The current perception of InfoFi and AttentionFi has received considerable criticism. Many people consider it Spam-to-Earn. The existing model doesn't work for many players in the market.
The goal of AttentionFi is to enable companies to grow in an entirely novel and dozens of times more efficient way, leveraging the scale of LLM automation and the freedom of crypto.
Current InfoFi and AttentionFi Blockers:
Many highly influential people won't post about things they are not familiar with for an unknown economic reward.
Many AI slops from accounts that haven’t even used the products they talk about.
Bot farms pump out tons of junk content. Even if the algo blocks and ignores almost all of it, they keep going because it’s cheap.
How to Unlock The Next 100x in AttentionFi?
We learn from healthy, organically grown companies and apply those models not just to the algorithm, but also to the product itself.
These models rely on mutual selection: influential voices choose companies, and companies choose groups of individuals for aligned growth.
The key is focusing on the voices that matter.
As a result, we’re introducing Gated Programmatic Mindshare Leaderboards - leaderboards designed to give access to individuals who are truly aligned.
The company defines the access rules. For example
Power users of a specific app or protocol
Loyal community members
Accounts below or above a certain level of influence
People with a history of interest in a specific niche
Whitelisted accounts
Accounts with specific onchain activity (e.g. token holders)
This ensures your signal is recognized more clearly, cutting through the noise with precise, granular filtering.
Real Chance to Win For Small Accounts
Gives smaller accounts a real shot to stand out from the 2M+ others in CT - not just through content, but through long-term loyalty, niche influence, power-user behavior, and value contributions like committed holding.
What's Next?
Those leaderboards won't be public at first. Only eligible individuals will have access.
More features for project-to-individual matching are coming soon within the app.