The Collapse of InfoFi: Platform Risk and the Future of Crypto-Social Models

The collapse of InfoFi in late 2025 marked a watershed moment for attention-based crypto projects, exposing systemic vulnerabilities in a sector built on speculative incentives and platform-dependent distribution. As over 53% of cryptocurrencies became "dead coins" and 11.6 million tokens failed in a single year, the crisis underscored the fragility of models prioritizing speed over sustainability. This analysis examines the collapse's root causes, the industry's response, and the evolving landscape of crypto-social models, offering insights into their long-term viability.

The Structural Weaknesses of InfoFi

The InfoFi collapse was not an isolated event but a symptom of broader misalignments in both crypto and AI sectors. By 2025, 95% of corporate AI projects failed to deliver measurable returns, despite $30–$40 billion in investment, revealing a parallel "AI bubble" driven by hype over utility. Similarly, crypto projects like Kaito and Cookie relied on incentivizing content creation through token rewards, a model that collapsed when X revoked API access for applications rewarding users for posting. This platform-driven policy shift triggered immediate sell-offs in tokens like KAITO and COOKIE, exposing the narrow, platform-dependent distribution mechanisms that left these projects vulnerable.

The collapse was exacerbated by a "liquidation cascade" in October 2025, when $19 billion in leveraged positions were liquidated within 24 hours-the largest deleveraging event in crypto history. This event highlighted the interconnected risks of speculative tokenomics, AI-generated content flooding platforms with low-quality posts, and governance models lacking transparency.

Industry Reactions and Lessons Learned

In response, projects like Kaito pivoted to new strategies. Founder Yu Hu announced the discontinuation of Kaito's reward-based Yaps system, shifting to Kaito Studio to align with X's policies. Cookie DAO similarly shut down its Snaps creator campaigns to comply with platform rules. These adaptations reflect a broader industry reckoning: attention-based models must evolve from rewarding visibility to fostering credibility and quality content.

However, post-InfoFi metrics reveal mixed results. Kaito's token value plummeted 20% after X's crackdown, while Cookie3 faced similar declines. Despite these challenges, platforms like Xeet and Wallchain introduced AI-driven filters and "Quack" scores to measure organic reach, signaling a shift toward sustainability. The key lesson? Projects must decouple from platform-specific incentives and instead build governance frameworks that prioritize user retention and content quality according to Tiger Research.

Regulatory Innovations and Sustainability Frameworks

The collapse accelerated regulatory innovation, with 70% of jurisdictions advancing stablecoin frameworks by 2025. The U.S. and EU led efforts like the GENIUS Act and MiCA, emphasizing cross-border standards to mitigate systemic risks. These frameworks now require attention-based projects to demonstrate alignment with environmental, economic, and social sustainability goals- a shift supported by blockchain's transparency and traceability features.

For example, Proof-of-Stake (PoS) consensus models gained traction as energy-efficient alternatives to Proof-of-Work, while AI-enhanced smart contracts enabled self-adjusting incentives. Decentralized identity (DID) solutions also emerged, empowering users to control digital identities. These innovations suggest that regulatory clarity and technological adaptability are critical to long-term viability.

Case Studies: Adaptation and Resilience

Post-InfoFi, projects like Kaito and Cookie3 illustrate divergent paths. Kaito reduced customer acquisition costs by leveraging an algorithmic reputation system, focusing on signal over follower count. Cookie3's "Snap" score, derived from on-chain actions and social behavior, attempts to quantify meaningful presence. Meanwhile, Xeet's AI filters and Wallchain's emphasis on organic reach highlight the sector's pivot toward quality metrics.

Yet challenges persist. Tiger Research noted that 86.3% of crypto failures since 2020 stemmed from poor governance and speculative tokenomics. Even projects like MindoAI, which rewards "conviction" through deep engagement, face scrutiny over user retention. The data underscores a harsh reality: without clear mechanisms to evaluate content quality and ensure user loyalty, attention-based models risk becoming short-lived fads.

The Path Forward

For attention-based crypto projects to survive, they must address three pillars:1. Content Quality: AI-driven filters and reputation systems can combat low-value content, but human curation remains essential.2. Financial Sustainability: Tokenomics must align with long-term user value, avoiding fast post-airdrop selling and insider-heavy allocations.3. Regulatory Compliance: Adapting to evolving frameworks like MiCA will require transparent governance and cross-platform interoperability.

Investors should prioritize projects demonstrating these traits. Kaito's CT Wrapped 2025 initiative, for instance, emphasizes credible content metrics, while Wallchain's focus on organic reach suggests a departure from vanity metrics. However, the sector remains fraught with risk, as AI-driven smart contract exploits- simulated attacks on $4.6 million in blockchain funds-highlight the need for robust cybersecurity.

Conclusion

The InfoFi collapse of 2025 was a cautionary tale of speculative excess, but it also catalyzed a necessary evolution in crypto-social models. While regulatory clarity and technological innovation offer hope, the sector's long-term viability hinges on projects' ability to balance attention with accountability. For investors, the lesson is clear: sustainability in this space requires more than catchy tokenomics-it demands a commitment to quality, governance, and adaptability in an ever-shifting landscape.