentive structure to send a signal to the community: long-term participation in narrative building is itself systematically recorded and recognized. Under this expectation, user participation decisions no longer depend on the ROI of a single activity, but are closer to a long-term investment behavior. This psychological shift is crucial for building a highly engaged community.

3. The common logic behind the two cases

Despite the significant differences between Caldera and Berachain in terms of stage, narrative, and product form, they follow a highly consistent set of principles when utilizing Kaito: growth is not achieved through "amplification" but through "filtering"; algorithms are not adversaries but need to be understood in advance and proactively adapted to; and the core role of incentives is to shape long-term behavior rather than stimulate short-term participation.

IV. Mechanism Upgrade: "Value Reassessment" and Reputation Shift in 2026

In early 2026, Kaito officially initiated a paradigm shift—a comprehensive upgrade from 'attention distribution' to 'reputation assetization'. The core of this upgrade lies in the fact that the system no longer focuses solely on 'content creation,' but begins to define 'what kind of participation is worth valuing in the long term.'

The most significant move occurred on January 4, 2026, when Kaito officially announced an upgrade to the entry standards for all leaderboards. This update, by introducing reputation data and on-chain holdings, fundamentally restructured the weighting logic of influence. This means that in the Kaito ecosystem, the "false prosperity" relying solely on AI scripts and automated posting has lost its place. The system begins to forcibly filter out low-quality activities by combining on-chain metrics and social reputation weights, ensuring that every piece of influence has genuine capital backing. Kaito is shifting from measuring "who is speaking" to measuring "who deserves to be taken seriously."

Complementing the algorithmic reshuffling is the formal implementation of the gKAITO governance mechanism. This mechanism marks Kaito's evolution from a growth tool into a reputation-based governance system. Community members are no longer simply traffic contributors, but are deeply involved in the quality control of token issuance through a "five-dimensional model" that evaluates thought leadership, engagement, and cultural contributions. Under the gKAITO framework, content production has transitioned from "traffic behavior" to "reputation assets," and influence is now formally and deeply anchored to governance rights, revenue rights, and investment priorities.