If I were the founder of Kaito, how should InfoFi 2.0 survive?

Original Title: What If: I Were the Founder of Kaito?

Original Author: RYAN YOON, TIGER RESEARCH

Original Compilation: Peggy, BlockBeats

Editor's Note: A single API policy change by X caused the InfoFi ecosystem to "collectively shut down" within three days. This collapse not only exposed Web3's deep dependence on centralized platforms but also revealed the other side of incentive mechanisms: the greater the rewards, the faster the farming, and the harder it is to control content quality.

Using Kaito as a case study, this article outlines five potential paths forward for InfoFi projects and suggests that InfoFi 2.0 will likely evolve towards a more controlled model characterized by smaller scale, stronger curation, and a greater focus on quality. Beyond this, a more critical question remains: after the airdrops and narratives recede, what will ultimately support the token value of InfoFi?

The following is the original text:

Key Takeaways

X's policy changes caused the InfoFi ecosystem to collapse within three days, exposing the structural ceiling of over-reliance on centralized platforms.

InfoFi projects currently face five choices: shut down; pivot to a bounty-based task platform; adopt a Korean-style brand-sponsored writing model; expand to multi-platform operations; or transform into an MCN-style KOL management model.

InfoFi 2.0 will likely evolve into a smaller-scale, more controllable model, shifting from "permissionless mass expansion" to "curated collaboration between KOLs and projects."

Two fundamental challenges remain unresolved: how to establish a fair compensation system and how to provide reasonable support for token value.

InfoFi Collapsed in Three Days

Source: X (@nikitabier)

On January 15th, X's product lead Nikita Bier posted a brief update, clearly stating that the platform would no longer allow apps that "reward posting" to continue operating. For InfoFi projects, this was almost equivalent to a death sentence.

According to Kaito founder Yu Hu's recollection, the events unfolded roughly as follows:

January 13th: Kaito received an email from X stating it might enter a review process. The team immediately sent a letter requesting further clarification.

January 14th: X sent a formal legal notice. Kaito submitted its legal response the same day.

January 15th: Nikita Bier's public post was published. Kaito, like everyone else, learned of the final decision almost simultaneously.

The market's reaction was merciless.

$KAITO plummeted rapidly, and the community began accusing the team of "claiming to have contingency plans but failing to warn of risks in advance." That evening, Kaito issued an emergency statement explaining that they had received legal notices from X in the past, which were ultimately resolved by signing new agreements. Therefore, this time the team chose to wait for further communication and negotiation.

But regardless of the explanation, the reality was clear enough: a single decision by X directly ended the entire InfoFi ecosystem. In just three days, an entire sector collapsed, simply because the platform deemed it detrimental to user experience and content quality.

If I Were an InfoFi Project Founder Today

Does this mean InfoFi is over? Projects like Kaito are already preparing for the next steps. But what is truly needed now is not to continue the old model, but to find a different form of InfoFi 2.0.

If I were the founder of an InfoFi project like Kaito, what viable options remain in today's reality? By examining these "feasible" paths, we might be able to sketch out the next phase of InfoFi.

Shut Down

This is the most direct and simplest choice: scale down and cease operations before funds run out. In reality, many small-to-medium projects will likely enter a "zombie state," essentially stopping product updates, occasionally posting a few social media updates, and then slowly fading away.

Since the product's PMF (Product-Market Fit) was built on X, and that foundation has now been pulled away, it makes more business sense to cut losses and exit proactively rather than continue burning money searching for a new direction.

If a project still holds reusable data assets, it could also consider selling them to other companies to recover some value. Precisely for this reason, most small-to-medium-sized InfoFi projects will likely choose this path.

Bounty-Based Task Platform

After losing access to X's API, a viable alternative is to revert to a more "traditional" incentive model: have KOLs directly sign up for campaigns, submit content for manual review, and receive rewards only after approval.

This mechanism is essentially more like early "task platforms" or "bounty campaigns": KOLs proactively apply; project teams manually screen and assign tasks; creators submit content; the platform reviews and approves before settling rewards.

It sacrifices the previous automation and scalability but gains a more controllable execution process. In the context of tightening platform rules, this "less efficient but compliant" approach is ironically more likely to survive.

Source: Scribble

Scribble is a typical case. Project teams publish grants in the form of "bounty tasks," and KOLs create content and submit it for review, receiving rewards only upon approval. This mechanism is not real-time tracking and instant settlement but leans more towards a "submit-review" process model.

This structure has the potential to become an open platform: the platform provides matching and infrastructure support, while specific campaign operations and content management remain the responsibility of individual projects. As more projects join, the KOL pool expands; as the creator base grows, project teams gain more potential collaborators.

But its drawbacks are equally obvious: high uncertainty for KOLs. If content is rejected, the invested time cost is completely sunk. After multiple failures, KOLs are likely to leave the platform.

Korean-Style "Brand Blog" Model

Source: Revu

The Korean "brand blog" model follows a "screen first, manage later" path, unlike bounty platforms which operate on a "create content first, then review" basis. Agencies like Revu have been operating with this model for over a decade.

The process is also clear: the project team first sets a target number of participants and launches a campaign. After creators apply, the project team screens potential KOLs based on data like follower count and historical performance. Selected KOLs receive clear content guidelines and writing requirements. After content is published, operations staff inspect it; if it doesn't meet standards, revisions are requested; failure to submit on time results in penalties or deductions.

The biggest advantage of this model is that creators almost never "work for nothing." As long as they pass the screening and follow the guidelines, the compensation is essentially locked in, avoiding the risk present in bounty mechanisms where "work is done but rejected, resulting in zero return on labor." For project teams, because collaborators are pre-screened, quality management is easier, and overall execution is more controllable.

Multi-Platform Expansion

If X is no longer usable, the next realistic option is to shift the battlefield to platforms like YouTube, TikTok, and Instagram. In fact, within the Web3 circle, "moving beyond X" has long been a consensus: to achieve genuine growth, one must migrate from a community primarily composed of crypto-native users to channels where a broader user base resides.

The biggest advantage of this route is: the potential user scale far exceeds X. Especially in emerging markets like Southeast Asia and Latin America, the influence of TikTok and Instagram might be even stronger. At the same time, different platforms have different content distribution logic; even if one platform restricts access, exposure and operations can be maintained on other channels.

But the cost is a steep increase in operational complexity. On X, only text and interactions needed review; on YouTube, video length and production quality directly determine performance; on TikTok, the first three seconds are almost decisive; on Instagram, Stories, layout, and format completion need evaluation. This requires the team to possess platform-specific operational capabilities or establish new tools and processes. Furthermore, each platform's API policies and data scraping methods differ, equating to "rebuilding the system from scratch."

Policy risks still exist; any platform could change rules suddenly like X did. But a multi-platform strategy at least reduces single-point risk. For larger-scale projects, this is also the only direction that still possesses "scalability potential."

MCN-Style KOL Management Model

In the Web2 MCN model, a KOL's brand value itself determines commercial value; in Web3, this effect is even more extreme. Narratives drive capital flows, the influence of opinion leaders is amplified to the point of directly affecting token prices, and a single comment can trigger volatility.

Some successful InfoFi projects have already cultivated an active and highly aligned KOL community. These KOLs aren't externally recruited temporarily but have gradually grown through months of participation on the platform. Compared to Web2 MCNs relying on continuously "discovering new talent," InfoFi is more likely to retain this existing KOL base and shift the platform's advantage towards data-driven management and distribution.

Becoming MCN-like means shifting the cooperative relationship from a loose "voluntary participation" to more formal contracts and bindings. Leveraging long-accumulated data and relationship networks, the platform's bargaining power within the Web3 ecosystem would also strengthen, making it easier to secure better partnership terms and resource placements.

But this path places higher demands on InfoFi projects: they must have a sufficiently strong management system, and "data" becomes the core asset. If a platform can use data to guide KOLs' production cadence, content direction, and conversion effectiveness, and provide project teams with more professional, data-driven GTM (Go-To-Market) strategies, this model could form a more enduring competitive moat.

InfoFi 2.0

The collapse of InfoFi leaves two important lessons for the entire Web3 ecosystem.

First, the irony of decentralization: many Web3 projects are in fact highly dependent on the centralized platform X, and a single decision by X was enough to crash the entire system.

Second, the boundaries of incentive design: reward mechanisms did successfully attract a large number of participants, but the platform lacked effective quality control measures. Low-quality content and farming behavior rapidly proliferated, giving X ample justification to intervene and ban them.

Source: X (@nikitabier)

Does this mean InfoFi is over?

Not entirely. A few projects that have truly achieved Product-Market Fit (PMF) may still survive by changing their form, such as pivoting to multi-platform expansion, conducting more curated campaign placements, or upgrading to an MCN-style KOL management model.

But InfoFi 2.0 will likely become smaller, more controllable, and place greater emphasis on content quality. It will shift from the previous open, permissionless, scale-seeking "platform form" to a curated collaborative network, more akin to an integrated marketing platform that combines components like localized GTM execution and offline advertising to form a more complete execution loop.

However, fundamental problems persist.

Joel Mun from Tiger Research House points out that once reward mechanisms are introduced, participants will inevitably seek ways to "farm airdrops," making it almost impossible to design a fair incentive structure. Such behavior continuously lowers content quality and creates a negative feedback loop, ultimately harming the platform itself—this is a key challenge InfoFi projects must confront directly.

David raises an even more fundamental question. He believes that the value support for InfoFi tokens stems less from the platform's actual performance and more from "staking airdrops" and "narrative faith." But both have now lost their practical significance, forcing the question into the open: why should investors still buy InfoFi tokens?

If InfoFi 2.0 wants to survive, it must provide clear answers to these questions. A project disconnected from its token holders will ultimately struggle to achieve true sustainability.

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