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Tiger Research: If I Were the Founder of Kaito, How Would I Make Decisions in the Face of InfoFi’s Upheaval?

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Core Insights

  • Ecosystem Collapse in Three Days: X platform’s policy adjustments destroyed the InfoFi ecosystem within just three days, fully exposing the structural fragility of Web3 projects’ over-reliance on centralized platforms.
  • Five Survival Paths: InfoFi projects currently face five choices: complete shutdown, transformation into a bounty funding platform, adoption of a Korean-style sponsorship model, multi-platform expansion, or evolution into an MCN-style KOL management model.
  • Evolution of InfoFi 2.0: The future model will be more refined and controllable, shifting from “permissionless scaling” to “curated, high-quality collaboration.”
  • Fundamental Challenges: Establishing a fair incentive compensation system and re-proving the intrinsic value of tokens remain chasms the industry must cross.

1. The “Collapse” of InfoFi in Three Days

Tiger Research: If I Were the Founder of Kaito, How Would I Make Decisions in the Face of InfoFi's Upheaval?

Source: X(@nikitabier)

On January 15th, X platform’s Product Lead, Nikita Bier, issued a brief announcement explicitly stating that applications incentivizing users to post via rewards would no longer be permitted to operate on the platform. For the InfoFi sector, this was tantamount to a “death sentence.”

According to the timeline disclosed by Kaito founder Yu Hu, the events unfolded as follows:

  • January 13th: Kaito received an email from X platform hinting at a possible review and requesting clarification.
  • January 14th: X platform sent a formal legal notice, to which Kaito submitted a legal response the same day.
  • January 15th: The official statement was publicly released, and Kaito, along with the entire industry, learned of the final decision simultaneously.

The market reaction was extremely severe, with the price of $KAITO plummeting. The community criticized the team for failing to provide advance warning despite claiming to have contingency plans. Kaito subsequently issued an emergency statement, explaining that they had previously resolved similar disputes through legal channels multiple times, leading them to misjudge the room for negotiation in this incident.

Lesson: A single decision by a centralized company ended an emerging Web3 category within three days. This reality, where the “power of life and death” lies in the hands of others, is suffocating the entire ecosystem.

2. If I Were an InfoFi Founder Now

Does this mean InfoFi has reached a dead end? Projects like Kaito are already preparing their next development plans. However, what is needed now is not a continuation of the old path but a distinctly different version of “InfoFi 2.0.”

If I were the founder of an InfoFi project like Kaito, what practical choices are actually available now? By examining these potential forward paths, we can begin to outline the contours of InfoFi’s next phase.

2.1 Complete Shutdown

This is the simplest and most direct option: cease operations before funds are completely exhausted. In reality, many small and medium-sized projects may enter a “zombie phase”—largely inactive, occasionally posting on social media, and gradually fading from public view.

Since the “product-market fit” (PMF) previously established around the X platform has now vanished, choosing to shut down may be more realistic than continuing to burn cash in search of an elusive new direction. If a project still holds usable data assets, these can be sold to other companies to recover some residual value. Therefore, most smaller-scale InfoFi projects will likely choose this path.

2.2 Bounty-Based Funding Platform

If access to X’s API is no longer possible, another option is to revert to an earlier business model: KOLs directly apply for relevant campaigns, submit content for manual review, and receive rewards upon approval.

Tiger Research: If I Were the Founder of Kaito, How Would I Make Decisions in the Face of InfoFi's Upheaval?

Source: Scribble

The model represented by Scribble is a typical example. Projects post funding tasks in the form of bounties, KOLs create and submit content for platform review, and receive payment upon approval. This is a “submit first, review later” model, not reliant on real-time API tracking.

This structure can be scaled as an open platform: the platform only provides matching intermediation and infrastructure, while individual project teams manage their own campaigns. As more projects participate, the KOL pool expands; the growth of the KOL base, in turn, provides more choices for projects. Its drawback is the high uncertainty for KOLs—if submitted content is rejected, the invested time and effort are wasted. After multiple failures, high-quality KOLs are likely to leave the platform.

2.3 Korean-Style Sponsored Blog Model

Tiger Research: If I Were the Founder of Kaito, How Would I Make Decisions in the Face of InfoFi's Upheaval?

The Korean sponsored blog model follows a “select first, manage later” approach, not post-hoc review. Agencies like Revu have been using this model for over a decade.

The process is very clear: the project sets a target number of participants and launches a campaign; applicants submit applications, and the project selects suitable KOLs based on data like follower count and past performance. Selected KOLs receive clear creation memandulines; after content is published, operations staff review it. If it doesn’t meet standards, revisions are requested; if deadlines are missed, corresponding penalties apply.

In this model, KOLs can effectively avoid wasted effort. Once selected, payment is largely guaranteed as long as guidelines are followed. Unlike bounty-based systems, there’s no risk of being arbitrarily rejected after completing the work. From the project’s perspective, quality control also becomes easier since only pre-vetted participants are chosen.

2.4 Multi-Platform Expansion

If X platform is no longer fertile ground, the next logical choice is to pivot to YouTube, TikTok, and Instagram. In the Web3 space, there is already a strong push to move beyond X. The prevailing view is that real growth requires shifting from platforms dominated by kripto-native users to mass-market channels with broader audiences.

The main advantage of this path is a much larger potential user base than X, especially in emerging markets like Southeast Asia and Latin America where TikTok and Instagram hold significant influence. Additionally, each platform runs on different algorithms, so operations can continue even if one channel is restricted.

However, the trade-off is a dramatic increase in operational complexity. On X, reviewing text-based posts was often sufficient; on YouTube, content length and production quality are crucial; on TikTok, the first three seconds of a video determine its performance; and on Instagram, the execution and format quality of Stories must be evaluated. This requires platform-specific expertise and may even necessitate developing entirely new internal tools. Given the vastly different API policies and data collection methods across platforms, this is practically equivalent to rebuilding the entire project from scratch. Furthermore, policy risks remain ever-present—any platform could suddenly change its rules like X did. However, spreading activities across multiple platforms does significantly reduce dependency on any single one, and for larger projects, this is the only option that offers substantial scalability.

2.5 MCN-Style KOL Management

In the Web2 MCN (Multi-Channel Network) model, a KOL’s brand value is paramount. In Web3, this influence is even more decisive: narratives drive capital, and a single comment from an opinion leader can directly impact token prices.

Successful InfoFi projects have typically cultivated an active and highly loyal KOL community—creators who have grown through months of deep engagement on the platform. The project can retain this group and pivot them towards a data-driven management model, rather than starting from scratch to find creators. This differs from traditional Web2 MCNs that rely on continuously discovering new talent.

An MCN-style structure implies establishing formal contractual relationships, not loose, selective participation. Leveraging accumulated historical data and established relationships, the platform can wield stronger influence within the Web3 ecosystem and negotiate better commercial deals. For InfoFi projects, this requires a robust management system where data becomes the core asset. If KOLs can be precisely guided via data, and projects are provided with professional, data-driven GTM (Go-To-Pasar) strategies, this model offers a lasting competitive advantage.

3. InfoFi 2.0

This collapse of the InfoFi ecosystem leaves two profound lessons for the Web3 world:

  1. The Irony of Decentralization: Many Web3 projects were deeply dependent on the centralized X platform, and a single decision by X was enough to destroy the entire system.
  2. The Limitations of Incentive Design: While reward mechanisms successfully attracted a large number of participants, there was no effective method to control content quality. The proliferation of spam content gave X platform a clear justification for intervention.

Tiger Research: If I Were the Founder of Kaito, How Would I Make Decisions in the Face of InfoFi's Upheaval?

Source: X(@nikitabier)

Does this mean the road for InfoFi has come to an end?

Not entirely. A few projects that found “product-market fit” may survive by altering their business form. They can pivot to multi-platform expansion, curated premium campaigns, or transform into MCN-style management.

InfoFi 2.0 will likely become smaller in scale, more controllable, and more focused on content quality. It will shift from an open, permissionless platform to a strictly curated professional network, taking a form closer to an integrated marketing platform that combines local GTM efforts with components like offline advertising.

However, fundamental questions remain on the table. Joel Mun dari Tiger Research House points out: once reward mechanisms are introduced, participants inevitably seek ways to exploit system loopholes, making a fair incentive structure extremely difficult to design. This speculative behavior leads to low-quality content and creates a negative feedback loop that can break the platform.

Furthermore, researcher David raises a more fundamental issue: he argues that the value maintenance of InfoFi tokens in the past relied more on staking airdrop expectations and belief in a certain narrative than on the platform’s actual performance. Now, both have lost relevance. This leads to a direct question: why should investors buy InfoFi tokens in the future?

For InfoFi 2.0 to truly survive, these questions must be answered clearly and convincingly. If a project cannot align its interests with those of its token holders, it cannot achieve genuine sustainability.

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