Regarding the airdrop from @humafinance to Kaito Yaper, the intricacies behind it are much deeper than they appear on the surface. Here are three points:
1) The transition from "interaction-based farming" to the "algorithm-based farming" era. In the past, farming relied on "diligence"—opening multiple wallets, increasing interactions, and piling up TVL. Now, we have directly entered an era where "algorithm weight" and Mindshare are what matter.
Platforms like @KaitoAI and @cookiedotfun essentially create a "digital profile" for each KOL, quantifying the value of content, audience quality, interaction efficiency, and other impact dimensions through machine learning.
To some extent, this upgrades the KOL selection mechanism, which originally depended on "insider relationships" and "subjective judgment," to a precision targeting driven by AI data.
However, initial algorithm assessments are often unsatisfactory. For example, it’s possible to engage in small-scale collusion through mutual liking groups, follower boosting, and comment exchanges, leading to a short-term influx of farming studios eager to seize the farming opportunities.
But remember, algorithms can be continuously optimized. Paying attention to the relationship between IP and assets during interactions can help avoid being flagged, but with algorithm-based farming, especially under "black box" conditions, the chances of being flagged only increase. Treating this as a “farming business strategy” requires caution.
2) The "layered differentiation" of the KOL ecosystem on platforms will accelerate. Frankly speaking, top KOLs already have the alpha research capabilities and opportunities to participate deeply in quality projects early on, and can monetize their influence through consulting, investments, and on-chain finance.
Therefore, these major influencers tend to be quite "aloof", posting infrequently and interacting cautiously, which may lead them to be classified as "inactive users" in the eyes of algorithms. Meanwhile, some mid-tier and lower-tier KOLs are frequently reposting, commenting, and interacting daily, achieving high scores in the algorithm's activity ratings.
This actually exposes a core bug in the current algorithm assessment—mistaking "quantity" for "quality" and treating "frequency" as "value". In the short term, this will indeed bring a wave of benefits to those KOLs willing to frequently promote projects.
However, algorithms ultimately need to rely on objective impact assessments to succeed. As algorithms continue to optimize, "interaction frequency" will inevitably give way to the weight of "content value"; otherwise, top KOLs and high-quality projects will leave, which is something platform providers controlling the algorithm black box definitely do not want to see. The key is how to balance content value and interaction frequency, avoiding serious differentiation in KOL resources.
3) The "implicit inflation" of marketing costs for project parties has already begun. On the surface, moving from finding agencies to package KOL resources to directly using platforms like Kaito for precise targeting indeed cuts out the middleman. But what is the reality? Project parties must pay booth fees to participate in this "algorithm arms race," and as competition for bidding positions intensifies, the hidden costs will only rise.
Even worse, algorithms overly rely on quantitative indicators—like the interaction numbers of Smart Followers—while neglecting truly valuable elements, such as content depth, audience quality, and brand match. The issues caused by algorithm bias are quite apparent:
First, marketing ROI declines—airdropping to accounts whose influence value does not match will definitely yield lower conversion results than expected; second, brand reputation risks—overemphasizing interaction quantity over content quality might damage the market perception that project parties have painstakingly established.
Of course, this is also a dynamic game process. Algorithm models will continuously optimize, and project parties can intervene manually, ultimately returning to the two-way match of brand value and user value, allowing the business strategies of algorithm platforms like Kaito and Cookie to truly grow and strengthen.
Note: Personally, I have obtained my Yap points in a very relaxed manner; in the past week, I have clearly felt that content with substance has been weighted more heavily, and my ranking is quite high. Such AI algorithm platforms play a significant role in the allocation of “ecological niches” in the attention economy's Mindshare.
However, it’s best to avoid monopolization; therefore, supporting more platforms like Cookie to join the competitive landscape is very necessary. (I have 10 beta test invitation codes; DM or comment if you need one.)
